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  • v.34; 2021 Dec

What factors contribute to the meaning of work? A validation of Morin’s Meaning of Work Questionnaire

Anne pignault.

1 Université de Lorraine, Psychology & Neuroscience Laboratory (2LPN, EA7489), 23 boulevard Albert 1er, 54000 Nancy, France

Claude Houssemand

2 University of Luxembourg, Department of Education and Social Work, Institute for Lifelong Learning & Guidance (LLLG), 2 Avenue de l’Université, L-4365 Esch-sur-Alzette, Luxembourg

Associated Data

The datasets generated and/or analyzed during the current study are available from the corresponding author.

Considering the recent and current evolution of work and the work context, the meaning of work is becoming an increasingly relevant topic in research in the social sciences and humanities, particularly in psychology. In order to understand and measure what contributes to the meaning of work, Morin constructed a 30-item questionnaire that has become predominant and has repeatedly been used in research in occupational psychology and by practitioners in the field. Nevertheless, it has been validated only in part.

Meaning of work questionnaire was conducted in French with 366 people (51.3% of women; age: ( M = 39.11, SD = 11.25); 99.2% of whom were employed with the remainder retired). Three sets of statistical analyses were run on the data. Exploratory and confirmatory factor analysis were conducted on independent samples.

The questionnaire described a five-factor structure. These dimensions (Success and Recognition at work and of work, α = .90; Usefulness, α = .88; Respect for work, α = .88; Value from and through work, α = .83; Remuneration, α = .85) are all attached to a general second-order latent meaning of work factor (α = .96).

Conclusions

Validation of the scale, and implications for health in the workplace and career counseling practices, are discussed.

Introduction

Since the end of the 1980s, many studies have been conducted to explore the meaning of work, particularly in psychology (Rosso, Dekas, & Wrzesniewski, 2010 ). A review of the bibliographical data in PsychInfo shows that between 1974 and 2006, 183 studies addressed this topic (Morin, 2006 ). This scholarly interest was primarily triggered by Sverko and Vizek-Vidovic’s ( 1995 ) article, which identified the approaches and models that have been used and their main results.

Whereas early studies on the meaning of work introduced the concept and its theoretical underpinnings (e.g., Harpaz, 1986 ; Harpaz & Fu, 2002 ; Morin, 2003 ; MOW International Research team, 1987 ), later research tried to connect this aspect of work with other psychological dimensions or individual perceptions of the work context (e.g., Harpaz & Meshoulam, 2010 ; Morin, 2008 ; Morin, Archambault, & Giroux, 2001 ; Rosso et al., 2010 ; Wrzesniewski, Dutton, & Debebe, 2003 ). Nevertheless, scholars, particularly those in organizational and occupational psychology, soon found it difficult to precisely identify the meaning of work because it changes in accordance with the conceptualizations of different researchers, the theoretical models used to describe it, and the tools that are available to measure it for individuals and for groups.

This article first seeks to clarify the concept of the meaning of work (definitions and models) before bringing up certain problems involved in its measurement and the diversity in how the concept has been used. Then the paper focuses on a particular meaning of work measurement tool developed in Canada, which is now widely used in French-speaking countries. At the beginning of the twenty-first century, Morin et al. ( 2001 ) developed a 30-item questionnaire to better determine the dimensions that give meaning to a person’s work. The statistical analyses needed to determine the reliability and validity of Morin et al.’s meaning of work questionnaire have never been completed. Indeed, some changes were made to the initial scale, and the analyses only based on homogenous samples of workers in different professional sectors. Thus and even though the meaning of work scale is used quite frequently, both researchers and practitioners have been unsure about whether or not to trust its results. The main objective of the present study was thus to provide a psychometric validation of Morin et al.’s meaning of work scale and to uncover its latent psychological structure.

Meaning of work: from definition to measurement

Meaning of work: what is it.

As many scholars have found, the concept of the meaning of work is not easy to define (e.g., Rosso et al., 2010 ). In terms of theory, it has been defined differently in different academic fields. In psychology, it refers to an individual’s interpretations of his/her actual experiences and interactions at work (Ros, Schwartz, & Surkiss, 1999 ). From a sociological point of view, it involves assessing meaning in reference to a system of values (Rosso et al., 2010 ). In this case, its definition depends on cultural or social differences, which make explaining this concept even more complex (e.g., Morse & Weiss, 1955 ; MOW International Research team, 1987 ; Steers & Porter, 1979 ; Sverko & Vizek-Vidovic, 1995 ).

At a conceptual level, the meaning of work has been defined in three different ways (Morin, 2003 ). First, it can refer to the meaning of work attached to an individual’s representations of work and the values he/she attributes to that work (Morse & Weiss, 1955 ; MOW International Research team, 1987 ). Second, it can refer to a personal preference for work as defined by the intentions that guide personal action (Super & Sverko, 1995 ). Third, it can be understood as consistency between oneself and one’s work, similar to a balance in one’s personal relationship with work (Morin & Cherré, 2004 ).

With respect to terms, some differences exist because the meaning of work is considered an individual’s interpretation of what work means or of the role it plays in one’s life (Pratt & Ashforth, 2003 ). Yet this individual perception is also influenced by the environment and the social context (Wrzesniewski et al., 2003 ). The psychological literature on the meaning of work has primarily examined its positive aspects, even though work experiences can be negative or neutral. This partiality about the nature of the meaning of work in research has led to some confusion in the literature between this concept and that of meaningful , which refers to the extent to which work has personal significance (a quantity) and seems to depend on positive elements (Steger, Dik, & Duffy, 2012 ). A clearer demarcation should be made between these terms in order to specify the exact sense of the meaning of work: “This would reserve ‘meaning’ for instances in which authors are referring to what work signifies (the type of meaning), rather than the amount of significance attached to the work” (Rosso et al., 2010 , p. 95).

The original idea of the meaning of work refers to the central importance of work for people, beyond the simple behavioral activity through which it occurs. Drawing on various historical references, certain authors present work as an essential driver of human life; these scholars then seek to understand how work is fundamental (e.g., Morin, 2006 ; Sverko & Vizek-Vidovic, 1995 ). The concept of the meaning of work is connected to the centrality of work for the individual and consequently fulfills four different important functions: economic (to earn a living), social (to interact with others), prestige (social position), and psychological (identity and recognition). In this view, the centrality of work is based on an ensemble of personal and social values that differ between individuals as well as between cultures, economic climates, and occupations (England, 1991 ; England & Harpaz, 1990 ; Roe & Ester, 1999 ; Ruiz-Quintanilla & England, 1994 ; Topalova, 1994 ; Zanders, 1993 ).

Meaning of work: which theoretical model?

The first theoretical model for the meaning of work was based on research in the MOW project (MOW International Research team, 1987 ), considered the “most empirically rigorous research ever undertaken to understand, both within and between countries, the meanings people attach to their work roles” (Brief, 1991 , p. 176). This view suggests that the meaning of work is based on five principal theoretical dimensions: work centrality as a life role, societal norms regarding work, valued work outcomes, importance of work goals, and work-role identification. A series of studies on this theory was conducted in Israel (Harpaz, 1986 ; Harpaz & Fu, 2002 ; Harpaz & Meshoulam, 2010 ), complementing the work of the MOW project (MOW International Research team, 1987 ). Harpaz ( 1986 ) empirically identified six latent factors that represent the meaning of work: work centrality, entitlement norm, obligation norm, economic orientation, interpersonal relations, and expressive orientation.

Another theoretical model on the importance of work in a person’s life was created by Sverko in 1989 . This approach takes into account the interactions among certain work values (the importance of these values and the perception of possible achievements through work), which depend on a process of socialization. The ensemble is then moderated by an individual’s personal experiences with work. In the same vein, Rosso et al. ( 2010 ) tried to create an exhaustive model of the sources that influence the meaning of work. This model is built around two major dimensions: Self-Others (individual vs. other individuals, groups, collectives, organizations, and higher powers) and Agency-Communion (the drives to differentiate, separate, assert, expand, master, and create vs. the drives to contact, attach, connect, and unite). This theoretical framework describes four major pathways to the meaning of work: individuation (autonomy, competence, and self-esteem), contribution (perceived impact, significance, interconnection, and self-abnegation), self-connection (self-concordance, identity affirmation, and personal engagement), and unification (value systems, social identification, and connectedness).

Lastly, a more recent model (Lips-Wiersma & Wright, 2012 ) converges with the theory suggested by Rosso et al. ( 2010 ) but distinguishes two dimensions: Self-Others versus Being-Doing. This model describes four pathways to meaningful work: developing the inner self, unity with others, service to others, and expressing one’s full potential.

Without claiming to be exhaustive, this brief presentation of the theoretical models of the meaning of work underscores the difficulty in precisely defining this concept, the diversity of possible approaches to identifying its contours, and therefore implicitly addresses the various tools designed to measure it.

Measuring the meaning of work

Various methodologies have been used to better determine the concept of the meaning of work and to grasp what it involves in practice. The tools examined below have been chosen because of their different methodological approaches.

One of the first kinds of measurements was developed by the international MOW project (MOW International Research team, 1987 ). In this study, England and Harpaz ( 1990 ) and Ruiz-Quintanilla and England ( 1994 ) used 14 defining elements to assess agreement on the perception of work of 11 different sample groups questioned between 1989 and 1992. These elements, resulting from the definition of work given by the MOW project and studied by applying multivariate analyses and textual content analyses ( When do you consider an activity as working ? Choose four statements from the list below which best define when an activity is “ working,” MOW International Research team, 1987 ), can be grouped into four distinct heuristic categories (Table ​ (Table1 1 ).

Items used to define the concept of work

BurdenConstraintResponsibility and exchange rationaleSocial contributions

b. if someone tells you what to do

j. if it is not pleasant

m. if you have to do it

a. if you do it in the workplace

c. if it is physically strenuous

h. if you do it at a certain time (for instance from 8 until 5)

d. if it is one of your tasks

g. if it is mentally strenuous

k. if you get money for doing it

1. if you have to account for it

e. if you do it to contribute to society

f. if, by doing it, you get a feeling of belonging

i. if it adds value to something

n. if others profit from it

These items were taken from Ruiz-Quintanilla and England ( 1994 ). The letter in front of each item corresponds to the initial order of the items (MOW International Research team, 1987 )

Similarly, England ( 1991 ) studied changes in the meaning of work in the USA between 1982 and 1989. He used four different methodological approaches to the meaning of work: societal norms about work, importance of work goals, work centrality, and definition of work by the labor force. In the wake of these studies, others developed scales to measure the centrality of work in people’s lives, either for the general population (e.g., Warr, 2008 ) or for specific subpopulations such as unemployed people, on the basis of a rather similar conceptualization of the meaning of work (McKee-Ryan, Song, Wanberg, & Kinicki, 2005 ; Wanberg, 2012 ).

Finally, Wrzesniewski, McCauley, Rozin, and Schwartz ( 1997 ) developed a rather unusual method for evaluating people’s relationships with their work. Although not directly connected to research on the meaning of work, this study and the questionnaire they used ( University of Pennsylvania Work-Life Questionnaire ) addressed some of the same concepts. Above all, they employed the concepts in a very particular way that combined psychological scales, scenarios, and sociodemographic questions. Through these scenarios (Table ​ (Table2) 2 ) and the extent to which the respondents felt like the described characters, their relationship to work was described as either a Job, a Career, or a Calling.

Scenarios used to measure the relationship to work

JobCareerCalling
Mr. A works primary to earn enough money to support his life outside of his job. If he was financially secure, he would no longer continue with his current line of work, but would really rather do something else instead. Mr. A’s job is basically a necessity of life, a lot like breathing or sleeping. He often wishes the time would pass more quickly at work. He greatly anticipates weekends and vacations. If Mr. A lived his life over again, he probably would not go into the same line of work. He would not encourage his friends and children to enter his line of work. Mr. A is very eager to retire.Mr. B basically enjoys his work, but does not expect to be in his current job five years from now. Instead, he plans to move on to a better, higher level job. He has several goals for his future pertaining to the positions he would eventually like to hold. Sometimes his work seems a waste of time, but he knows that he must do sufficiently well in his current position in order to move on. Mr. B can’t wait to get a promotion. For him, a promotion means recognition of his good work, and is a sign of his success in competition with his coworkers.Mr. C’s work is one of the most important parts of his life. He is very pleased that he is in this line of work. Because what he does for a living is a vital part of who he is, it is one of the first things he tells people about himself. He tends to take his work home with him and on vacations, too. The majority of his friends are from his place of employment, and he belongs to several organizations and clubs relating to his work. Mr. C feels good about his work because he loves it, and because he thinks it makes the world a better place. He would encourage his friends and children to enter his line of work. Mr. C would be pretty upset if he were forced to stop working, and he is not particularly looking forward to retirement.

These scenarios were taken from Wrzesniewski et al. ( 1997 , p. 24)

This presentation of certain tools for measuring the meaning of work reveals a variety of methodological approaches. Nevertheless, whereas certain methods have adopted a rather traditional psychological approach, others are often difficult to use for various reasons such as their psychometrics (e.g., the use of only one item to measure a concept; England, 1991 ; Wrzesniewski et al., 1997 ) or for practical reasons (e.g., the participants were asked questions that pertained not only to their individual assessment of work but also to various other parts of their lives; England, 1991 ; Warr, 2008 ). This diversity in the possible uses of the meaning of work makes it difficult to select a tool to measure it.

In French-speaking countries (Canada and Europe primarily), the previously mentioned scale created by Morin et al. ( 2001 ) has predominated and has repeatedly been used in research in occupational psychology and by practitioners in the field. Nevertheless, there has not been a complete validation of the scale (i.e., different forms of the same tool, only the use of exploratory factor analyses, and no similar structures found) that was the motivation for the current study.

The present study

The present article conceives of the meaning of work as representing a certain consistency between what an individual wants out of work and the individual’s perception, lived or imagined, of his/her work. It thus corresponds to the third definition of the meaning of work presented above—consistency between oneself and one's work (Morin & Cherré, 2004 ). This definition is strictly limited to the meaning given to work and the personal significance of this work from the activities that the work implies. Within this conceptual framework, some older studies adopted a slightly different cognitive conception, in which individuals constantly seek a balance between themselves and their environment, and any imbalance triggers a readjustment through which the person attempts to stabilize his/her cognitive state (e.g., Heider, 1946 ; Osgood & Tannenbaum, 1955 ). Here, the meaning of work must be considered a means for maintaining psychological harmony despite the destabilizing events that work might involve. In this view, meaning is viewed as an effect or a product of the activity (Brief & Nord, 1990 ) and not as a permanent or fixed state. It then becomes a result of person-environment fit and falls within the theory of work adjustment (Dawis, Lofquist, & Weiss, 1968 ).

Within this framework, a series of recurring and interdependent studies should be noted (e.g., Morin, 2003 , 2006 ; Morin & Cherré, 1999 , 2004 ) because they have attempted to measure the coherence that a person finds in the relation between the person’s self and his/her work and thus implicitly the meaning of that work. Therefore, these studies make it possible to understand the meaning of work in greater detail, meaning that it could be used in practice through a self-evaluation questionnaire. The level of coherence is considered the degree of similarity between the characteristics of work that the person attributes meaning to and the characteristics that he/she perceives in his/her present work (Aronsson, Bejerot, & Häremstam, 1999 ; Morin & Cherré, 2004 ). Based on semi-structured interviews and on older research related to the quality of life at work (Hackman & Oldham, 1976 ; Ketchum & Trist, 1992 ), a model involving 14 characteristics was developed: the usefulness of work, the social contribution of work, rationalization of the tasks, workload, cooperation, salary, the use of skills, learning opportunities, autonomy, responsibilities, rectitude of social and organizational practices, the spirit of service, working conditions, and, finally, recognition and appreciation (Morin, 2006 ; Morin & Cherré, 1999 ). Then, based on this model, a 30-item questionnaire was developed to offer more precise descriptions of these dimensions. Table ​ Table3 3 presents the items, which were designed and administered to the participants in French.

Items from the meaning of work scale by Morin with their theoretical dimensions and exploratory factor analyses

Original theoretical dimensions of the meaning of work
1
Items from the questionnaire with the original item numbers
:
( )*:
23
Usefulness of work ( )

21. Serves some purpose

( )

UUT

3. Leads to results that you value

( )

RIE
Social contribution ( )

9. Is useful to society

( )

UUT

25. Is useful to others

( )

UUT
Rationalization of work ( )

7. Is done efficiently

( )

ART

2. Its objectives are clear

( )

RRT

24. Enables you to achieve the goals that you set for yourself

(

REFF
Workload ( )

12. Respects your private life

( )

SVP

18. Workload is adjusted to your capacities

( )

RRT
Cooperation ( )

1. Allows you to have interesting contact with others

(

PIE

15. Done in a team spirit

( )

PET
Wages ( )

23. Gives you wages that provide for your needs

( )

SRT
Using skills ( )

1. Corresponds to your interests and your skills

( )

AEF

14. You enjoy doing it

( )

PVP
Occasions for learning ( )

2. Allows you to learn or to improve

( )

AEF

28. Enables you to feel fulfilled

( )

PVP
Autonomy ( )

3. Enables you to use your judgment to solve problems

( )

AIE

8. Allows you to take initiatives to improve your results

( )

AEF

13. You are free to organize things in whatever way you think best

( )

PVP
Responsibility ( )

11. Allows you to have influence over your environment

( )

PIE

27. You are responsible

( )

PIE
Rectitude of practices ( )

4. Is done in an environment in which people are respected

( )

EET

5. Human values are followed

( )

EET
Spirit of service ( )

22. Gives you the opportunity to serve others

( )

UUT

26. You can count on the help of your colleagues when you have problems

( )

SET
Health and safety ( )

6. Enables you to consider the future with confidence

( )

SRT

16. Is done in a healthy and safe environment

( )

SET
Recognition ( )

17. Your competence is recognized

( )

RVP

19. Your results are recognized

( )

RVP

29. You can count on the support of your superior

( )

RIE

P personal power at work, U usefulness of work, R success at work, A autonomy at work, S safety, E ethics, UT usefulness of work, VP personal value, EF personal efficacy, ET ethics of work, RT rationalization of work, IE personal influence

(*) = French version. 1 = Morin and Cherré ( 1999 ). 2 = Morin et al. ( 2001 ) and Morin ( 2003 ). 3 = Morin and Cherré ( 2004 )

Some studies for structurally validating this questionnaire have been conducted over the years (e.g., Morin, 2003 , 2006 , 2008 ; Morin & Cherré, 2004 ). However, their results were not very precise or comparable. For example, the number of latent factors in the meaning of work scale structure varied (e.g., six or eight factors: Morin, 2003 ; six factors: Morin, 2006 ; Morin & Cherré, 2004 ), the sample groups were not completely comparable (especially with respect to occupations), and finally, items were added or removed or their phrasing was changed (e.g., 30 and 33 items: Morin, 2003 ; 30 items: Morin, 2006 ; 26 items: Morin, 2008 ). Yet the most prominent methodological problem was that only exploratory analyses (most often a principal component analysis with varimax rotation) had been applied. This scale was entirely relevant from a theoretical point of view because it offered a more specific definition of the meaning of work than other scales and, mainly, because some subdimensions appeared to be linked with anxiety, depression, irritability, cognitive problems, psychological distress, and subjective well-being (Morin et al., 2001 ). It was also relevant from a practical point of view because it was short and did not take much time to complete. However, its use was questionable because it had never been validated psychometrically, and a consistent latent psychological structure had not been identified across studies.

As an example, two models representing the structure of the 30-item scale are presented in Table ​ Table3 3 (Morin et al., 2001 ; Morin, 2003 , for the first model; Morin & Cherré, 2004 , for the second one). This table presents the items, the meaning of work dimensions they are theoretically related to, and the solution from the principal component analysis in each study. These analyses revealed that the empirical and theoretical structures of this tool are not stable and that the latent structure suffers from the insufficient use of statistical methods. In particular, there was an important difference found between the two models in previous studies (Morin et al., 2001 ; Morin & Cherré, 2004 ). Only the “usefulness of work” dimension was found to be identical, comprised of the same items in both models. Other dimensions had a maximum of only three items in common. Therefore, it is very difficult to utilize this tool both in practice and diagnostically, and complementary studies must be conducted. Even though there are techniques for replicating explanatory analyses (e.g., Osborne, 2012 ), such techniques could not be used here because not all the necessary information was given (e.g., all factor loadings, communalities). This is why collecting new data appeared to be the only way to analyze the scale.

More recently, two studies (which applied a new 25-item meaningful work questionnaire ) were developed on the basis of Morin’s scale (Bendassolli & Borges-Andrade, 2013 ; Bendassolli, Borges-Andrade, Coelho Alves, & de Lucena Torres, 2015 ). Even though the concepts of the “meaning of work” and “meaningful work” are close, the two scales are formally and theoretically different and do not evaluate the same construct.

The purpose of the present study was thus to determine the structure of original Morin’s 30-item scale (Morin, 2003 ; Morin & Cherré, 2004 ) by using an exploratory approach as well as confirmatory statistical methods (structural equation modeling) and in so doing, to address the lacunae in previous research discussed above. The end goal was thus to identify the structure of the scale statistically so that it can be used empirically in both academic and professional fields. Indeed, as mentioned previously, this scale is of particular interest to researchers because its design is not limited to measuring a general meaning of work for each individual; it can also be used to evaluate discrepancies or a convergence between a person’s own personal meaning of work and a specific work context (e.g., tasks, relations with others, autonomy). Finally, and with respect to previous results, the scale could be a potential predictor of professional well-being and psychological distress at work (Morin et al., 2001 ).

Participants

The questionnaire was conducted with 366 people who were mainly resident in Paris and the surrounding regions in France. The gender distribution was almost equal; 51.3% of the respondents were women. The respondents’ ages ranged from 19 to 76 years ( M = 39.11, SD = 11.25). The large majority of people were employed (99.2%). Twenty percent worked in medical and paramedical fields, 26% in retail and sales, and 17% in human resources (the other respondents worked in education, law, communication, reception, banking, and transportation). Seventy percent had fewer than 10 years of seniority in their current job ( M = 8.64, SD = 9.65). Only three people were retired (0.8%).

Morin’s 30-item meaning of work questionnaire (Morin, 2003 ; Morin et al., 2001 ; Morin & Cherré, 2004 ) along with sociodemographic questions (i.e., sex, age, job activities, and seniority at work) were conducted in French through an online platform. Answers to the meaning of work questionnaire were given on a 5-point Likert scale ranging from 1 ( strongly disagree ) to 5 ( strongly agree ).

Participants were recruited through various professional online social networks. This method does not provide for a true random sample but, owing to it resulting in a potentially larger range of respondents, it enlarges the heterogeneousness of the participants, even if it cannot ensure representativeness (Barberá & Zeitzoff, 2018 ; Hoblingre Klein, 2018 ). This point seems important because very homogenous samples were used in previous studies, especially with regard to professions.

Participants were volunteers, and were given the option of being able to stop the survey at any time. They received no compensation and no individual feedback. Participants were informed of these conditions before filling out the questionnaire. Oral and informed consent was obtained from all participants. Moreover, the Luxembourg Agency for Research Integrity (LARI on which the researchers in this study depend) specified that according to Code de la santé publique—Article L1123-7, it appears that France does not require research ethics committee [Les Comités de Protection des Personnes (CPP)] approval if the research is non-biomedical, non-interventional, observational, and does not collect personal health information, and thus CNR approval was not required.

Participants had to answer each question in order to submit the questionnaire: If one item was not answered, the respondent was not allowed to proceed to the next question. Thus, the database has no missing data. An introduction presented the subject of the study and its goals and guaranteed the participant’s anonymity. Researchers’ e-mail addresses were given, and participants were informed that they could contact the researchers for more information.

Data analyses

Three sets of statistical analyses were run on the data:

  • Analysis of the items, using traditional true score theory and item response theory, for verifying the psychometric qualities (using mainly R package “psych”). The main objectives of this part of analysis were to better understand the variability of respondents’ answers, to compute the discriminatory power of items, and to verify the distribution of items by using every classical descriptive indicator (mean, standard-deviation, skewness, and kurtosis), corrected item-total correlations, and functions of responses for distributions.
  • An exploratory factor analysis (EFA) with an oblimin rotation in order to define the latent structure of the meaning of work questionnaire, performed with the R packages “psych” and “GPArotation”. The structure we retained was based on adequation fits of various solutions (TLI, RMSEA and SRMR, see “List of abbreviations” section at the end of the article), and the use of R package “EFAtools” which helps to determine the adequate number of factors to retain for the EFA solution. Finally, this part of the analysis was concluded using calculations of internal consistency for each factor found in the scale.
  • A confirmatory factor analysis using the R package Lavaan and based on the results of the EFA, in order to verify that the latent structure revealed in Step c was valid and relevant for this meaning of work scale. The adequation between data and latent structure was appreciated on the basis of CFI, TLI, RMSEA, and SRMR (see “Abbreviations” section).

For step a, the responses of the complete sample were considered. For steps b and c, 183 subjects were selected randomly for each analysis from the total study sample. Thus, two subsamples comprised of completely different participants were used, one for the EFA in step b and one for the CFA in step c.

Because of the ordinal measurement of the responses and its small number of categories (5-point Likert), none of the items can be normally distributed. This point was verified in step a of the analyses. Thus, the data did not meet the necessary assumptions for applying factor analyses with conventional estimators such as maximum likelihood (Li, 2015 ; Lubke & Muthén, 2004 ). Therefore, because the variables were measured on ordinal scales, it was most appropriate to apply the EFA and CFA analyses to the polychoric correlation matrix (Carroll, 1961 ). Then, to reduce the effects of the specific item distributions of the variables used in the factor analyses, a minimum residuals extraction (MINRES; Harman, 1960 ; Jöreskog, 2003 ) was used for the EFA, and a weighted least squares estimator with degrees of freedom adjusted for means and variances (WLSMV) was used for the CFA as recommended psychometric studies (Li, 2015 ; Muthén, 1984 ; Muthén & Kaplan, 1985 ; Muthén & Muthén, 2010 ; Yang, Nay, & Hoyle, 2010 ; Yu, 2002 ).

The size of samples for the different analyses has been taken into consideration. A model structure analysis with 30 observed variables needs a recommended minimum sample of 100 participants for 6 latent variables, and 200 for 5 latent variables (Soper, 2019 ). The samples used in the present research corresponded to these a priori calculations.

Finally, according to conventional rules of thumb (Hu & Bentler, 1999 ; Kline, 2011 ), acceptable and excellent model fits are indicated by CFI and TLI values greater than .90 and .95, respectively, by RMSEA values smaller than .08 (acceptable) and .06 (excellent), respectively, and SRMR values smaller than .08.

Item analyses

The main finding was the limited amount of variability in the answers to each item. Indeed, as Table ​ Table4 4 shows, respondents usually and mainly chose the answers agree and strongly agree , as indicated by the column of cumulated percentages of these response modalities (%). Thus, for all items, the average answer was higher than 4, except for item 11, the median was 4, and skewness and kurtosis indicators confirmed a systematic skewed on the left leptokurtic distribution. This lack of variability in the participants’ responses and the high average scores indicate nearly unanimous agreement with the propositions made about the meaning of work in the questionnaire.

Distribution and analysis of the 30 items of the scale

Items from the questionnaire
:
%
1. Corresponds to your interests and your skills4.4.74.091.8− 4.522.6.571
2. Allows you to learn or to improve4.4.64.093.7− 4.420.5.581
3. Enables you to use your judgment to solve problems4.0.94.075.7− 2.24.9.432
4. Is done in an environment where people are respected4.5.84.092.9− 4.117.6.634
5. Human values are respected4.5.64.094.0− 4.621.6.608
6. Enables you to consider the future with confidence4.3.84.088.5− 3.816.8.648
7. Is done efficiently4.3.74.089.6− 3.615.5.665
8. Allows you to take initiatives to improve your results4.3.74.090.2− 3.210.2.642
9. Is useful to society4.2.84.084.7− 2.99.1.547
10. Allows you to have interesting contact with others4.3.74.088.8− 3.413.2.608
11. Allows you to have influence over your environment3.7.94.057.7− 1.31.5.436
12. Respects your private life4.3.94.085.8− 3.210.6.516
13. You are free to organize things in the way that you think best4.2.84.083.1− 2.78.4.498
14. You enjoy doing it4.5.74.094.0− 5.433.9.579
15. Done in a team spirit4.2.84.082.8− 2.910.7.559
16. Is done in a healthy and safe environment4.2.84.086.3− 3.311.9.595
17. Your competence is recognized4.3.84.088.3− 3.715.7.724
18. Workload is adjusted to your capacities4.0.84.078.1− 2.56.7.562
19. Your results are recognized4.2.84.084.2− 2.99.1.657
20. Its objectives are clear4.2.84.085.8− 3.212.0.603
21. Serves some purpose4.4.74.090.7− 3.919.2.545
22. Gives you the opportunity to serve others4.2.84.082.8− 2.88.7.549
23. Gives you wages that provide for your needs4.4.74.091.8− 4.321.0.548
24. Enables you to achieve the goals you set yourself4.2.74.083.9− 2.45.2.631
25. Is useful to others4.2.84.085.0− 2.99.3.560
26. You can count on the help of your colleagues when you have problems4.2.84.082.8− 3.010.6.584
27. You are responsible4.2.84.084.4− 3.010.3.562
28. Enables you to feel fulfilled4.4.74.088.0− 3.312.8.642
29. You can count on the support of your superior4.1.94.081.7− 2.88.2.557
30. Leads to results that you value4.1.84.077.6− 2.36.6.542

M average of the answers to the item, SD standard deviation of the answers to the item, Med median, % cumulated percentages of answers 4 ( agree ) and 5 ( strongly agree ) for each item, skew skewness, kurt kurtosis, rit corrected item-total correlations

Table ​ Table4 4 also shows that the items had good discriminatory power, expressed by corrected item-total correlations (calculated with all items) which were above .40 for all items. Finally, item analyses were concluded through the application of item response theory (Excel tools using the eirt add in; Valois, Houssemand, Germain, & Belkacem, 2011 ) which confirmed, by analyses of item characteristic curves (taking into account that item response theory models are parametric and assume that the item responses distributions follow a logistic function, Rasch, 1980 ; Streiner, Norman, & Cairney, 2015 , p. 297), the psychometric quality of each item and their link to an identical latent dimension. These different results confirmed the interest in keeping all items of the questionnaire in order to measure the work-meaning construct.

Exploratory analyses of the scale

A five-factor solution was identified. This solution explained 58% of the total variance in the responses of the scale items; the TLI was .885, the RMSEA was .074, and the SRMR was .04. The structure revealed by this analysis was relatively simple (saturation of one main factor for each item; Thurstone, 1947 ), and the communality of each item was high, except for item 11. The solution we retained presented the best adequation fits and the most conceptual explanation concerning the latent factors. Additionally, the “EFAtools” R package confirmed the appropriateness of the chosen solution. Table ​ Table5 5 shows the EFA results, which described a five-factor structure.

Loadings and communalities of the 30 items from the meaning of work scale

ItemsF1
Success and Recognition
F2
Usefulness
F3
Respect
F4
Value
F5
Remuneration
19. Your results are recognized − .02− .05.06.08.75
18. Workload is adjusted to your capacities .05.14− .22.13.60
17. Your competence is recognized − .06.09.21.12.71
30. Leads to results that you value .26.04.01− .22.57
29. You can count on the support of your superior .15.13− .07.06.49
20. Its objectives are clear .10.11.02.19.49
24. Enables you to achieve the goals you set yourself .00.16.24.03.55
11. Allows you to have influence over your environment .10− .14.26− .11.39
25. Is useful to others .09.20− .11 .47
27. You are responsible− .02 .03.00− .07.79
22. Gives you the opportunity to serve others− .03 .04− .08.21.58
9. Is useful to society.06 .14.09− .11.58
10. Allows you to have interesting contact with others.05 − .02.31.24.55
21. Serves some purpose.17 .10− .01− .02.46
28. Enables you to feel fulfilled.07 − .04.22.14.56
26. You can count on the help of your colleagues when you have problems.28 − .05.23.06.44
5. Human values are respected− .01.06 .00− .02.92
4. Is done in an environment where people are respected.05.01 .15.07.78
6. Enables you to consider the future with confidence.23− .02 .14.28.59
7. Is done efficiently.10.15 .20.25.58
2. Allows you to learn or to improve− .09.15.08 .17.71
1. Corresponds to your interests and your skills.12.03.27 − .10.60
3. Enables you to use your judgment to solve problems .08− .10 − .04.43
8. Allows you to take initiatives to improve your results.27.06.11 .07.66
12. Respects your private life.22− .01.27.01 .56
16. Is done in a healthy and safe environment .12.13.02 .59
13. You are free to organize things in the way that you think best.04.09.03.18 .49
23. Gives you wages that provide for your needs.31− .09.03.23 .50
15. Done in a team spirit.08.26.18.01 .51
14. You enjoy doing it.06.21.10 .53

EFA with five factors, oblimin rotation. Bold = loading ≥ .30. h 2 = communality

Nevertheless, the correlation matrix for the latent factors obtained by the EFA (see Table ​ Table6) 6 ) suggested the existence of a general second-order meaning of work factor, because the five factors were significantly correlated each with others. This result could be described as the existence of a general meaning of work factor, which alone would explain 44% of the total variance in the responses.

Correlations between the latent factors from the EFA, Cronbach’s alpha, and McDonald omega for each dimension and general factor

F1F2F3F4F5AlphaOmega
F1.90.93
F2.46.88.92
F3.48.57.88.91
F4.46.42.34.83.85
F5.44.29.48.34.85.87
General.96.97

F1: success and recognition at work and from work; F2: usefulness; F3: respect; F4: value from and through work; F5: remuneration; general: total scale

Internal consistency of latent factors of the scale

The internal consistency of each latent factor, estimated by Cronbach alpha and McDonald omega, was high (above .80) and very high for the entire scale (α = .96 and ω = .97). Thus, for S uccess and Recognition at work and from work ’ s factor ω was .93, for Usefulness ’s factor ω was .92, for Respect ’s factor ω was .91, for Value from and through work ’s factor ω was slightly lower and equal to .85, and finally for Remuneration ’ s factor for which ω was .87.

Confirmatory factor analyses of the scale

In order to improve the questionnaire, we applied a CFA to this five-factor model to improve the model fit and refine the latent dimensions of the questionnaire. We used CFA to (a) determine the relevance of this latent five-factor structure and (b) confirm the relevance of a general second-order meaning-of-work factor. Although this procedure might appear redundant at first glance, it enabled us to select a definitive latent structure in which each item represents only one latent factor (simple structure; Thurstone, 1947 ), whereas the EFA that was computed in the previous step showed that certain items loaded on several factors. The CFA also easily verified the existence of a second-order latent meaning of work factor (the first-order loadings were .894, .920, .873, .892, and .918, respectively). Thus, this CFA was computed to complement the previous analyses by refining the latent model proposed for the questionnaire.

According to conventional rules of thumb (Hu & Bentler, 1999 ; Kline, 2011 ), although the RMSEA value for the five-factor model was somewhat too high, the CFI and TLI values were excellent (χ 2 = 864.72, df = 400, RMSEA = .080, CFI = .989, TLI = .988). Table ​ Table7 7 presents the adequation fits for both solutions: a model with 5 first-order factors (as EFA suggests), and a model with 5 first-order factors and 1 second-order factor.

Solutions of confirmatory factor analyses

Indicators CFITLIRMSEASRMR
Model with 5 first-order factors837.097395.989.988.078.073
Model with 5 first-order factors and 1 second-order factor864.724400.989.988.080.075

χ 2 Chi-square, df degrees of freedom, CFI comparative fit index, TLI Tucker-Lewis Index of factoring reliability, RMSEA root mean square error of approximation, SRMR standardized root mean square residual

Figure ​ Figure1 1 shows the model after the confirmatory test. This analysis confirmed the existence of a simple structure with five factors for the meaning of work scale and with a general, second-order factor of the meaning of work as suggested by the previous EFA.

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Object name is 41155_2020_167_Fig1_HTML.jpg

Standardized solution of the structural model of the Meaning of Work Scale

The objective of this study was to verify the theoretical and psychometric structure of the meaning of work scale developed by Morin in recent years (Morin, 2003 ; Morin et al., 2001 ; Morin & Cherré, 2004 ). This scale has the advantages of being rather short, of proposing a multidimensional structure for the meaning of work, and of making it possible to assess the coherence between the aspects of work that are personally valued and the actual characteristics of the work environment. Thus, it can be used diagnostically or to guide individuals. To establish the structure of this scale, we analyzed deeply the items, and we implemented exploratory and confirmatory factor analyses, which we believe the scale’s authors had not carried out sufficiently. Moreover, we used a broad range of psychometric evaluation methods (traditional true score theory, item response theory, EFA, and structural equation modeling) to test the validity of the scale.

Item analyses confirmed results found in previous studies in which the meaning-of-work scale was administered. The majority of respondents agreed with the proposals of the questionnaire. Thus, this lack of variability is not specific to the present research and its sample (e.g., Morin & Cherré, 2004 ). Nevertheless, this finding can be explained by different reasons (which could be studied by other research) such as social desirability and the importance of work norms in industrial societies, or a lack of control regarding response bias.

The various versions of the latent structure of the scale proposed by the authors were not confirmed by the statistical analyses seen here. It nevertheless appears that this tool for assessing the meaning of work can describe and measure five different dimensions, all attached to a general factor. The first factor (F1), composed of nine items, is a dimension of recognition and success (e.g., item 17: work where your skills are recognized ; item 19: work where your results are recognized ; item 24: work that enables you to achieve the goals that you set for yourself ). It should thus be named Success and Recognition at work and from work and is comparable to dimensions from previous studies (personal success, Morin et al., 2001 ; social influence, Morin & Cherré, 2004 ). The second factor (F2), composed of seven items, is a dimension that represents the usefulness of work for an individual, whether that usefulness is social (e.g., Item 22: work that gives you the opportunity to serve others ) or personal (e.g., Item 28: work that enables you to be fulfilled ). It can be interpreted in terms of the Usefulness of work and generally corresponds to dimensions of the same name in earlier models (Morin, 2003 ; Morin & Cherré, 2004 ), although the definition used here is more precise. The third factor (F3), described by four items, refers to the Respect dimension of work (e.g., Item 5: work that respects human values ) and corresponds in part to the factors highlighted in prior studies (respect and rationalization of work, Morin, 2003 ; Morin & Cherré, 2004 ). The fourth factor (F4), composed of four items, refers to the personal development dimension and Value from and through work (e.g., Item 2: work that enables you to learn or to improve ). It is in some ways similar to autonomy and effectiveness, described by the authors of the scale (Morin, 2003 ; Morin & Cherré, 2004 ). Finally, the fifth and final factor (F5), with six items, highlights the financial and, more important, personal benefits sought or received from work. This includes physical and material safety and the enjoyment of work (e.g., item 14: work you enjoy doing ). This dimension of Remuneration partially converges with the aspects of personal values related to work described in previous research (Morin et al., 2001 ). Although the structure of the scale highlighted here differed from previous studies, some theoretical elements were nevertheless consistent with each other. To be convinced of this, the Table ​ Table8 8 highlights possible overlaps.

Final structure the items of the meaning of work scale by Morin and their theoretical dimensions

Final structure of the scaleItems from the questionnaire with the original item numbers
:
12
Success and recognition at work and from work11. Allows you to have influence over your environmentSuccess at workRecognition of work
17. Your competence is recognized

18. Workload is adjusted to your capacities

19. Your results are recognized

20. Allows you to learn or to improve
24. Enables you to achieve the goals that you set for yourself
25. Is useful to others
29. You can count on the support of your superior
30. Leads to results that you value
Usefulness of work9. Is useful to society

Usefulness of work

Personal power at work

Spirit of service

Social contribution

10. Allows you to have interesting contact with others
21. Serves some purpose
22. Gives you the opportunity to serve others
26. You can count on the help of your colleagues when you have problems
27. You are responsible
28. Enables you to feel fulfilled
Respect dimension of work4. Is done in an environment in which people are respectedEthicsRectitude of practices
5. Human values are followed
6. Enables you to consider the future with confidence
7. Is done efficiently
Value from and through work1. Corresponds to your interests and your skillsAutonomy at workMixture
2. Allows you to learn or to improve
3. Enables you to use your judgment to solve problems
8. Allows you to take initiatives to improve your results
Remuneration12. Respects your private life

Personal power at work

Safety

Mixture
13. You are free to organize things in whatever way you think best
14. You enjoy doing it
15. Done in a team spirit
16. Is done in a healthy and safe environment
23. Gives you wages that provide for your needs

1 = Previous dimensions of Morin et al. ( 2001 ) and Morin ( 2003 ). 2 = Morin and Cherré ( 1999 )

A second important result of this study is the highlighting of a second-order factor by the statistical analyses carried out. This latent second-level factor refers to the existence of a general meaning of work dimension. This unitary conception of the meaning of work, subdivided into different linked facets, is not in contradiction with the different theories related to this construct. Thus, Ros et al. ( 1999 ) defined the meaning of work as a personal interpretation of experiences and interaction at work. This view of meaning of work can confer it a unitary functionality for maintaining psychological harmony, despite the destabilizing events that are often a feature of work. It must be considered as a permanent process of work adjustment or work adaptation. In order to be effective, this adjustment needs to remain consistent and to be globally oriented toward the cognitive balance between the reality of work and the meaning attributed to it. Thus, it has to keep a certain coherence which would explain the unitary conception of the meaning of work.

In addition to the purely statistical results of this study, whereas some partial overlap was found between the structural model in this study and structural models from previous work, this paper provides a much-needed updating and improvement of these dimensions, as we examined several theoretical meaning of work models in order to explain them psychologically. Indeed, the dimensions defined here as Success and Recognition , Usefulness , Respect , Value , and Remuneration from the meaning of work scale by Morin et al. ( 2001 ) have some strong similarities to other theoretical models on the meaning of work, even though the authors of the scale referred to these models only briefly. For example, the dimensions work centrality as a life role , societal norms regarding work , valued work outcomes , importance of work goals , and work-role identification (MOW International Research team, 1987 ) concur with the model described in the present study. In the same manner, the model by Rosso et al. ( 2010 ) has some similarities to the present structure, and there is a conceptual correspondence between the five dimensions found here and those from their study ( individuation , contribution , self-connection , and unification ). Finally, Baumeister’s ( 1991 ), Morin and Cherré’s ( 2004 ), and Sommer, Baumeister, and Stillman ( 2012 ) studies presented similar findings on the meaning of important life experiences for individuals; they described four essential needs that make such experiences coherent and reasonable ( purpose , efficacy - control , rectitude , and self - worth ). It is obvious that the parallels noted here were fostered by the conceptual breadth of the dimensions as defined in these models. In future research, much more precise definitions are needed. To do so, it will be essential to continue running analyses to test for construct validity by establishing convergent validity between the dimensions of the various existing meaning of work scales.

It is also interesting to note the proximity between the dimensions described here and those examined in studies on the dimensions that characterize the work context (Pignault & Houssemand, 2016 ) or in Karasek’s ( 1979 ) and Siegrist’s ( 1996 ) well-known models, for example, which determined the impact of work on health, stress, and well-being. These studies were able to clearly show how dimensions related to autonomy, support, remuneration, and esteem either contribute to health or harm it. These dimensions, which give meaning to work in a manner that is similar to the dimensions highlighted in the current study (Recognition, Value, and Remuneration in particular), are also involved in health. Thus, it would be interesting to verify the relations between these dimensions and measures of work health.

Thus, the conceptual dimensions of the meaning of work, as defined by Morin ( 2003 ) and Morin and Cherré ( 1999 ), remained of strong theoretical importance even if, at the empirical level, the scale created on this basis did not correspond exactly. The present study has had the modest merit of showing this interest, and also of proposing a new structure of the facets of this general dimension. One of the major interests of this research can be found in the possible better interpretations that this scale will enable to make. As mentioned above, the Morin’s scale is very frequently used in practice (e.g., in state employment agencies or by Human Resources departments), and the divergent models of previous studies could lead to individual assessments of the meaning of work diverging, depending on the reading grid chosen. Showing that a certain similarity in the structures of the meaning of work exists, and that a general factor of the meaning of work could be considered, the results of the current research can contribute to more precise use of this tool.

At this stage and in conclusion, it may be interesting to consider the reasons for the variations between the structures of the scale highlighted by the different studies. There were obviously the different changes applied to the different versions of the scale, but beyond that, three types of explanation could emerge. At the level of methods, the statistics used by the studies varied greatly, and could explain the variations observed. At the level of the respondents, work remains one of the most important elements of life in our societies. A certain temptation to overvalue its importance and purposes could be at the origin of the broad acceptance of all the proposals of the questionnaire, and the strong interactions between the sub-dimensions. Finally, at the theoretical level, if, as our study showed, a general dimension of meaning of work seems to exist, all the items, all the facets and all the first order factors of the scale, are strongly interrelated at each respective level. As well, small variations in the distribution of responses could lead to variations of the structure.

The principal contribution of this study is undoubtedly the use of confirmatory methods to test the descriptive models that were based on Morin’s scale (Morin, 2003 , 2006 ; Morin & Cherré, 1999 , 2004 ). The principal results confirm that the great amount of interest in this scale is not without merit and suggest its validity for use in research, both by practitioners (e.g., career counselors and Human Resources departments) and diagnostically. The results show a tool that assesses a general dimension and five subdimensions of the meaning of work with a 30-item questionnaire that has strong psychometric qualities. Conceptual differences from previous exploratory studies were brought to light, even though there were also certain similarities. Thus, the objectives of this study were met.

Limitations

As with any research, this study also has a certain number of limitations. The first is the sample size used for statistical analyses. Even if the research design respected the general criteria for these kind of analyses (Soper, 2019 ), it will be necessary to repeat the study with larger samples. The second is the cultural and social character of the meaning of work, which was not addressed in this study because the sample was comprised of people working in France. They can thus be compared with those in Morin’s studies ( 2003 ) because of the linguistic proximity (French) of the samples, but differences in the structure of the scale could be due to cultural differences between America and Europe. Nevertheless, other different international populations should be questioned about their conception of the meaning of work in order to measure the impact of cultural and social aspects (England, 1991 ; England & Harpaz, 1990 ; Roe & Ester, 1999 ; Ruiz-Quintanilla & England, 1994 ; Topalova, 1994 ; Zanders, 1993 ). In the same vein, a third limitation involves the homogeneity of the respondents’ answers. Indeed, there was quasi-unanimous agreement with all of the items describing work (see Table ​ Table4 4 and previous results, Morin & Cherré, 2004 ). It is worth examining whether this lack of variance results from a work norm that is central and promoted in industrialized countries as it might mask broader interindividual differences. Thus, this study’s protocol should be repeated with other samples from different cultures. Finally, a fourth limitation that was mentioned previously involves the validity of the scale. Concerning the content validity and because some items loaded similarly different factors, it could be interesting to verify the wording content of the items, and potentially modify or replace some of them. The purpose of the present study was not to change the content of the scale but to suggest how future studies could analyze this point. Concerning the construct validity, this first phase of validation needs to be followed by other phases that involve tests of convergent validity between the existing meaning of work scales as well as tests of discriminant validity in order to confirm the existence of the meaning of work construct examined here. In such studies, the centrality of work (Warr, 2008 ; Warr, Cook, & Wall, 1979 ) should be used to confirm the validity of the meaning of work scale. Other differential, individual, and psychological variables related to work (e.g., performance, motivation, well-being) should also be introduced in order to expand the understanding of whether relations exist between the set of psychological concepts involved in work and individuals’ jobs.

Acknowledgements

Not applicable.

Abbreviations

CFAConfirmatory factor analyses
CFIComparative Fit Index
EFAExploratory factor analyses
LARILuxembourg Agency for Research Integrity
MOWMeaning of work
TLITucker Lewis Index of factoring reliability
RMSEARoot mean square error of approximation
SRMRStandardized root mean square residual

Authors’ contributions

Both the authors are responsible for study conceptualization, data collection, data preparation, data analysis and report writing. The original questionnaire is a public one. No permission is required. The author(s) read and approved the final manuscript.

No funding.

Availability of data and materials

Ethics approval and consent to participate.

Ethical review and approval was not required for the study on human participants in accordance with the local legislation and institutional requirements. The Luxembourg Agency for Research Integrity (LARI) specifies that according to Code de la santé publique - Article L1123-7, it appears that France does not require research ethics committee (Les Comités de Protection des Personnes (CPP)) approval if the research is non-biomedical, non-interventional, observational, and does not collect personal health information. Written informed consent for participation was not required for this study in accordance with the national legislation and the institutional requirements. At the beginning of the questionnaire, the participants had to give their consent that the data could be used for research purposes, and they had to consent to the publication of the results of the study. Participation was voluntary and confidential. No potentially identifiable human images or data is presented in this study.

Competing interests

The authors declare that they have no competing interests.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Contributor Information

Anne Pignault, Email: [email protected] .

Claude Houssemand, Email: [email protected] .

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  • Published: 01 August 2023

Organizational behaviour

The meaning of work

  • Hannah Weisman   ORCID: orcid.org/0000-0002-6874-9339 1  

Nature Reviews Psychology volume  2 ,  page 522 ( 2023 ) Cite this article

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Close your eyes for a moment and imagine it is 9 a.m. tomorrow. You are opening your laptop to start your workday. Why are you working?

Work holds different meanings for different people. For some people, work is a means to a financial end (a job), an unfortunate necessity of life that provides a paycheck and funds life’s more enjoyable, non-work pursuits. For other people, work is a means of advancement in the world (a career), an opportunity to achieve higher social standing by ascending in an occupational or organizational hierarchy. Finally, for some people, work is a meaningful end in itself (a calling), an intrinsically rewarding endeavour that they see as central to their identity and, often, as making the world a better place.

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Original article

Wrzesniewski, A. et al. Jobs, careers, and callings: people’s relations to their work. J. Res. Pers. 31 , 21–33 (1997)

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the meaning of research work

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What factors contribute to the meaning of work? A validation of Morin’s Meaning of Work Questionnaire

  • Anne Pignault   ORCID: orcid.org/0000-0001-7946-3793 1 &
  • Claude Houssemand 2  

Psicologia: Reflexão e Crítica volume  34 , Article number:  2 ( 2021 ) Cite this article

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Considering the recent and current evolution of work and the work context, the meaning of work is becoming an increasingly relevant topic in research in the social sciences and humanities, particularly in psychology. In order to understand and measure what contributes to the meaning of work, Morin constructed a 30-item questionnaire that has become predominant and has repeatedly been used in research in occupational psychology and by practitioners in the field. Nevertheless, it has been validated only in part.

Meaning of work questionnaire was conducted in French with 366 people (51.3% of women; age: ( M = 39.11, SD = 11.25); 99.2% of whom were employed with the remainder retired). Three sets of statistical analyses were run on the data. Exploratory and confirmatory factor analysis were conducted on independent samples.

The questionnaire described a five-factor structure. These dimensions (Success and Recognition at work and of work, α = .90; Usefulness, α = .88; Respect for work, α = .88; Value from and through work, α = .83; Remuneration, α = .85) are all attached to a general second-order latent meaning of work factor (α = .96).

Conclusions

Validation of the scale, and implications for health in the workplace and career counseling practices, are discussed.

Introduction

Since the end of the 1980s, many studies have been conducted to explore the meaning of work, particularly in psychology (Rosso, Dekas, & Wrzesniewski, 2010 ). A review of the bibliographical data in PsychInfo shows that between 1974 and 2006, 183 studies addressed this topic (Morin, 2006 ). This scholarly interest was primarily triggered by Sverko and Vizek-Vidovic’s ( 1995 ) article, which identified the approaches and models that have been used and their main results.

Whereas early studies on the meaning of work introduced the concept and its theoretical underpinnings (e.g., Harpaz, 1986 ; Harpaz & Fu, 2002 ; Morin, 2003 ; MOW International Research team, 1987 ), later research tried to connect this aspect of work with other psychological dimensions or individual perceptions of the work context (e.g., Harpaz & Meshoulam, 2010 ; Morin, 2008 ; Morin, Archambault, & Giroux, 2001 ; Rosso et al., 2010 ; Wrzesniewski, Dutton, & Debebe, 2003 ). Nevertheless, scholars, particularly those in organizational and occupational psychology, soon found it difficult to precisely identify the meaning of work because it changes in accordance with the conceptualizations of different researchers, the theoretical models used to describe it, and the tools that are available to measure it for individuals and for groups.

This article first seeks to clarify the concept of the meaning of work (definitions and models) before bringing up certain problems involved in its measurement and the diversity in how the concept has been used. Then the paper focuses on a particular meaning of work measurement tool developed in Canada, which is now widely used in French-speaking countries. At the beginning of the twenty-first century, Morin et al. ( 2001 ) developed a 30-item questionnaire to better determine the dimensions that give meaning to a person’s work. The statistical analyses needed to determine the reliability and validity of Morin et al.’s meaning of work questionnaire have never been completed. Indeed, some changes were made to the initial scale, and the analyses only based on homogenous samples of workers in different professional sectors. Thus and even though the meaning of work scale is used quite frequently, both researchers and practitioners have been unsure about whether or not to trust its results. The main objective of the present study was thus to provide a psychometric validation of Morin et al.’s meaning of work scale and to uncover its latent psychological structure.

Meaning of work: from definition to measurement

Meaning of work: what is it.

As many scholars have found, the concept of the meaning of work is not easy to define (e.g., Rosso et al., 2010 ). In terms of theory, it has been defined differently in different academic fields. In psychology, it refers to an individual’s interpretations of his/her actual experiences and interactions at work (Ros, Schwartz, & Surkiss, 1999 ). From a sociological point of view, it involves assessing meaning in reference to a system of values (Rosso et al., 2010 ). In this case, its definition depends on cultural or social differences, which make explaining this concept even more complex (e.g., Morse & Weiss, 1955 ; MOW International Research team, 1987 ; Steers & Porter, 1979 ; Sverko & Vizek-Vidovic, 1995 ).

At a conceptual level, the meaning of work has been defined in three different ways (Morin, 2003 ). First, it can refer to the meaning of work attached to an individual’s representations of work and the values he/she attributes to that work (Morse & Weiss, 1955 ; MOW International Research team, 1987 ). Second, it can refer to a personal preference for work as defined by the intentions that guide personal action (Super & Sverko, 1995 ). Third, it can be understood as consistency between oneself and one’s work, similar to a balance in one’s personal relationship with work (Morin & Cherré, 2004 ).

With respect to terms, some differences exist because the meaning of work is considered an individual’s interpretation of what work means or of the role it plays in one’s life (Pratt & Ashforth, 2003 ). Yet this individual perception is also influenced by the environment and the social context (Wrzesniewski et al., 2003 ). The psychological literature on the meaning of work has primarily examined its positive aspects, even though work experiences can be negative or neutral. This partiality about the nature of the meaning of work in research has led to some confusion in the literature between this concept and that of meaningful , which refers to the extent to which work has personal significance (a quantity) and seems to depend on positive elements (Steger, Dik, & Duffy, 2012 ). A clearer demarcation should be made between these terms in order to specify the exact sense of the meaning of work: “This would reserve ‘meaning’ for instances in which authors are referring to what work signifies (the type of meaning), rather than the amount of significance attached to the work” (Rosso et al., 2010 , p. 95).

The original idea of the meaning of work refers to the central importance of work for people, beyond the simple behavioral activity through which it occurs. Drawing on various historical references, certain authors present work as an essential driver of human life; these scholars then seek to understand how work is fundamental (e.g., Morin, 2006 ; Sverko & Vizek-Vidovic, 1995 ). The concept of the meaning of work is connected to the centrality of work for the individual and consequently fulfills four different important functions: economic (to earn a living), social (to interact with others), prestige (social position), and psychological (identity and recognition). In this view, the centrality of work is based on an ensemble of personal and social values that differ between individuals as well as between cultures, economic climates, and occupations (England, 1991 ; England & Harpaz, 1990 ; Roe & Ester, 1999 ; Ruiz-Quintanilla & England, 1994 ; Topalova, 1994 ; Zanders, 1993 ).

Meaning of work: which theoretical model?

The first theoretical model for the meaning of work was based on research in the MOW project (MOW International Research team, 1987 ), considered the “most empirically rigorous research ever undertaken to understand, both within and between countries, the meanings people attach to their work roles” (Brief, 1991 , p. 176). This view suggests that the meaning of work is based on five principal theoretical dimensions: work centrality as a life role, societal norms regarding work, valued work outcomes, importance of work goals, and work-role identification. A series of studies on this theory was conducted in Israel (Harpaz, 1986 ; Harpaz & Fu, 2002 ; Harpaz & Meshoulam, 2010 ), complementing the work of the MOW project (MOW International Research team, 1987 ). Harpaz ( 1986 ) empirically identified six latent factors that represent the meaning of work: work centrality, entitlement norm, obligation norm, economic orientation, interpersonal relations, and expressive orientation.

Another theoretical model on the importance of work in a person’s life was created by Sverko in 1989 . This approach takes into account the interactions among certain work values (the importance of these values and the perception of possible achievements through work), which depend on a process of socialization. The ensemble is then moderated by an individual’s personal experiences with work. In the same vein, Rosso et al. ( 2010 ) tried to create an exhaustive model of the sources that influence the meaning of work. This model is built around two major dimensions: Self-Others (individual vs. other individuals, groups, collectives, organizations, and higher powers) and Agency-Communion (the drives to differentiate, separate, assert, expand, master, and create vs. the drives to contact, attach, connect, and unite). This theoretical framework describes four major pathways to the meaning of work: individuation (autonomy, competence, and self-esteem), contribution (perceived impact, significance, interconnection, and self-abnegation), self-connection (self-concordance, identity affirmation, and personal engagement), and unification (value systems, social identification, and connectedness).

Lastly, a more recent model (Lips-Wiersma & Wright, 2012 ) converges with the theory suggested by Rosso et al. ( 2010 ) but distinguishes two dimensions: Self-Others versus Being-Doing. This model describes four pathways to meaningful work: developing the inner self, unity with others, service to others, and expressing one’s full potential.

Without claiming to be exhaustive, this brief presentation of the theoretical models of the meaning of work underscores the difficulty in precisely defining this concept, the diversity of possible approaches to identifying its contours, and therefore implicitly addresses the various tools designed to measure it.

Measuring the meaning of work

Various methodologies have been used to better determine the concept of the meaning of work and to grasp what it involves in practice. The tools examined below have been chosen because of their different methodological approaches.

One of the first kinds of measurements was developed by the international MOW project (MOW International Research team, 1987 ). In this study, England and Harpaz ( 1990 ) and Ruiz-Quintanilla and England ( 1994 ) used 14 defining elements to assess agreement on the perception of work of 11 different sample groups questioned between 1989 and 1992. These elements, resulting from the definition of work given by the MOW project and studied by applying multivariate analyses and textual content analyses ( When do you consider an activity as working ? Choose four statements from the list below which best define when an activity is “ working,” MOW International Research team, 1987 ), can be grouped into four distinct heuristic categories (Table 1 ).

Similarly, England ( 1991 ) studied changes in the meaning of work in the USA between 1982 and 1989. He used four different methodological approaches to the meaning of work: societal norms about work, importance of work goals, work centrality, and definition of work by the labor force. In the wake of these studies, others developed scales to measure the centrality of work in people’s lives, either for the general population (e.g., Warr, 2008 ) or for specific subpopulations such as unemployed people, on the basis of a rather similar conceptualization of the meaning of work (McKee-Ryan, Song, Wanberg, & Kinicki, 2005 ; Wanberg, 2012 ).

Finally, Wrzesniewski, McCauley, Rozin, and Schwartz ( 1997 ) developed a rather unusual method for evaluating people’s relationships with their work. Although not directly connected to research on the meaning of work, this study and the questionnaire they used ( University of Pennsylvania Work-Life Questionnaire ) addressed some of the same concepts. Above all, they employed the concepts in a very particular way that combined psychological scales, scenarios, and sociodemographic questions. Through these scenarios (Table 2 ) and the extent to which the respondents felt like the described characters, their relationship to work was described as either a Job, a Career, or a Calling.

This presentation of certain tools for measuring the meaning of work reveals a variety of methodological approaches. Nevertheless, whereas certain methods have adopted a rather traditional psychological approach, others are often difficult to use for various reasons such as their psychometrics (e.g., the use of only one item to measure a concept; England, 1991 ; Wrzesniewski et al., 1997 ) or for practical reasons (e.g., the participants were asked questions that pertained not only to their individual assessment of work but also to various other parts of their lives; England, 1991 ; Warr, 2008 ). This diversity in the possible uses of the meaning of work makes it difficult to select a tool to measure it.

In French-speaking countries (Canada and Europe primarily), the previously mentioned scale created by Morin et al. ( 2001 ) has predominated and has repeatedly been used in research in occupational psychology and by practitioners in the field. Nevertheless, there has not been a complete validation of the scale (i.e., different forms of the same tool, only the use of exploratory factor analyses, and no similar structures found) that was the motivation for the current study.

The present study

The present article conceives of the meaning of work as representing a certain consistency between what an individual wants out of work and the individual’s perception, lived or imagined, of his/her work. It thus corresponds to the third definition of the meaning of work presented above—consistency between oneself and one's work (Morin & Cherré, 2004 ). This definition is strictly limited to the meaning given to work and the personal significance of this work from the activities that the work implies. Within this conceptual framework, some older studies adopted a slightly different cognitive conception, in which individuals constantly seek a balance between themselves and their environment, and any imbalance triggers a readjustment through which the person attempts to stabilize his/her cognitive state (e.g., Heider, 1946 ; Osgood & Tannenbaum, 1955 ). Here, the meaning of work must be considered a means for maintaining psychological harmony despite the destabilizing events that work might involve. In this view, meaning is viewed as an effect or a product of the activity (Brief & Nord, 1990 ) and not as a permanent or fixed state. It then becomes a result of person-environment fit and falls within the theory of work adjustment (Dawis, Lofquist, & Weiss, 1968 ).

Within this framework, a series of recurring and interdependent studies should be noted (e.g., Morin, 2003 , 2006 ; Morin & Cherré, 1999 , 2004 ) because they have attempted to measure the coherence that a person finds in the relation between the person’s self and his/her work and thus implicitly the meaning of that work. Therefore, these studies make it possible to understand the meaning of work in greater detail, meaning that it could be used in practice through a self-evaluation questionnaire. The level of coherence is considered the degree of similarity between the characteristics of work that the person attributes meaning to and the characteristics that he/she perceives in his/her present work (Aronsson, Bejerot, & Häremstam, 1999 ; Morin & Cherré, 2004 ). Based on semi-structured interviews and on older research related to the quality of life at work (Hackman & Oldham, 1976 ; Ketchum & Trist, 1992 ), a model involving 14 characteristics was developed: the usefulness of work, the social contribution of work, rationalization of the tasks, workload, cooperation, salary, the use of skills, learning opportunities, autonomy, responsibilities, rectitude of social and organizational practices, the spirit of service, working conditions, and, finally, recognition and appreciation (Morin, 2006 ; Morin & Cherré, 1999 ). Then, based on this model, a 30-item questionnaire was developed to offer more precise descriptions of these dimensions. Table 3 presents the items, which were designed and administered to the participants in French.

Some studies for structurally validating this questionnaire have been conducted over the years (e.g., Morin, 2003 , 2006 , 2008 ; Morin & Cherré, 2004 ). However, their results were not very precise or comparable. For example, the number of latent factors in the meaning of work scale structure varied (e.g., six or eight factors: Morin, 2003 ; six factors: Morin, 2006 ; Morin & Cherré, 2004 ), the sample groups were not completely comparable (especially with respect to occupations), and finally, items were added or removed or their phrasing was changed (e.g., 30 and 33 items: Morin, 2003 ; 30 items: Morin, 2006 ; 26 items: Morin, 2008 ). Yet the most prominent methodological problem was that only exploratory analyses (most often a principal component analysis with varimax rotation) had been applied. This scale was entirely relevant from a theoretical point of view because it offered a more specific definition of the meaning of work than other scales and, mainly, because some subdimensions appeared to be linked with anxiety, depression, irritability, cognitive problems, psychological distress, and subjective well-being (Morin et al., 2001 ). It was also relevant from a practical point of view because it was short and did not take much time to complete. However, its use was questionable because it had never been validated psychometrically, and a consistent latent psychological structure had not been identified across studies.

As an example, two models representing the structure of the 30-item scale are presented in Table 3 (Morin et al., 2001 ; Morin, 2003 , for the first model; Morin & Cherré, 2004 , for the second one). This table presents the items, the meaning of work dimensions they are theoretically related to, and the solution from the principal component analysis in each study. These analyses revealed that the empirical and theoretical structures of this tool are not stable and that the latent structure suffers from the insufficient use of statistical methods. In particular, there was an important difference found between the two models in previous studies (Morin et al., 2001 ; Morin & Cherré, 2004 ). Only the “usefulness of work” dimension was found to be identical, comprised of the same items in both models. Other dimensions had a maximum of only three items in common. Therefore, it is very difficult to utilize this tool both in practice and diagnostically, and complementary studies must be conducted. Even though there are techniques for replicating explanatory analyses (e.g., Osborne, 2012 ), such techniques could not be used here because not all the necessary information was given (e.g., all factor loadings, communalities). This is why collecting new data appeared to be the only way to analyze the scale.

More recently, two studies (which applied a new 25-item meaningful work questionnaire ) were developed on the basis of Morin’s scale (Bendassolli & Borges-Andrade, 2013 ; Bendassolli, Borges-Andrade, Coelho Alves, & de Lucena Torres, 2015 ). Even though the concepts of the “meaning of work” and “meaningful work” are close, the two scales are formally and theoretically different and do not evaluate the same construct.

The purpose of the present study was thus to determine the structure of original Morin’s 30-item scale (Morin, 2003 ; Morin & Cherré, 2004 ) by using an exploratory approach as well as confirmatory statistical methods (structural equation modeling) and in so doing, to address the lacunae in previous research discussed above. The end goal was thus to identify the structure of the scale statistically so that it can be used empirically in both academic and professional fields. Indeed, as mentioned previously, this scale is of particular interest to researchers because its design is not limited to measuring a general meaning of work for each individual; it can also be used to evaluate discrepancies or a convergence between a person’s own personal meaning of work and a specific work context (e.g., tasks, relations with others, autonomy). Finally, and with respect to previous results, the scale could be a potential predictor of professional well-being and psychological distress at work (Morin et al., 2001 ).

Participants

The questionnaire was conducted with 366 people who were mainly resident in Paris and the surrounding regions in France. The gender distribution was almost equal; 51.3% of the respondents were women. The respondents’ ages ranged from 19 to 76 years ( M = 39.11, SD = 11.25). The large majority of people were employed (99.2%). Twenty percent worked in medical and paramedical fields, 26% in retail and sales, and 17% in human resources (the other respondents worked in education, law, communication, reception, banking, and transportation). Seventy percent had fewer than 10 years of seniority in their current job ( M = 8.64, SD = 9.65). Only three people were retired (0.8%).

Morin’s 30-item meaning of work questionnaire (Morin, 2003 ; Morin et al., 2001 ; Morin & Cherré, 2004 ) along with sociodemographic questions (i.e., sex, age, job activities, and seniority at work) were conducted in French through an online platform. Answers to the meaning of work questionnaire were given on a 5-point Likert scale ranging from 1 ( strongly disagree ) to 5 ( strongly agree ).

Participants were recruited through various professional online social networks. This method does not provide for a true random sample but, owing to it resulting in a potentially larger range of respondents, it enlarges the heterogeneousness of the participants, even if it cannot ensure representativeness (Barberá & Zeitzoff, 2018 ; Hoblingre Klein, 2018 ). This point seems important because very homogenous samples were used in previous studies, especially with regard to professions.

Participants were volunteers, and were given the option of being able to stop the survey at any time. They received no compensation and no individual feedback. Participants were informed of these conditions before filling out the questionnaire. Oral and informed consent was obtained from all participants. Moreover, the Luxembourg Agency for Research Integrity (LARI on which the researchers in this study depend) specified that according to Code de la santé publique—Article L1123-7, it appears that France does not require research ethics committee [Les Comités de Protection des Personnes (CPP)] approval if the research is non-biomedical, non-interventional, observational, and does not collect personal health information, and thus CNR approval was not required.

Participants had to answer each question in order to submit the questionnaire: If one item was not answered, the respondent was not allowed to proceed to the next question. Thus, the database has no missing data. An introduction presented the subject of the study and its goals and guaranteed the participant’s anonymity. Researchers’ e-mail addresses were given, and participants were informed that they could contact the researchers for more information.

Data analyses

Three sets of statistical analyses were run on the data:

Analysis of the items, using traditional true score theory and item response theory, for verifying the psychometric qualities (using mainly R package “psych”). The main objectives of this part of analysis were to better understand the variability of respondents’ answers, to compute the discriminatory power of items, and to verify the distribution of items by using every classical descriptive indicator (mean, standard-deviation, skewness, and kurtosis), corrected item-total correlations, and functions of responses for distributions.

An exploratory factor analysis (EFA) with an oblimin rotation in order to define the latent structure of the meaning of work questionnaire, performed with the R packages “psych” and “GPArotation”. The structure we retained was based on adequation fits of various solutions (TLI, RMSEA and SRMR, see “List of abbreviations” section at the end of the article), and the use of R package “EFAtools” which helps to determine the adequate number of factors to retain for the EFA solution. Finally, this part of the analysis was concluded using calculations of internal consistency for each factor found in the scale.

A confirmatory factor analysis using the R package Lavaan and based on the results of the EFA, in order to verify that the latent structure revealed in Step c was valid and relevant for this meaning of work scale. The adequation between data and latent structure was appreciated on the basis of CFI, TLI, RMSEA, and SRMR (see “Abbreviations” section).

For step a, the responses of the complete sample were considered. For steps b and c, 183 subjects were selected randomly for each analysis from the total study sample. Thus, two subsamples comprised of completely different participants were used, one for the EFA in step b and one for the CFA in step c.

Because of the ordinal measurement of the responses and its small number of categories (5-point Likert), none of the items can be normally distributed. This point was verified in step a of the analyses. Thus, the data did not meet the necessary assumptions for applying factor analyses with conventional estimators such as maximum likelihood (Li, 2015 ; Lubke & Muthén, 2004 ). Therefore, because the variables were measured on ordinal scales, it was most appropriate to apply the EFA and CFA analyses to the polychoric correlation matrix (Carroll, 1961 ). Then, to reduce the effects of the specific item distributions of the variables used in the factor analyses, a minimum residuals extraction (MINRES; Harman, 1960 ; Jöreskog, 2003 ) was used for the EFA, and a weighted least squares estimator with degrees of freedom adjusted for means and variances (WLSMV) was used for the CFA as recommended psychometric studies (Li, 2015 ; Muthén, 1984 ; Muthén & Kaplan, 1985 ; Muthén & Muthén, 2010 ; Yang, Nay, & Hoyle, 2010 ; Yu, 2002 ).

The size of samples for the different analyses has been taken into consideration. A model structure analysis with 30 observed variables needs a recommended minimum sample of 100 participants for 6 latent variables, and 200 for 5 latent variables (Soper, 2019 ). The samples used in the present research corresponded to these a priori calculations.

Finally, according to conventional rules of thumb (Hu & Bentler, 1999 ; Kline, 2011 ), acceptable and excellent model fits are indicated by CFI and TLI values greater than .90 and .95, respectively, by RMSEA values smaller than .08 (acceptable) and .06 (excellent), respectively, and SRMR values smaller than .08.

Item analyses

The main finding was the limited amount of variability in the answers to each item. Indeed, as Table 4 shows, respondents usually and mainly chose the answers agree and strongly agree , as indicated by the column of cumulated percentages of these response modalities (%). Thus, for all items, the average answer was higher than 4, except for item 11, the median was 4, and skewness and kurtosis indicators confirmed a systematic skewed on the left leptokurtic distribution. This lack of variability in the participants’ responses and the high average scores indicate nearly unanimous agreement with the propositions made about the meaning of work in the questionnaire.

Table 4 also shows that the items had good discriminatory power, expressed by corrected item-total correlations (calculated with all items) which were above .40 for all items. Finally, item analyses were concluded through the application of item response theory (Excel tools using the eirt add in; Valois, Houssemand, Germain, & Belkacem, 2011 ) which confirmed, by analyses of item characteristic curves (taking into account that item response theory models are parametric and assume that the item responses distributions follow a logistic function, Rasch, 1980 ; Streiner, Norman, & Cairney, 2015 , p. 297), the psychometric quality of each item and their link to an identical latent dimension. These different results confirmed the interest in keeping all items of the questionnaire in order to measure the work-meaning construct.

Exploratory analyses of the scale

A five-factor solution was identified. This solution explained 58% of the total variance in the responses of the scale items; the TLI was .885, the RMSEA was .074, and the SRMR was .04. The structure revealed by this analysis was relatively simple (saturation of one main factor for each item; Thurstone, 1947 ), and the communality of each item was high, except for item 11. The solution we retained presented the best adequation fits and the most conceptual explanation concerning the latent factors. Additionally, the “EFAtools” R package confirmed the appropriateness of the chosen solution. Table 5 shows the EFA results, which described a five-factor structure.

Nevertheless, the correlation matrix for the latent factors obtained by the EFA (see Table 6 ) suggested the existence of a general second-order meaning of work factor, because the five factors were significantly correlated each with others. This result could be described as the existence of a general meaning of work factor, which alone would explain 44% of the total variance in the responses.

Internal consistency of latent factors of the scale

The internal consistency of each latent factor, estimated by Cronbach alpha and McDonald omega, was high (above .80) and very high for the entire scale (α = .96 and ω = .97). Thus, for S uccess and Recognition at work and from work ’ s factor ω was .93, for Usefulness ’s factor ω was .92, for Respect ’s factor ω was .91, for Value from and through work ’s factor ω was slightly lower and equal to .85, and finally for Remuneration ’ s factor for which ω was .87.

Confirmatory factor analyses of the scale

In order to improve the questionnaire, we applied a CFA to this five-factor model to improve the model fit and refine the latent dimensions of the questionnaire. We used CFA to (a) determine the relevance of this latent five-factor structure and (b) confirm the relevance of a general second-order meaning-of-work factor. Although this procedure might appear redundant at first glance, it enabled us to select a definitive latent structure in which each item represents only one latent factor (simple structure; Thurstone, 1947 ), whereas the EFA that was computed in the previous step showed that certain items loaded on several factors. The CFA also easily verified the existence of a second-order latent meaning of work factor (the first-order loadings were .894, .920, .873, .892, and .918, respectively). Thus, this CFA was computed to complement the previous analyses by refining the latent model proposed for the questionnaire.

According to conventional rules of thumb (Hu & Bentler, 1999 ; Kline, 2011 ), although the RMSEA value for the five-factor model was somewhat too high, the CFI and TLI values were excellent (χ 2 = 864.72, df = 400, RMSEA = .080, CFI = .989, TLI = .988). Table 7 presents the adequation fits for both solutions: a model with 5 first-order factors (as EFA suggests), and a model with 5 first-order factors and 1 second-order factor.

Figure 1 shows the model after the confirmatory test. This analysis confirmed the existence of a simple structure with five factors for the meaning of work scale and with a general, second-order factor of the meaning of work as suggested by the previous EFA.

figure 1

Standardized solution of the structural model of the Meaning of Work Scale

The objective of this study was to verify the theoretical and psychometric structure of the meaning of work scale developed by Morin in recent years (Morin, 2003 ; Morin et al., 2001 ; Morin & Cherré, 2004 ). This scale has the advantages of being rather short, of proposing a multidimensional structure for the meaning of work, and of making it possible to assess the coherence between the aspects of work that are personally valued and the actual characteristics of the work environment. Thus, it can be used diagnostically or to guide individuals. To establish the structure of this scale, we analyzed deeply the items, and we implemented exploratory and confirmatory factor analyses, which we believe the scale’s authors had not carried out sufficiently. Moreover, we used a broad range of psychometric evaluation methods (traditional true score theory, item response theory, EFA, and structural equation modeling) to test the validity of the scale.

Item analyses confirmed results found in previous studies in which the meaning-of-work scale was administered. The majority of respondents agreed with the proposals of the questionnaire. Thus, this lack of variability is not specific to the present research and its sample (e.g., Morin & Cherré, 2004 ). Nevertheless, this finding can be explained by different reasons (which could be studied by other research) such as social desirability and the importance of work norms in industrial societies, or a lack of control regarding response bias.

The various versions of the latent structure of the scale proposed by the authors were not confirmed by the statistical analyses seen here. It nevertheless appears that this tool for assessing the meaning of work can describe and measure five different dimensions, all attached to a general factor. The first factor (F1), composed of nine items, is a dimension of recognition and success (e.g., item 17: work where your skills are recognized ; item 19: work where your results are recognized ; item 24: work that enables you to achieve the goals that you set for yourself ). It should thus be named Success and Recognition at work and from work and is comparable to dimensions from previous studies (personal success, Morin et al., 2001 ; social influence, Morin & Cherré, 2004 ). The second factor (F2), composed of seven items, is a dimension that represents the usefulness of work for an individual, whether that usefulness is social (e.g., Item 22: work that gives you the opportunity to serve others ) or personal (e.g., Item 28: work that enables you to be fulfilled ). It can be interpreted in terms of the Usefulness of work and generally corresponds to dimensions of the same name in earlier models (Morin, 2003 ; Morin & Cherré, 2004 ), although the definition used here is more precise. The third factor (F3), described by four items, refers to the Respect dimension of work (e.g., Item 5: work that respects human values ) and corresponds in part to the factors highlighted in prior studies (respect and rationalization of work, Morin, 2003 ; Morin & Cherré, 2004 ). The fourth factor (F4), composed of four items, refers to the personal development dimension and Value from and through work (e.g., Item 2: work that enables you to learn or to improve ). It is in some ways similar to autonomy and effectiveness, described by the authors of the scale (Morin, 2003 ; Morin & Cherré, 2004 ). Finally, the fifth and final factor (F5), with six items, highlights the financial and, more important, personal benefits sought or received from work. This includes physical and material safety and the enjoyment of work (e.g., item 14: work you enjoy doing ). This dimension of Remuneration partially converges with the aspects of personal values related to work described in previous research (Morin et al., 2001 ). Although the structure of the scale highlighted here differed from previous studies, some theoretical elements were nevertheless consistent with each other. To be convinced of this, the Table 8 highlights possible overlaps.

A second important result of this study is the highlighting of a second-order factor by the statistical analyses carried out. This latent second-level factor refers to the existence of a general meaning of work dimension. This unitary conception of the meaning of work, subdivided into different linked facets, is not in contradiction with the different theories related to this construct. Thus, Ros et al. ( 1999 ) defined the meaning of work as a personal interpretation of experiences and interaction at work. This view of meaning of work can confer it a unitary functionality for maintaining psychological harmony, despite the destabilizing events that are often a feature of work. It must be considered as a permanent process of work adjustment or work adaptation. In order to be effective, this adjustment needs to remain consistent and to be globally oriented toward the cognitive balance between the reality of work and the meaning attributed to it. Thus, it has to keep a certain coherence which would explain the unitary conception of the meaning of work.

In addition to the purely statistical results of this study, whereas some partial overlap was found between the structural model in this study and structural models from previous work, this paper provides a much-needed updating and improvement of these dimensions, as we examined several theoretical meaning of work models in order to explain them psychologically. Indeed, the dimensions defined here as Success and Recognition , Usefulness , Respect , Value , and Remuneration from the meaning of work scale by Morin et al. ( 2001 ) have some strong similarities to other theoretical models on the meaning of work, even though the authors of the scale referred to these models only briefly. For example, the dimensions work centrality as a life role , societal norms regarding work , valued work outcomes , importance of work goals , and work-role identification (MOW International Research team, 1987 ) concur with the model described in the present study. In the same manner, the model by Rosso et al. ( 2010 ) has some similarities to the present structure, and there is a conceptual correspondence between the five dimensions found here and those from their study ( individuation , contribution , self-connection , and unification ). Finally, Baumeister’s ( 1991 ), Morin and Cherré’s ( 2004 ), and Sommer, Baumeister, and Stillman ( 2012 ) studies presented similar findings on the meaning of important life experiences for individuals; they described four essential needs that make such experiences coherent and reasonable ( purpose , efficacy - control , rectitude , and self - worth ). It is obvious that the parallels noted here were fostered by the conceptual breadth of the dimensions as defined in these models. In future research, much more precise definitions are needed. To do so, it will be essential to continue running analyses to test for construct validity by establishing convergent validity between the dimensions of the various existing meaning of work scales.

It is also interesting to note the proximity between the dimensions described here and those examined in studies on the dimensions that characterize the work context (Pignault & Houssemand, 2016 ) or in Karasek’s ( 1979 ) and Siegrist’s ( 1996 ) well-known models, for example, which determined the impact of work on health, stress, and well-being. These studies were able to clearly show how dimensions related to autonomy, support, remuneration, and esteem either contribute to health or harm it. These dimensions, which give meaning to work in a manner that is similar to the dimensions highlighted in the current study (Recognition, Value, and Remuneration in particular), are also involved in health. Thus, it would be interesting to verify the relations between these dimensions and measures of work health.

Thus, the conceptual dimensions of the meaning of work, as defined by Morin ( 2003 ) and Morin and Cherré ( 1999 ), remained of strong theoretical importance even if, at the empirical level, the scale created on this basis did not correspond exactly. The present study has had the modest merit of showing this interest, and also of proposing a new structure of the facets of this general dimension. One of the major interests of this research can be found in the possible better interpretations that this scale will enable to make. As mentioned above, the Morin’s scale is very frequently used in practice (e.g., in state employment agencies or by Human Resources departments), and the divergent models of previous studies could lead to individual assessments of the meaning of work diverging, depending on the reading grid chosen. Showing that a certain similarity in the structures of the meaning of work exists, and that a general factor of the meaning of work could be considered, the results of the current research can contribute to more precise use of this tool.

At this stage and in conclusion, it may be interesting to consider the reasons for the variations between the structures of the scale highlighted by the different studies. There were obviously the different changes applied to the different versions of the scale, but beyond that, three types of explanation could emerge. At the level of methods, the statistics used by the studies varied greatly, and could explain the variations observed. At the level of the respondents, work remains one of the most important elements of life in our societies. A certain temptation to overvalue its importance and purposes could be at the origin of the broad acceptance of all the proposals of the questionnaire, and the strong interactions between the sub-dimensions. Finally, at the theoretical level, if, as our study showed, a general dimension of meaning of work seems to exist, all the items, all the facets and all the first order factors of the scale, are strongly interrelated at each respective level. As well, small variations in the distribution of responses could lead to variations of the structure.

The principal contribution of this study is undoubtedly the use of confirmatory methods to test the descriptive models that were based on Morin’s scale (Morin, 2003 , 2006 ; Morin & Cherré, 1999 , 2004 ). The principal results confirm that the great amount of interest in this scale is not without merit and suggest its validity for use in research, both by practitioners (e.g., career counselors and Human Resources departments) and diagnostically. The results show a tool that assesses a general dimension and five subdimensions of the meaning of work with a 30-item questionnaire that has strong psychometric qualities. Conceptual differences from previous exploratory studies were brought to light, even though there were also certain similarities. Thus, the objectives of this study were met.

Limitations

As with any research, this study also has a certain number of limitations. The first is the sample size used for statistical analyses. Even if the research design respected the general criteria for these kind of analyses (Soper, 2019 ), it will be necessary to repeat the study with larger samples. The second is the cultural and social character of the meaning of work, which was not addressed in this study because the sample was comprised of people working in France. They can thus be compared with those in Morin’s studies ( 2003 ) because of the linguistic proximity (French) of the samples, but differences in the structure of the scale could be due to cultural differences between America and Europe. Nevertheless, other different international populations should be questioned about their conception of the meaning of work in order to measure the impact of cultural and social aspects (England, 1991 ; England & Harpaz, 1990 ; Roe & Ester, 1999 ; Ruiz-Quintanilla & England, 1994 ; Topalova, 1994 ; Zanders, 1993 ). In the same vein, a third limitation involves the homogeneity of the respondents’ answers. Indeed, there was quasi-unanimous agreement with all of the items describing work (see Table 4 and previous results, Morin & Cherré, 2004 ). It is worth examining whether this lack of variance results from a work norm that is central and promoted in industrialized countries as it might mask broader interindividual differences. Thus, this study’s protocol should be repeated with other samples from different cultures. Finally, a fourth limitation that was mentioned previously involves the validity of the scale. Concerning the content validity and because some items loaded similarly different factors, it could be interesting to verify the wording content of the items, and potentially modify or replace some of them. The purpose of the present study was not to change the content of the scale but to suggest how future studies could analyze this point. Concerning the construct validity, this first phase of validation needs to be followed by other phases that involve tests of convergent validity between the existing meaning of work scales as well as tests of discriminant validity in order to confirm the existence of the meaning of work construct examined here. In such studies, the centrality of work (Warr, 2008 ; Warr, Cook, & Wall, 1979 ) should be used to confirm the validity of the meaning of work scale. Other differential, individual, and psychological variables related to work (e.g., performance, motivation, well-being) should also be introduced in order to expand the understanding of whether relations exist between the set of psychological concepts involved in work and individuals’ jobs.

Availability of data and materials

The datasets generated and/or analyzed during the current study are available from the corresponding author.

Abbreviations

Confirmatory factor analyses

Comparative Fit Index

Exploratory factor analyses

Luxembourg Agency for Research Integrity

  • Meaning of work

Tucker Lewis Index of factoring reliability

Root mean square error of approximation

Standardized root mean square residual

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Pignault, A., Houssemand, C. What factors contribute to the meaning of work? A validation of Morin’s Meaning of Work Questionnaire. Psicol. Refl. Crít. 34 , 2 (2021). https://doi.org/10.1186/s41155-020-00167-4

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Abstract and Figures

The three?level model of meaningful work proposed by Steger, Dik, & Duffy (2012). Each level represents a degree of transcendence from the worker's specific job. Meaningful work includes: (1) Workers' perceptions of meaning or purpose in job or career activities (in the center circle); (2) The capacity for work to be in harmony with and to help nurture meaning in the worker's broader life, which is one level of transcendence higher than the job itself (in the second circle); and (3) the opportunity to positively impact or benefit the greater good of stakeholders in the worker's community, society, or even planet, which is another level of transcendence higher (in the outer circle). Source: Steger et al. (2012). Reproduced with permission of Sage Publications, Inc.

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Is this work? Revisiting the definition of work in the 21st century

Journal of Work-Applied Management

ISSN : 2205-2062

Article publication date: 23 June 2023

Issue publication date: 27 September 2023

The purpose of the study was to specify the perceived outdated nature and lack of definitional clarity associated with the concept of work and further to outline that the nature of work has dramatically changed in the 21st century, while definitions of work referenced in research remain those that were dominant in the previous century. Lastly, the study aimed to propose an updated conceptualisation and definition of work to aid future research.

Design/methodology/approach

A scoping literature review was adopted as the methodology guiding the study. A scoping review is particularly suited to identifying the conceptual boundaries on a given multi-disciplinary topic and is used to map the key concepts underpinning a research area as well as to clarify working definitions.

Nine main themes underpinning the concept of work were extracted from the extant literature. These were assimilated with contemporary literature across multiple disciplines. Contexts of work as they relate to dimensions of work and workspace are developed and visualised. A proposed contemporary definition of work is presented.

Research limitations/implications

The aim of the study was to address the problem with current and future research continuing to refer to traditional conceptualisations of work, while the nature of work has dramatically changed. The findings are preliminary and intended to stimulate further discourse towards a greater consensus of a definition. The implications of proposing an updated definition of work is that it is intended to better inform future research reflective of its multi-disciplinary and significantly changed nature.

Practical implications

The implications to practice are the main impetus of this study. The authors found that research associated with work was being confounded by traditional and outdated interpretations, excluding alternative forms of work or not recognising its multi-dimensionality. It is proposed by the paper that an updated conceptualisation of the nature of work in this era, as it is reflected across disciplines and practice, would positively contribute to the understanding, management and conceptualisation of work in practice.

Originality/value

A systematic literature review across disciplines of the definition of work will reveal the outdated nature and disparate interpretation of the concept of work. An inclusive, multi-disciplinary and contemporary definition of work has not been suggested. This scoping review was conducted to address this problem and gap in the literature. Further, this paper presents a multi-dimensional and spatial conceptualisation of work that is proposed to better inform future research and practice associated with work.

  • Definition of work
  • Meaning of work

van der Laan, L. , Ormsby, G. , Fergusson, L. and McIlveen, P. (2023), "Is this work? Revisiting the definition of work in the 21st century", Journal of Work-Applied Management , Vol. 15 No. 2, pp. 252-272. https://doi.org/10.1108/JWAM-04-2023-0035

Emerald Publishing Limited

Copyright © 2023, Luke van der Laan, Gail Ormsby, Lee Fergusson and Peter McIlveen

Published in Journal of Work-Applied Management . Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcode

1. Work in the 21st century

The United Nation's Declaration of Human Rights states in Article 23: “Everyone has the right to work, to free choice of employment, to just and favourable conditions of work, and to protection against unemployment … the right to equal pay for equal work”. With that goal not achieved a half century later, the International Labour Organization articulated the Decent Work Agenda as an added dimension of human rights. Still grappling with how to achieve full and productive employment and decent work, the United Nations incorporated the Decent Work Agenda in their 17 Sustainable Development Goals, to promote “sustained, inclusive, and sustainable economic growth, full and productive employment, and decent work for all”. Progress towards securing these rights and goals which acclaim work as a self-evident good is undermined by a paradox: We are still left wondering; What is work?

Traditional perspectives of work define it in narrow terms, including work as functional and transactional framed in terms of a predetermined workplace (e.g. Colbert et al ., 2016 ; Lester and Costley, 2010 ), remuneration (e.g. Guthrie, 2008 ; Kustini and Purwanto, 2020 ) and/or employment (e.g. Pettinger, 2019 ; Taylor, 2004 ). Indeed, these traditional perspectives of work have been dominant within research discourse on the topic throughout the 19th and 20th centuries.

However, literature emerging in the early part of the 21st century points towards a need to revisit what work means to individuals and humanity more broadly. This is especially relevant within the context of rapid technological and social change in this era of the so-called Fourth Industrial Revolution ( Hirschi, 2018 ; Schwab, 2016 ). More recently, the dramatic changes in the nature of work have become more stark. The COVID pandemic not only forced a significant shift towards remote work enabled by technology, while emptying city office blocks, but also forced many production workers to remain at home, closing down whole industries and resulting in increased economic hardship for those unable to go to work. Similarly, while we have anticipated the automation of work in terms of artificial intelligence, its rapid adoption have given rise to a dramatic increase in the discourse as to what constitutes work and what forms of human work will become redundant.

More than a decade ago for example, Dejours (2007 , p. 72) maintained “there is no such thing as purely mechanical work” and Deranty (2009 , p. 70) argued that “the definition of work remains a serious theoretical problem”. Veltman (2016) concurs and observes that “yet the topic of work has received only minor attention in leading theories of justice and human flourishing”. The purpose of the present research is to examine the dimensions which define the nature of work at the individual unit level and consider what a suitable definition of work might be for the 21st century. Following on from the recommendation by Cho (2020 , np) that future research should consider micro and macro boundaries in “advancing our knowledge on the boundaries in work and careers”, we revisit the micro boundaries of the notion of work.

2. Conventional conceptualisations

Earlier industrial era literature about work was primarily concerned with human productivity in exchange for remuneration and the conditions under which such transactional exchanges took place. This focus reflected and was largely shaped by liberal economic theory as articulated by Smith (1937) and theories of labour, such as those of Marx ( Sayers, 2005 ). The work of Fayol (1916) and Taylor (1947) further served to stimulate research in terms of the management of labour and the outputs of work as part of an increasingly dominant economic rationale associated with productivity and the performance of work, particularly in relation to the organisation of work.

Conceptualisations of work have changed over time and reflect transitions from agrarian to industrial and post-industrial production systems ( Savickas and Baker, 2005 ). Accordingly, “the meaning of work literature is the product of a long tradition of rich inquiry spanning many disciplines” ( Rosso et al ., 2010 ), such as applied psychology (vocational psychology, organisational and industrial psychology), sociology and economics. However, “the field of industrial sociology (work and occupations) … has moved it even farther away from the study of work to a concern with individuals conceived as economic beings” ( Simpson, 1986 , p. 578). Furthermore, “conceptual confusion” has resulted in what Deranty (2009 , p. 70) described as “operating on an ultra-thin definition of work … [that] claim[s] for sole authority in the other social sciences”. Conceptual confusion and concomitantly thin or disparate operational definitions of work hamper research and should be countered with conceptual clarity ( Bringmann et al ., 2022 ).

Work is commonly defined in terms of outputs of production or as associated with notions of employment and capital, most notably the problematic term “human capital” ( Tan, 2014 ). However, highly cited work by Casey (1995) suggests that based on this, “the industrial legacy of the centrality of production and work in social and self-formation hovers precipitously with the post-industrial condition in which work is declining in social primacy”. This continues to hold true ( Casey, 2013 ). It appears that the precipitous balance between research being guided by such industrial era “thin definitions” associated with economic perspectives fail to capture the context of significant societal changes, due to dramatic shifts in technology, knowledge systems, human mobility and production systems. Furthermore, traditionally dominant definitions of work no longer capture its full meaning and, therefore, the multi-disciplinary field of work studies requires a comprehensive analysis of work's theoretical foundations from a people-centred and current pragmatic perspective ( Provis, 2009 ; Rosso et al ., 2010 ).

More recently the literature has broadened to include the psychology of working ( Blustein, 2006 , 2013 ; Duffy et al ., 2016 ). Yet despite what seem to be advances in the research on work, the notion of work largely remains within the paradigm of employment and economic theory. Rarely has the literature acknowledged, as an example, unpaid or unrecognised forms of work, such as voluntary service ( Taylor, 2004 ), entrepreneurial activities, subsistence activities, modern slavery ( Craig, 2017 ) or the care work done by women without compensation ( Richardson, 2012 ; Richardson and Schaeffer, 2013 ) or those in forced marriages ( Fellows and Chong, 2020 ). It is the work of women which seems invisible to the dominant paradigm and discourse of economics ( Shah, 2006 ).

Humans are “capable of genuine intentionality, forethought, self-regulation, and self-reflectiveness”;

“Humans are meaning-making organisms who consciously and subconsciously construct both global and particular meanings for life experience”;

“Individuals enact a constellation of life roles that interact in varied and complex ways … [and] work to occupy one of these life roles and define working broadly to include any activity or effort, paid or unpaid, that is directed toward accomplishing or producing something that fills a societal or organizational need”;

“Humans, by necessity, live in societies bound by common needs and mutual service and that work role activities therefore have direct or indirect social implications that vary in magnitude”; and

“Obstacles to meaningfulness and purpose at work are present on multiple levels (e.g. individual, organisational, societal) but also that these obstacles are amenable to change”.

However, the failure to recognise work as an innate human function and one which is not always defined in terms of remuneration, employment or place has depersonalised human work activity. In turn, this has allowed conditions of exploitation and economic rationalism to remain unchecked for many decades ( Dejours, 2002 ; Deranty, 2009 ; Mauss, 1979 ). The concept of the division of labour conforms to a “logic that is strictly functional and instrumental” ( Deranty, 2009 , p. 74) within an economic rationalism that does not fully take into account the personal and social fluidity of work. Even when addressed outside its economic paradigm, a primary focus of the psychology of work has traditionally aimed at the clinical, pathogenic nature and impact of experiences of work, particularly those usually associated with employment ( Deranty, 2009 ). In an attempt to resolve this problem within psychology, Blustein (2011) promoted the relational theory of working as a way in which the meaning of work can be better understood.

An examination of the chronological development of the notion of work forms a foundation for what is proposed as moving towards a more holistic definition of this important human function. We seek to progress the recognition of work as a broader concept and start by building on the foundational definitions promoted by the sociology and psychology of work.

3. Decent work?

Work has evolved alongside changing societal trends driven most recently by the industrialisation of society ( Laurance, 2019 ). In the mid-1960s, work was increasingly promoted as a virtue for the development of an individual's career ( Quey, 1968 ) and became regarded as a vehicle for the development and expression of an individual's self-concept ( Super, 1957 ). However, the definition of work at this time continued to be the theme of linking the individual to a form of economic benefit and incompatible with, or at least indifferent to, individual and political freedom ( Deranty, 2009 ). As Quey (1968 , p. 223) stated at that time, “work is purposeful mental and physical human activity which deliberately points beyond the present by creating economic products or values to be consumed in the future”. The understanding of the work environment within which this economic exchange was to occur was predominantly restricted to a place, with set times and well-defined procedures and outcomes.

Yet Quey (1968) also opposed the potential depersonalisation of the human being within the context of work and as such shifted the economic benefit perspective from the system (i.e. the macro-environment) to the individual (i.e. the micro-environment) as a beneficiary. The general work–remuneration relationship however continued to be a key component of the argument for work, but this shift started a recognition of broader meaning that is ascribed to work. Thus, Quey (1968 , p. 225) concluded, “In order to preserve its own health, society periodically may need to revalidate its overarching values and purposes including the meaning and role of work in society”. This paper furthers that dialogue about the role of work but has as its key premise, work as a fundamentally innate human concept influenced, but not defined, by an economic rationale of remuneration and place of production.

In this Fourth Industrial Revolution ( Schwab, 2016 ), the world of work is fast moving from an information age to a conceptual age where the processing and conceptualisation of new knowledge and ideas typifies much work ( European Foundation of Management Development, 2012 ). As such, the conceptual age has been significantly influenced by traditional liberalism and the notion of freedom of the individual. Driven primarily through technological progress, increasing access to information, social networks and media and communications, emphasis on individual freedom has become more widespread and acceptable. Enabled by dynamic technological platforms, global and cultural communications have exponentially increased creating “a new wave of networked social movements [positive and negative], which have been mobilized in the urban space and in the institutional space [introducing new] movements and actors of social change” ( Castells, 2012 , pp. 19–20). These shifts have altered the nexus between individuals and work in an unprecedented way.

The impact of a largely networked global society ( Castells, 2010 ) has added to what we refer to as the “liberalisation of work”, making certain previously defining dimensions redundant. In short, we put forward the “liberalisation of work” to mean that individuals are increasingly being liberated from the confines of traditional notions of work in favour of shifting the emphasis towards finding meaning in and/or an awareness of their relationship with work. The liberalisation of work seeks to acknowledge all forms of work as an inclusive concept whose purpose is to accommodate the multitudes of positive or negative outcomes resulting from work and the changes currently transforming the “social structure of society” ( Castells, 2012 ).

Evidence in the last 15 years suggests there is increased uncertainty among those who work in the traditional workplace as to the existential nature of work in their lives, which in turn has eroded the individual's confidence in the idea of having a predictable long-term career or secure employment ( Blustein, 2006 ; Blustein et al ., 2013 ; Savickas et al ., 2009 ). It is increasingly evident that an individual's purpose and work meaningfulness can no longer be generally attributed to a stable career or place of work ( Paulík et al ., 2014 ; Pratt and Ashforth, 2003 ; Steger et al. , 2009 ; Steger et al ., 2012 ). Consequently, traditional and persistent paradigms which describe work are questionable and a broad, multi-disciplinary revisiting of the concept is required.

4. Towards conceptual clarity and thick definitions of work

Definitions of work have been referred to by Deranty (2009) as thin and thick. “Thin” definitions of work have been typified by narrowly categorised descriptions that are strictly functional and instrumental and usually occur within a particular economic worldview. Clot (2004 , p. 98) subsequently termed this narrow focus of work as “directed activity”, suggesting the organisation of human effort towards productivity aims. However, Wisner (1995) had earlier made the critical observation that the modelling of work activities under these definitions rarely accounts for real-world experiences, overlooking working conditions and the consequence to lived experiences of the worker.

In contrast, “thick” definitions account for the richer subjective meanings ascribed to work, including personal interpretation and investment in work activities. The relationship of thin and thick descriptions of work provided by Deranty has been provided in Table 1 .

To resolve the suggested dichotomy between thin and thick definitional approaches to the construct of work, as well as considering that not all work is defined by institutional productivity parameters, remuneration, employment and workplace, it is necessary to conduct a review of the theoretical perspectives of work.

This paper therefore systematically explores the literature and seeks to propose a tentative revised definition of work for the 21st century in order to promote a common understanding of the universal nature of work. A more human-centric and pragmatic perspective is arguably needed to accommodate rapidly changing notions of work, where it takes place, what it is exchanged for and how it is recognised in the different lines of scholarly enquiry. As Provis (2009 , p. 124) suggests, “The point here is not that we need to get rid of the idea of work or define it precisely for everyday purposes, but that we need to do so for purposes of theory and policy development”. As such the paper therefore aims to review the literature and work towards a more contemporary conceptual definition of work.

A scoping literature review is a relatively newer form of mapping the literature on a given multi-disciplinary topic ( Arksey and O'Malley, 2005 ; Cacchione, 2016 ; Peters et al ., 2015 ). Scoping studies, as defined by Arksey and O ' Malley (2005 , p. 21), “aim to map rapidly the key concepts underpinning a research area” and can “be used to map the key concepts underpinning a research area as well as to clarify working definitions, and/or the conceptual boundaries of a topic” ( Peters et al ., 2015 , p. 141). Munn et al . (2018) agree that scoping reviews are appropriate to clarify key concepts or definitions in the literature. A key premise of the study is that current definitions of work are inadequate in capturing the contemporary nature of work. As such, the paper's intent is to collate a multi-disciplinary perspective of work including its conceptual boundaries. To this end, a scoping review was deemed an appropriate initial research method.

Tricco et al . (2016) further indicate that scoping reviews are helpful in exploring evidence to inform future research. The purpose of this paper aligns with the motivation to conduct a preliminary study that (1) recognises the conceptual limitations of current definitions of work, (2) identifies underlying dimensions and parameters of what may constitute a contemporary, multi-disciplinary definition and (3) stimulates future discourse and research in order to contribute to theory.

In contrast to a systematic literature review, where the investigation is structured and defined by narrow parameters to exhaustively answer a clearly defined question, a scoping review can utilise a flexible approach to search for descriptive meaning surrounding a topic of interest setting a foundation for further research ( Peters et al ., 2015 ). Similarly, while an integrative review seeks to provide a comprehensive and holistic understanding of a particular topic in order to generate new theory ( Torraco, 2005 ), a scoping review is a preliminary assessment of the nature of the phenomenon and may inform a more exhaustive review ( Grant and Booth, 2009 ). As the intent of this paper is to stimulate further discourse and future research, a scoping review was deemed an appropriate approach.

Identifying the research question;

Identifying the relevant studies and study selection (i.e. inclusion criteria);

Study selection;

Charting the data;

Collating, summarizing and reporting the results;

Step 1: Identifying the research question

The key premise of this paper is that work is an “area in philosophy where progress has stalled” ( Deranty, 2009 , p. 70), yet its nature is irrevocably changing. Further, those previously dominant definitions of work do not adequately capture its current nature. In order to address this apparent stagnation despite very clear indications to those certain paradigms continue to frame academic discourse, the primary purpose of this scoping literature review was to identify and examine current definitions or pseudo-definitions of work within a multi-disciplinary context. This was deemed necessary as definitions typically inform the theories of disciplines and the operationalisation of concepts which, in the case of “work”, have arguably led to the fragmented nature of current research.

The question that the scoping review seeks to address is What are the definitions of “ work ” in peer reviewed literature and do they capture the broad and rapidly changing nature of work in the 21 st century?

Step 2: Identifying the relevant studies and study selection (i.e. inclusion criteria)

Decisions have to be made at the outset about the coverage of the scoping review ( Peters et al ., 2020 ). These are determined based on the purpose of the review and within the constraints of resources and time. The search strategy for this paper adopted Peters et al .'s (2020) three-stage process: (1) initial search of multiple databases to determine the extent of use of the term “work”; (2) an analysis of the key words “definition of work” and “work is defined as” as contained in retrieved papers and (3) search of the reference list of retrieved papers to identify additional sources.

As this study is concerned with definitions of work as presented and cited in academic literature, only peer-reviewed published academic articles related directly to the definition or description of work were considered. Grey literature was not included as the study sought to identify definitions as peer reviewed and cited in mainstream disciplines.

The point of departure for the review was that if the notion of work is universal in nature, its definition should be clear, be current and not be constrained by disciplinary boundaries. As such, search results across all disciplines were considered.

Step 3: Study selection

Due to the preliminary nature of a scoping review, two main databases were selected for the review search. A number of databases were considered including Google Scholar, Primo.exlibris, Scopus and Web of Science. It was deemed that due to the preliminary nature of the study, Google Scholar and Primo.exlibris would provide sufficient coverage and avoid duplication of the results.

A Google Scholar search yielded approximately 19,300 results that referred to meanings attributed to “work”. These mostly included articles associated with “the meaning of work”, “organising work”, “psychology of work”, “employment and work”, “work productivity”, “socialisation of work” and “workplace”, and search for academic publications between 2010 and 2020 yielded 9,920 results reflecting these different fields. These results confirmed the vast breadth and application of the notion of work, yet few moved beyond being descriptive and actually defined ”work”.

A second search using Primo.exlibris group for the term “definition of work” yielded 157 results. These papers were cross-checked with the results from the Google Scholar search. After applying a test that the paper must contain the phrases “work is defined as” or “the definition of work is”, 22 papers and two UN Charters were left to review.

Step 4: Charting the data

Step 4 identifies and presents the definitions and main themes that have emerged from the selected literature. A thematic analysis of retrieved sources was conducted that sought to identify the main themes that were associated with “work”. These definitions and themes have been tabulated and presented in Table 2 .

Step 5: Collating, summarizing and reporting the results

Based on the key literature identified in step 4, the data were collated and presented for analysis.

6. Summary and analysis of results

From this preliminary scan of the literature as presented in Table 2 , there are indications that work has predominantly been defined in terms of its being associated with the workplace, remuneration and employment. In contrast, some mention has been made of the need to adopt a more holistic view ( Veltman, 2015 ), understand work as a mental and physical human activity common to all humans ( Quey, 1968 ), identify work as fundamentally inherent to all people's lives ( Harpaz and Fu, 2002 ), be inclusive of all workers within a broader experiential and psychological context ( Duffy et al ., 2016 ), see work as relational made up of social interactions ( Blustein et al ., 2019 ) and see work as critical in the development of all individuals ( Blustein et al ., 2019 ; Duckenfield and Stirner, 1992 ; Issa, 2014 ; Duckenfield and Stirner, 1992 ; Issa, 2014 ; Duffy et al ., 2016 ; Mikkonen et al. , 2017 ; Blustein et al ., 2019 ).

It appears that there is growing recognition that work is a complex relational dynamic rather than a purely transactional exchange ( Richardson, 1993 ; Casey, 1995 ; Provis, 2009 ; Blustein, 2013 ; Veltman, 2016 ; Blustein et al ., 2019 ). Not all work is remunerated ( Duffy et al ., 2016 ).

Three papers discuss the nature of the definitions of work. As noted earlier, Deranty (2009) points to the conceptual confusion associated with “work” and that its philosophical development has stalled. He suggests that “today the area [of work] suffers from added conceptual confusion since economic theory, operating with an ultra-thin definition of work, has come to occupy a position of quasi-hegemony in policy debates and is pressing its claim for sole authority in the other social sciences” ( Deranty, 2009 , p. 70). Dejours' perspective was that work can be constitutive and normative and rejects the notion that work is only functional and instrumental ( 2002 , 2007 ). The observation justifies the criticism that not all work is transactional and related to economic precepts but rather that its description should be broader and normative so as to capture the full human experience of work.

Blustein recognises the social aspects of work especially in its being relational in nature ( 2011 , 2013 ). The “real world” of work impacts people's lives, and he asserts that the sociology of work cannot be ignored. The dynamic human interchanges and interactions (both positive and negative) that occur during work processes help to define the nature of work.

The main themes associated with work that were identified include the following.

6.1 Work as employment

Veltman (2016) points out that work can be autonomous or lack autonomy such as that conducted by the stay-at-home parent, family carers, slaves, volunteers or the subsistence farmer, amongst others. Work that lacks autonomy largely falls outside the parameters of employment. One is compelled to agree that despite not being employed and largely unpaid, such work influences agency, identity and self-worth but is not easily definable ( Geens and Vandenbroeck, 2014 ; Pfau-Effinger et al ., 2009 ). Albeit that most work is in the form of employment, definitions of work that make employment defining conditions to qualify as work are flawed. It is necessary to frame future discourse in a way that is able to accommodate unpaid work and work outside of employment.

6.2 Work and the workplace

It is increasingly apparent, especially as illustrated by the COVID-19 pandemic, that the notion of workplace is fluid ( Issa, 2014 , Veltman, 2016 ) and probably better described in terms of a “space within which work takes place”. A spatial model for work, as Harrison and Dourish (1996) argued, includes features of relational orientation, proximity, partitioning and presence relative to the real world. The creation and existence of new spaces where “work” is carried out encompass new behavioural and collaborative interactions that have become exponentially more prevalent. Workplaces, as locales of organised work, are still predominant but are no longer an apt or defining feature of work. Instead, it is suggested that space for working is three dimensional, with multiple determinants and possibilities of how that space is organised into a locale including the digital environment that locates human action and behaviours ( Harrison and Dourish, 1996 , p. 69). Dourish (2006 , p. 300) further concludes that “digital technologies have colonized other locations and other aspects of life” including that of work.

6.3 Work as ubiquitous

Quey (1968 , p. 223) defined work as “purposeful mental and physical human activity which deliberately points beyond the present”. Richardson broadened the definition of work as “embedded in family and personal lives, as well as in paid employment” ( 1993 p. 431). All people work as noted by Veltman (2016) .

6.4 Work as relational

Blustein (2011 , 2013) and Blustein et al . (2019) have appropriately concentrated on exploring aspects of the psychology of work to strengthen and theorise the importance of human relationship as experienced in the context of work. They suggests that “work-based decisions, transitions, and experiences are not simply the expression of individual agency, but are rooted in interactions with a broad array of external influences … new theoretical positions are needed for the 21st century that encompass an expanded vision of working along with an integrative understanding of the complex, reciprocal relationships between work and other life domains” ( Blustein, 2013 , pp. 1–2). Blustein therefore agrees that due to the dramatic global societal changes of this century, a new, holistic theoretical position is needed to accurately describe work.

6.5 Work and meaningfulness

Work is also one of the most significant contributing factors to one’s inner life and development … Work is the means by which we form our character and complete ourselves as persons … Work is the yardstick by which we measure ourselves against others. It is the means by which we establish our rank, role, and function within a community. Work not only conditions our lives; it is the necessary condition for life ( Gini, 2001 , pp. 2–3).

There is general agreement in the papers sourced that work needs to offer meaning. That said, not all work may be very meaningful and certain forms of work may confound the idea that work has any formative value.

6.6 Work and career

In the early 1900s, the term “career” aligned with the choice and development of a vocation and a career path often determined by an organisation. However, there has been a significant shift over the last few decades in that individuals are now mostly responsible for the development of their own career or, more recently, different careers ( European Foundation of Management Development, 2012 ). The variability of careers and transferability of skills have made career changes more common and less definable as categories work. Instead, it has been recognised since the later stages of the 20th century that “developmental considerations need to be shifted from a focus on career to a more central focus on the individual” ( Richardson, 1993 , p. 431).

Blustein similarly differentiated working from the notion of a career. He notes ( 2011 , p. 3) that the “conceptual view of working is not meant to replace the notion of career; rather, working is viewed as set of activities that, under optimal circumstances, may yield greater volition levels in educational and work-based options”. These activities may culminate in a particular career, but the work itself is not defined by it.

6.7 Work and well-being

Sigmund Freud believed that work was an essential and a fundamentally human characteristic, describing it as a “pillar of a healthy life”. Duffy and Dik (2013) , in defining work as a “calling”, propose a linkage between work-related and general well-being outcomes. They indicate that connecting one's work with a tangible, pro-socially oriented purpose rather than a career is more relevant in modern times. Simpson (1986 , p. 563) warns that “the field of industrial sociology (work and occupations) has shifted from work and workers to economic concerns, and has transformed our conception of the worker from a social actor to a passive object acted on by macro level forces”. Indeed, Cho (2020) suggests that work should instead be determined in terms of role boundaries that impact health outcomes rather than economic considerations only. He points out the negative health outcomes that result from work that falls outside of role boundaries as perceived by the individual. Duffy and Dik (2013 , p. 140) conclude that conceptions of work should be “inclusive of all workers, capturing the primarily contextual and secondarily psychological variables that impact the ability to secure decent work, satisfy needs, and experience work fulfilment and well-being”.

6.8 Work and remuneration

Traditionally, remuneration refers to the way in which employees are rewarded in exchange for their efforts ( Kessler, 2000 ). Bloom and Milkovich (1992 , p. 22) defined remuneration as a “bundle of returns offered in exchange for a cluster of employee contributions”. The transactional nature of remuneration has thus traditionally framed work as a product of one's effort in exchange for financial rewards. This perspective of work is overwhelmingly still referred to as defining work (and is able to accommodate the nuances and shifts described above). However, it has also been observed that a view fixated on the transactional nature of work threatens the inherent meaning, social and individual value of work by becoming commoditised and packaged to reflect financial value ( Cho, 2020 ). As such, remuneration is mostly seen as the organisation of a payroll system in relation to a performance assessment system of work outcomes ( Sardjana et al ., 2019 ) rather than work relative to human capability, expression of professional identity or agency and self-realisation. This standard view has also driven much of the research on work especially as it relates to enhancing productivity, processes and costs/benefits (See, e.g. Martono et al. , 2018 ).

Despite sufficient evidence and recognition in the literature that (1) work may take place in the absence of remuneration ( Veltman, 2016 ), (2) work is a service to society and a community ( Issa, 2014 ) and (3) work is relational and an expression of self-determination including the “full spectrum of work that people do to survive” ( Blustein, 2011 , p. 3), a consensual and holistic definition of work that includes these perspectives remains elusive.

6.9 Work as innate function

Harpaz and Fu (2002 , p. 569) note that “work constitutes a pivotal and fundamental component of people's lives”. Blustein's (2011 , p. 3) examination of the definition of work includes additional concepts such as “working is a central aspect of life, providing a source of structure, a means of survival, connection to others and optimally a means of self-determination”.

In summary, work is not constrained by employment, place, remuneration or career even though it is often linked to these notions. The next section discusses emergent perspectives about work in the scholarly literature.

7. Discussion

Monumental changes have taken place in the way work and workers are conceived throughout the period of industrial modernisation. The literature reflects these shifts from early 19th century works to more recent studies. A thematic analysis of located literature identified using a scoping review methodology is presented above. The analysis identified themes associated with work conceived in studies in terms of employment, the workplace, being ubiquitous, being relational, being meaningful, career, well-being, remuneration and as an innate human function. Despite the array of themes, they have not been assimilated into a cohesive concept that balances the internal (individual, human centric and experiential) perspectives of work with the external (contextual and economic) conceptions of work.

Commentators are increasingly acknowledging that the values and attributes of dignity, equality and mutual respect are important conditions for decent work. This has allowed more recent extensions of studies of “work” to include individual interests in the development of knowledge and capabilities ( European Foundation of Management Development, 2012 ; Gherardi, 2009 ; Smith, 2001 ); human-centric resource management ( Dal Poz et al. , 2009 ); work as an expression of human foresight, intentionality and self-reflectiveness ( Dik and Duffy, 2009 ); qualities of leadership in the workplace ( Gill, 2002 ; Kumar, 2015 ); emotions and organisational behaviour ( Benozzo and Colley, 2012 ) and workplace reflection ( Nilsen et al. , 2012 ), amongst others.

Despite the emergence of these perspectives in more recent studies, the traditional understanding of work defined in terms of employment and economic rationalism continue to guide dominant discourses despite no longer being universally applicable ( Veltman, 2016 ). However, the literature does agree across disciplines that work is largely relational in nature ( Blustein et al ., 2019 ) and is a social construct that differs according to context and culture ( Cruess and Cruess, 2016 ).

Dik and Duffy (2009) argue there is congruence between work and the subjective perceptions of life satisfaction and vocational identity/conditions. These are not solely aspirational but functional, thus representing a spectrum of internal individual experiences and external functional conditions and metrics with which it can be perceived. The point being made is that humans' perception of work and their response to it is experiential and relative to their environment but functions within a rational and instrumental context. Blustein et al . (2019 , p. 5) expand on this by suggesting that the Psychology of Working Framework focuses on the “role of social connections throughout many aspects of contemporary working … the relational theory present(s) a set of propositions about the interpersonal and social contexts of working, encompassing relationships throughout the life span”. This reinforces the idea of an internal and external dichotomy framing how work can be conceived.

Employment was often historically associated with achieving one's career, worth or identity through work and employment ( Gini, 2001 ; Tausig, 2013 ). However, as Pouyaud (2016 , p. 12) states, “Work [employment] has become increasingly precarious and constraining. This change does not only concern the poorest countries, where work may not even allow survival, but also rich ones, where work has become a form of alienation, even if it provides sufficient income”. There is growing awareness that work is increasingly able to alienate individuals from society especially when the work is ad hoc and conducted in virtual spaces. Despite this awareness, the conceptualisation of work in the literature is not yet broad enough to inform these new lines of enquiry.

Arguably, the world of work serves to broaden the individual's experience and its influence on self-esteem, self-worth and the individual's physical and psychological well-being ( Burke, 2012 ; Kuhnert and Palmer, 1991 ). Meaningful work is closely associated with worker well-being ( Steger et al ., 2012 ) and increasingly extends beyond the traditional parameters of workplace. Well-being can be associated with positive relationships; personal growth; purpose in life; environmental mastery; self-acceptance; and autonomy ( Wright and Huang, 2012 ) or by its components such as psychological well-being (e.g. happiness), physical well-being (e.g. health) and social well-being (e.g. friendships and human interaction) ( Grant et al. , 2007 ). The interpretation of well-being, happiness and life satisfaction are terms increasingly associated with meaningful work ( Steger et al. , 2009 ) and require further investigation across different physical, social and political structures and economic systems ( Selezneva, 2011 ). Broadening the conceptualisation of work therefore is necessary to be more representative of the lived experience of work while being more inclusive of different forms of work that fall outside of employment.

Work experiences are based on the interaction between the person and his or her environment. Experiences are influenced by the confluence of an individual's desires, needs, purpose and capacities and the individual's environment, i.e. the world, both physically and increasingly digital. Provis (2009) notes that in the past, the notion of work was primarily given meaning within the context of an institution and/or workplace. This arguably is embedded in the idea that one's place of work and institution shapes the identity of individuals. Based on these interactions with their environment, individuals learn to improvise, revise and create new ways of deriving meaning from their experiences ( Fouad and Bynner, 2008 ). All forms of work result in individual experiences, both positive and negative. These experiences inform the way individuals behave, both consciously and subconsciously. Associated with learned behaviours influenced by work experiences, Smith (2017) notes that workers are, in essence, learners and that they learn through the activities that make up work.

Fouad and Bynner (2008 , p. 241) conclude that “work has a central place in adult life and in shaping individuals' identities.” Identity is defined as self-categorisation in the formation of one's identity, in which categorisation depends upon a named and classified world which includes terms learned within a culture ( Brenner and DeLamater, 2016 ; Stets and Burke, 2000 ). Cultures that shape personal identity include workplaces and institutional cultures ( Angouri, 2018 ) which have symbols used to designate positions in social structures and are described as roles ( Stets and Burke, 2000 ). Gini (2001 , pp. 2–3) agrees and states that “work is the yardstick by which we measure ourselves against others. It is the means by which we establish our rank, role, and function within a community.” This dynamic and effect of work on identity is not well captured within the context of work framed by employment, productivity and remuneration. Certainly with the significant shift towards remote and digitally enabled work, the associated effect on self-identity is of interest.

With the dynamic changes in work described earlier and its more subjective interpretation as suggested in emerging literature, it can be proposed that the cultural symbols that dominated identity formation in the past will have shifted and have become confounded. As an example, the physical determinations of workplaces, such as the executive corner office or one's position in a production line, are no longer as deterministic of identity as before. Similarly, increasingly different forms of work experienced by individuals in the 21st century suggest that new cultural “symbols” will inform identity formation. A broader frame of reference beyond workplaces and institutions is needed to sufficiently capture this shift.

Blustein (2013 , p. 2) alludes to these new places of work but still largely confines his definitions to workplaces as “the space shared by working and relationships is considerable, with each domain of life affecting the other, often in profound ways”. It is suggested that nature of these new “workspaces” have created new forms of relational interactions and identity formation. Figure 1 tentatively illustrates the notion of the world of work occurring within a space for thinking and doing beyond the confines of a workplace. The degree to which an individual's work takes place within a workplace is variable and may differ in proportion, but such places are often shared with others and as such lie partly or completely outside the individual's realm of thinking and doing.

Lefebvre (1996) outlines three dimensions of learning spaces: (1) the perceived space, (2) conceived space and (3) the lived space. Extending Lefebvre's argument more broadly, the same dimensions can be applied to where work takes place. The academic discourse still largely associates work with a geographical location and the physical environment as conceived by the parameters of employment but fails to capture the broader notion of spaces where work takes place as described by Lefebvre (1996) and Dourish (2006) . Work in the home, in the park, on the golf course, in the shower or in a coffee shop can be represented as a “perceived” and “lived” workspaces and thereby prompts reconfiguring how work is associated with workplaces.

8. A tentative new definition of work

Blustein (2013 , p. 4) suggests that “this shifting context will require different conceptual and practice tools … that are designed for a radically different work context that has framed most 20th century career development theories”. This paper presents the results of a scoping review aimed at providing a preliminary clarification of the dimensions and parameters of what may constitute a contemporary, multi-disciplinary definition of work.

In response to the scoping review question, Do current definitions of work capture the broad and rapidly changing nature of work in the 21st century? , the results of this review suggest that there have been calls for a more contemporary approach to studies of work reflecting the significant shifts that have been taken/are taking place. The literature notes that there are numerous instances of work that are not captured by mainstream definitions of work. From the preliminary review, the paper suggests that the dominant themes of employment, remuneration, workplace and career, among others, are “external” contexts of work and that these interact with the “internal” dimensions of work.

Work is innate. Work is an innate human function ( Dejours, 2002 ; Dik and Duffy, 2009 ) which inherently informs the individual's life purpose and role ( Ward and King, 2017 );

Work affects well - being. Work influences well-being ( Dejours, 2002 ; Deranty, 2009 ; Duffy and Dik, 2013 ; Duffy et al ., 2017 );

Work is relational. Work is relational ( Blustein, 2011 , 2013 ; Richardson, 1993 ) and is manifest through various socialisation processes ( Dejours, 2002 ; Deranty, 2009 ; Veltman, 2015 );

Work is identity. Work is driven by personal and societal codes of ethos and praxis ( Fergusson et al ., 2019 ), which in turn is manifest through one's expression of professional or vocational identity ( Savickas et al ., 2009 ; Ward and King, 2017 ) and/or social service ( Issa, 2014 ) and

Work is learning. Workers are learners, and they learn through the activities that make up work (Smith, 2017). Learning through work is a product of the subjective experience of the worker ( Dewey, 1938 ) as they derive meaning ( Fouad and Bynner, 2008 ) from the interactions within the contexts of work ( Rodgers, 2003 ).

Building on the analysis and argument extracted from the aforementioned literature, it is proposed that the definitional perspective suggested by this paper contributes to (1) justifying a delineation of the definition and study of work in order to addresses redundant assumptions associated with dominant paradigms in a vastly changed approach to and modality of work and (2) developing a more inclusive approach that is a more accurate description of work. To this end, a summary is proposed that may inform a new definition of work: Work is an innate human function which inherently informs the individual's life purpose and role; work is relational and is manifest through various socialisation processes comprising interactions with the contexts of work, deriving meaning from conscious thought and activity and/or efforts, and is driven by personal and societal codes of ethos and praxis which in turn is manifest in the expression of one's work and social service, while influencing one's well - being .

8.1 Conclusion

The dramatic changes to the nature, context and manifestations of work evident in this century show no signs of being linear or reducing in the rate of change. Rather, exponential and material changes in the way humans work are anticipated and require proactive research and design for future application. Failing this, emerging threats to the autonomy of individuals and humanity are possible.

We have argued that work can no longer be primarily defined in terms of place, employment, productivity or remuneration. Our scoping review of the literature establishes that previously dominant conceptualisations and lines of enquiry of work do not adequately capture the contemporary nature of work, its diversity of the forms it takes, and may be redundant in certain contexts. Instead, this review identified emerging dimensions of work, such as the innate nature of work, work and well-being, work as identity and learning as common underlying dimensions of work that interact with contexts of work.

Guided by the notion of thin and thick definitions of work, the paper provides insights into the convergent and divergent perspectives associated with how work is described in the extant literature. The literature suggests there needs to be better consensus on the definition of work and its meaning as these have far-reaching implications for future research and society more generally.

This study thus proposes that understanding work at the individual unit of analysis in terms of the dimensions of work and contexts of work is more meaningful than current, bounded disciplinary paradigms. This paper seeks to stimulate discourse and lead to more meaningful, future research, particularly across the areas of sociology, psychology, education, health and economics. The implications of the paper do not necessarily exclude helpful perspectives associated with the rational economics of work. Rather, it seeks to encapsulate a holistic perspective that may better understand and organise work in the future.

It is proposed that future research critically considers the summary definition proposed by the paper. The dimensions identified should also be tested in order to develop greater consensus on a contemporary definition. Further, it is suggested that new lines of enquiry emerge that include comprehensive reviews, qualitative and quantitative studies that seek to confirm, develop and elaborate on the taxonomy of work and its underlying dimensions suggested by the paper. It is noted that the paper is a preliminary investigation of the literature aimed to inform future research by proposing a taxonomy of work and tentative definition.

the meaning of research work

The interface of individual and work occurring within a workplace and more generally within a space for thinking and doing

the meaning of research work

Illustration of the interaction between “contexts of work” and “dimensions of work”

Thin or thick definitions to explain the world of work

Thin definitionThick definition
Foundation established on neoliberal economic theorySubjective investment in work (self-motivation)
Money is key to personal motivationMobilisation of individual capabilities
Given the opportunity, humans would opt out of workingPersonal interpretation of work and adaptation to the context of work
Transactional interactions associated with workSociality and sociability (relational) interactions of work
Adapted from

Author and dateInnate functionUbiquitousMeaningfulnessWell-beingA callingWorkplaceEmployment/jobRemunerationCareer/professionRelationalService
X XX
XXX
XXX
XX
X X X X
XX X
X X X
X X
X X
X
X XX X
XXXXXXXXX
X XX
X X
X X
. (2016) XX X
. (2017) XX
. (2019) X X
X X X
4754210154352

Source(s): Authors' own work

Funding : This research did not receive any specific grant from funding agencies in the public, commercial or not-for-profit sectors.

Disclosure statement: There is no conflict of interest.

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What Is Research, and Why Do People Do It?

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  • First Online: 03 December 2022

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the meaning of research work

  • James Hiebert 6 ,
  • Jinfa Cai 7 ,
  • Stephen Hwang 7 ,
  • Anne K Morris 6 &
  • Charles Hohensee 6  

Part of the book series: Research in Mathematics Education ((RME))

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Abstractspiepr Abs1

Every day people do research as they gather information to learn about something of interest. In the scientific world, however, research means something different than simply gathering information. Scientific research is characterized by its careful planning and observing, by its relentless efforts to understand and explain, and by its commitment to learn from everyone else seriously engaged in research. We call this kind of research scientific inquiry and define it as “formulating, testing, and revising hypotheses.” By “hypotheses” we do not mean the hypotheses you encounter in statistics courses. We mean predictions about what you expect to find and rationales for why you made these predictions. Throughout this and the remaining chapters we make clear that the process of scientific inquiry applies to all kinds of research studies and data, both qualitative and quantitative.

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Part I. What Is Research?

Have you ever studied something carefully because you wanted to know more about it? Maybe you wanted to know more about your grandmother’s life when she was younger so you asked her to tell you stories from her childhood, or maybe you wanted to know more about a fertilizer you were about to use in your garden so you read the ingredients on the package and looked them up online. According to the dictionary definition, you were doing research.

Recall your high school assignments asking you to “research” a topic. The assignment likely included consulting a variety of sources that discussed the topic, perhaps including some “original” sources. Often, the teacher referred to your product as a “research paper.”

Were you conducting research when you interviewed your grandmother or wrote high school papers reviewing a particular topic? Our view is that you were engaged in part of the research process, but only a small part. In this book, we reserve the word “research” for what it means in the scientific world, that is, for scientific research or, more pointedly, for scientific inquiry .

Exercise 1.1

Before you read any further, write a definition of what you think scientific inquiry is. Keep it short—Two to three sentences. You will periodically update this definition as you read this chapter and the remainder of the book.

This book is about scientific inquiry—what it is and how to do it. For starters, scientific inquiry is a process, a particular way of finding out about something that involves a number of phases. Each phase of the process constitutes one aspect of scientific inquiry. You are doing scientific inquiry as you engage in each phase, but you have not done scientific inquiry until you complete the full process. Each phase is necessary but not sufficient.

In this chapter, we set the stage by defining scientific inquiry—describing what it is and what it is not—and by discussing what it is good for and why people do it. The remaining chapters build directly on the ideas presented in this chapter.

A first thing to know is that scientific inquiry is not all or nothing. “Scientificness” is a continuum. Inquiries can be more scientific or less scientific. What makes an inquiry more scientific? You might be surprised there is no universally agreed upon answer to this question. None of the descriptors we know of are sufficient by themselves to define scientific inquiry. But all of them give you a way of thinking about some aspects of the process of scientific inquiry. Each one gives you different insights.

An image of the book's description with the words like research, science, and inquiry and what the word research meant in the scientific world.

Exercise 1.2

As you read about each descriptor below, think about what would make an inquiry more or less scientific. If you think a descriptor is important, use it to revise your definition of scientific inquiry.

Creating an Image of Scientific Inquiry

We will present three descriptors of scientific inquiry. Each provides a different perspective and emphasizes a different aspect of scientific inquiry. We will draw on all three descriptors to compose our definition of scientific inquiry.

Descriptor 1. Experience Carefully Planned in Advance

Sir Ronald Fisher, often called the father of modern statistical design, once referred to research as “experience carefully planned in advance” (1935, p. 8). He said that humans are always learning from experience, from interacting with the world around them. Usually, this learning is haphazard rather than the result of a deliberate process carried out over an extended period of time. Research, Fisher said, was learning from experience, but experience carefully planned in advance.

This phrase can be fully appreciated by looking at each word. The fact that scientific inquiry is based on experience means that it is based on interacting with the world. These interactions could be thought of as the stuff of scientific inquiry. In addition, it is not just any experience that counts. The experience must be carefully planned . The interactions with the world must be conducted with an explicit, describable purpose, and steps must be taken to make the intended learning as likely as possible. This planning is an integral part of scientific inquiry; it is not just a preparation phase. It is one of the things that distinguishes scientific inquiry from many everyday learning experiences. Finally, these steps must be taken beforehand and the purpose of the inquiry must be articulated in advance of the experience. Clearly, scientific inquiry does not happen by accident, by just stumbling into something. Stumbling into something unexpected and interesting can happen while engaged in scientific inquiry, but learning does not depend on it and serendipity does not make the inquiry scientific.

Descriptor 2. Observing Something and Trying to Explain Why It Is the Way It Is

When we were writing this chapter and googled “scientific inquiry,” the first entry was: “Scientific inquiry refers to the diverse ways in which scientists study the natural world and propose explanations based on the evidence derived from their work.” The emphasis is on studying, or observing, and then explaining . This descriptor takes the image of scientific inquiry beyond carefully planned experience and includes explaining what was experienced.

According to the Merriam-Webster dictionary, “explain” means “(a) to make known, (b) to make plain or understandable, (c) to give the reason or cause of, and (d) to show the logical development or relations of” (Merriam-Webster, n.d. ). We will use all these definitions. Taken together, they suggest that to explain an observation means to understand it by finding reasons (or causes) for why it is as it is. In this sense of scientific inquiry, the following are synonyms: explaining why, understanding why, and reasoning about causes and effects. Our image of scientific inquiry now includes planning, observing, and explaining why.

An image represents the observation required in the scientific inquiry including planning and explaining.

We need to add a final note about this descriptor. We have phrased it in a way that suggests “observing something” means you are observing something in real time—observing the way things are or the way things are changing. This is often true. But, observing could mean observing data that already have been collected, maybe by someone else making the original observations (e.g., secondary analysis of NAEP data or analysis of existing video recordings of classroom instruction). We will address secondary analyses more fully in Chap. 4 . For now, what is important is that the process requires explaining why the data look like they do.

We must note that for us, the term “data” is not limited to numerical or quantitative data such as test scores. Data can also take many nonquantitative forms, including written survey responses, interview transcripts, journal entries, video recordings of students, teachers, and classrooms, text messages, and so forth.

An image represents the data explanation as it is not limited and takes numerous non-quantitative forms including an interview, journal entries, etc.

Exercise 1.3

What are the implications of the statement that just “observing” is not enough to count as scientific inquiry? Does this mean that a detailed description of a phenomenon is not scientific inquiry?

Find sources that define research in education that differ with our position, that say description alone, without explanation, counts as scientific research. Identify the precise points where the opinions differ. What are the best arguments for each of the positions? Which do you prefer? Why?

Descriptor 3. Updating Everyone’s Thinking in Response to More and Better Information

This descriptor focuses on a third aspect of scientific inquiry: updating and advancing the field’s understanding of phenomena that are investigated. This descriptor foregrounds a powerful characteristic of scientific inquiry: the reliability (or trustworthiness) of what is learned and the ultimate inevitability of this learning to advance human understanding of phenomena. Humans might choose not to learn from scientific inquiry, but history suggests that scientific inquiry always has the potential to advance understanding and that, eventually, humans take advantage of these new understandings.

Before exploring these bold claims a bit further, note that this descriptor uses “information” in the same way the previous two descriptors used “experience” and “observations.” These are the stuff of scientific inquiry and we will use them often, sometimes interchangeably. Frequently, we will use the term “data” to stand for all these terms.

An overriding goal of scientific inquiry is for everyone to learn from what one scientist does. Much of this book is about the methods you need to use so others have faith in what you report and can learn the same things you learned. This aspect of scientific inquiry has many implications.

One implication is that scientific inquiry is not a private practice. It is a public practice available for others to see and learn from. Notice how different this is from everyday learning. When you happen to learn something from your everyday experience, often only you gain from the experience. The fact that research is a public practice means it is also a social one. It is best conducted by interacting with others along the way: soliciting feedback at each phase, taking opportunities to present work-in-progress, and benefitting from the advice of others.

A second implication is that you, as the researcher, must be committed to sharing what you are doing and what you are learning in an open and transparent way. This allows all phases of your work to be scrutinized and critiqued. This is what gives your work credibility. The reliability or trustworthiness of your findings depends on your colleagues recognizing that you have used all appropriate methods to maximize the chances that your claims are justified by the data.

A third implication of viewing scientific inquiry as a collective enterprise is the reverse of the second—you must be committed to receiving comments from others. You must treat your colleagues as fair and honest critics even though it might sometimes feel otherwise. You must appreciate their job, which is to remain skeptical while scrutinizing what you have done in considerable detail. To provide the best help to you, they must remain skeptical about your conclusions (when, for example, the data are difficult for them to interpret) until you offer a convincing logical argument based on the information you share. A rather harsh but good-to-remember statement of the role of your friendly critics was voiced by Karl Popper, a well-known twentieth century philosopher of science: “. . . if you are interested in the problem which I tried to solve by my tentative assertion, you may help me by criticizing it as severely as you can” (Popper, 1968, p. 27).

A final implication of this third descriptor is that, as someone engaged in scientific inquiry, you have no choice but to update your thinking when the data support a different conclusion. This applies to your own data as well as to those of others. When data clearly point to a specific claim, even one that is quite different than you expected, you must reconsider your position. If the outcome is replicated multiple times, you need to adjust your thinking accordingly. Scientific inquiry does not let you pick and choose which data to believe; it mandates that everyone update their thinking when the data warrant an update.

Doing Scientific Inquiry

We define scientific inquiry in an operational sense—what does it mean to do scientific inquiry? What kind of process would satisfy all three descriptors: carefully planning an experience in advance; observing and trying to explain what you see; and, contributing to updating everyone’s thinking about an important phenomenon?

We define scientific inquiry as formulating , testing , and revising hypotheses about phenomena of interest.

Of course, we are not the only ones who define it in this way. The definition for the scientific method posted by the editors of Britannica is: “a researcher develops a hypothesis, tests it through various means, and then modifies the hypothesis on the basis of the outcome of the tests and experiments” (Britannica, n.d. ).

An image represents the scientific inquiry definition given by the editors of Britannica and also defines the hypothesis on the basis of the experiments.

Notice how defining scientific inquiry this way satisfies each of the descriptors. “Carefully planning an experience in advance” is exactly what happens when formulating a hypothesis about a phenomenon of interest and thinking about how to test it. “ Observing a phenomenon” occurs when testing a hypothesis, and “ explaining ” what is found is required when revising a hypothesis based on the data. Finally, “updating everyone’s thinking” comes from comparing publicly the original with the revised hypothesis.

Doing scientific inquiry, as we have defined it, underscores the value of accumulating knowledge rather than generating random bits of knowledge. Formulating, testing, and revising hypotheses is an ongoing process, with each revised hypothesis begging for another test, whether by the same researcher or by new researchers. The editors of Britannica signaled this cyclic process by adding the following phrase to their definition of the scientific method: “The modified hypothesis is then retested, further modified, and tested again.” Scientific inquiry creates a process that encourages each study to build on the studies that have gone before. Through collective engagement in this process of building study on top of study, the scientific community works together to update its thinking.

Before exploring more fully the meaning of “formulating, testing, and revising hypotheses,” we need to acknowledge that this is not the only way researchers define research. Some researchers prefer a less formal definition, one that includes more serendipity, less planning, less explanation. You might have come across more open definitions such as “research is finding out about something.” We prefer the tighter hypothesis formulation, testing, and revision definition because we believe it provides a single, coherent map for conducting research that addresses many of the thorny problems educational researchers encounter. We believe it is the most useful orientation toward research and the most helpful to learn as a beginning researcher.

A final clarification of our definition is that it applies equally to qualitative and quantitative research. This is a familiar distinction in education that has generated much discussion. You might think our definition favors quantitative methods over qualitative methods because the language of hypothesis formulation and testing is often associated with quantitative methods. In fact, we do not favor one method over another. In Chap. 4 , we will illustrate how our definition fits research using a range of quantitative and qualitative methods.

Exercise 1.4

Look for ways to extend what the field knows in an area that has already received attention by other researchers. Specifically, you can search for a program of research carried out by more experienced researchers that has some revised hypotheses that remain untested. Identify a revised hypothesis that you might like to test.

Unpacking the Terms Formulating, Testing, and Revising Hypotheses

To get a full sense of the definition of scientific inquiry we will use throughout this book, it is helpful to spend a little time with each of the key terms.

We first want to make clear that we use the term “hypothesis” as it is defined in most dictionaries and as it used in many scientific fields rather than as it is usually defined in educational statistics courses. By “hypothesis,” we do not mean a null hypothesis that is accepted or rejected by statistical analysis. Rather, we use “hypothesis” in the sense conveyed by the following definitions: “An idea or explanation for something that is based on known facts but has not yet been proved” (Cambridge University Press, n.d. ), and “An unproved theory, proposition, or supposition, tentatively accepted to explain certain facts and to provide a basis for further investigation or argument” (Agnes & Guralnik, 2008 ).

We distinguish two parts to “hypotheses.” Hypotheses consist of predictions and rationales . Predictions are statements about what you expect to find when you inquire about something. Rationales are explanations for why you made the predictions you did, why you believe your predictions are correct. So, for us “formulating hypotheses” means making explicit predictions and developing rationales for the predictions.

“Testing hypotheses” means making observations that allow you to assess in what ways your predictions were correct and in what ways they were incorrect. In education research, it is rarely useful to think of your predictions as either right or wrong. Because of the complexity of most issues you will investigate, most predictions will be right in some ways and wrong in others.

By studying the observations you make (data you collect) to test your hypotheses, you can revise your hypotheses to better align with the observations. This means revising your predictions plus revising your rationales to justify your adjusted predictions. Even though you might not run another test, formulating revised hypotheses is an essential part of conducting a research study. Comparing your original and revised hypotheses informs everyone of what you learned by conducting your study. In addition, a revised hypothesis sets the stage for you or someone else to extend your study and accumulate more knowledge of the phenomenon.

We should note that not everyone makes a clear distinction between predictions and rationales as two aspects of hypotheses. In fact, common, non-scientific uses of the word “hypothesis” may limit it to only a prediction or only an explanation (or rationale). We choose to explicitly include both prediction and rationale in our definition of hypothesis, not because we assert this should be the universal definition, but because we want to foreground the importance of both parts acting in concert. Using “hypothesis” to represent both prediction and rationale could hide the two aspects, but we make them explicit because they provide different kinds of information. It is usually easier to make predictions than develop rationales because predictions can be guesses, hunches, or gut feelings about which you have little confidence. Developing a compelling rationale requires careful thought plus reading what other researchers have found plus talking with your colleagues. Often, while you are developing your rationale you will find good reasons to change your predictions. Developing good rationales is the engine that drives scientific inquiry. Rationales are essentially descriptions of how much you know about the phenomenon you are studying. Throughout this guide, we will elaborate on how developing good rationales drives scientific inquiry. For now, we simply note that it can sharpen your predictions and help you to interpret your data as you test your hypotheses.

An image represents the rationale and the prediction for the scientific inquiry and different types of information provided by the terms.

Hypotheses in education research take a variety of forms or types. This is because there are a variety of phenomena that can be investigated. Investigating educational phenomena is sometimes best done using qualitative methods, sometimes using quantitative methods, and most often using mixed methods (e.g., Hay, 2016 ; Weis et al. 2019a ; Weisner, 2005 ). This means that, given our definition, hypotheses are equally applicable to qualitative and quantitative investigations.

Hypotheses take different forms when they are used to investigate different kinds of phenomena. Two very different activities in education could be labeled conducting experiments and descriptions. In an experiment, a hypothesis makes a prediction about anticipated changes, say the changes that occur when a treatment or intervention is applied. You might investigate how students’ thinking changes during a particular kind of instruction.

A second type of hypothesis, relevant for descriptive research, makes a prediction about what you will find when you investigate and describe the nature of a situation. The goal is to understand a situation as it exists rather than to understand a change from one situation to another. In this case, your prediction is what you expect to observe. Your rationale is the set of reasons for making this prediction; it is your current explanation for why the situation will look like it does.

You will probably read, if you have not already, that some researchers say you do not need a prediction to conduct a descriptive study. We will discuss this point of view in Chap. 2 . For now, we simply claim that scientific inquiry, as we have defined it, applies to all kinds of research studies. Descriptive studies, like others, not only benefit from formulating, testing, and revising hypotheses, but also need hypothesis formulating, testing, and revising.

One reason we define research as formulating, testing, and revising hypotheses is that if you think of research in this way you are less likely to go wrong. It is a useful guide for the entire process, as we will describe in detail in the chapters ahead. For example, as you build the rationale for your predictions, you are constructing the theoretical framework for your study (Chap. 3 ). As you work out the methods you will use to test your hypothesis, every decision you make will be based on asking, “Will this help me formulate or test or revise my hypothesis?” (Chap. 4 ). As you interpret the results of testing your predictions, you will compare them to what you predicted and examine the differences, focusing on how you must revise your hypotheses (Chap. 5 ). By anchoring the process to formulating, testing, and revising hypotheses, you will make smart decisions that yield a coherent and well-designed study.

Exercise 1.5

Compare the concept of formulating, testing, and revising hypotheses with the descriptions of scientific inquiry contained in Scientific Research in Education (NRC, 2002 ). How are they similar or different?

Exercise 1.6

Provide an example to illustrate and emphasize the differences between everyday learning/thinking and scientific inquiry.

Learning from Doing Scientific Inquiry

We noted earlier that a measure of what you have learned by conducting a research study is found in the differences between your original hypothesis and your revised hypothesis based on the data you collected to test your hypothesis. We will elaborate this statement in later chapters, but we preview our argument here.

Even before collecting data, scientific inquiry requires cycles of making a prediction, developing a rationale, refining your predictions, reading and studying more to strengthen your rationale, refining your predictions again, and so forth. And, even if you have run through several such cycles, you still will likely find that when you test your prediction you will be partly right and partly wrong. The results will support some parts of your predictions but not others, or the results will “kind of” support your predictions. A critical part of scientific inquiry is making sense of your results by interpreting them against your predictions. Carefully describing what aspects of your data supported your predictions, what aspects did not, and what data fell outside of any predictions is not an easy task, but you cannot learn from your study without doing this analysis.

An image represents the cycle of events that take place before making predictions, developing the rationale, and studying the prediction and rationale multiple times.

Analyzing the matches and mismatches between your predictions and your data allows you to formulate different rationales that would have accounted for more of the data. The best revised rationale is the one that accounts for the most data. Once you have revised your rationales, you can think about the predictions they best justify or explain. It is by comparing your original rationales to your new rationales that you can sort out what you learned from your study.

Suppose your study was an experiment. Maybe you were investigating the effects of a new instructional intervention on students’ learning. Your original rationale was your explanation for why the intervention would change the learning outcomes in a particular way. Your revised rationale explained why the changes that you observed occurred like they did and why your revised predictions are better. Maybe your original rationale focused on the potential of the activities if they were implemented in ideal ways and your revised rationale included the factors that are likely to affect how teachers implement them. By comparing the before and after rationales, you are describing what you learned—what you can explain now that you could not before. Another way of saying this is that you are describing how much more you understand now than before you conducted your study.

Revised predictions based on carefully planned and collected data usually exhibit some of the following features compared with the originals: more precision, more completeness, and broader scope. Revised rationales have more explanatory power and become more complete, more aligned with the new predictions, sharper, and overall more convincing.

Part II. Why Do Educators Do Research?

Doing scientific inquiry is a lot of work. Each phase of the process takes time, and you will often cycle back to improve earlier phases as you engage in later phases. Because of the significant effort required, you should make sure your study is worth it. So, from the beginning, you should think about the purpose of your study. Why do you want to do it? And, because research is a social practice, you should also think about whether the results of your study are likely to be important and significant to the education community.

If you are doing research in the way we have described—as scientific inquiry—then one purpose of your study is to understand , not just to describe or evaluate or report. As we noted earlier, when you formulate hypotheses, you are developing rationales that explain why things might be like they are. In our view, trying to understand and explain is what separates research from other kinds of activities, like evaluating or describing.

One reason understanding is so important is that it allows researchers to see how or why something works like it does. When you see how something works, you are better able to predict how it might work in other contexts, under other conditions. And, because conditions, or contextual factors, matter a lot in education, gaining insights into applying your findings to other contexts increases the contributions of your work and its importance to the broader education community.

Consequently, the purposes of research studies in education often include the more specific aim of identifying and understanding the conditions under which the phenomena being studied work like the observations suggest. A classic example of this kind of study in mathematics education was reported by William Brownell and Harold Moser in 1949 . They were trying to establish which method of subtracting whole numbers could be taught most effectively—the regrouping method or the equal additions method. However, they realized that effectiveness might depend on the conditions under which the methods were taught—“meaningfully” versus “mechanically.” So, they designed a study that crossed the two instructional approaches with the two different methods (regrouping and equal additions). Among other results, they found that these conditions did matter. The regrouping method was more effective under the meaningful condition than the mechanical condition, but the same was not true for the equal additions algorithm.

What do education researchers want to understand? In our view, the ultimate goal of education is to offer all students the best possible learning opportunities. So, we believe the ultimate purpose of scientific inquiry in education is to develop understanding that supports the improvement of learning opportunities for all students. We say “ultimate” because there are lots of issues that must be understood to improve learning opportunities for all students. Hypotheses about many aspects of education are connected, ultimately, to students’ learning. For example, formulating and testing a hypothesis that preservice teachers need to engage in particular kinds of activities in their coursework in order to teach particular topics well is, ultimately, connected to improving students’ learning opportunities. So is hypothesizing that school districts often devote relatively few resources to instructional leadership training or hypothesizing that positioning mathematics as a tool students can use to combat social injustice can help students see the relevance of mathematics to their lives.

We do not exclude the importance of research on educational issues more removed from improving students’ learning opportunities, but we do think the argument for their importance will be more difficult to make. If there is no way to imagine a connection between your hypothesis and improving learning opportunities for students, even a distant connection, we recommend you reconsider whether it is an important hypothesis within the education community.

Notice that we said the ultimate goal of education is to offer all students the best possible learning opportunities. For too long, educators have been satisfied with a goal of offering rich learning opportunities for lots of students, sometimes even for just the majority of students, but not necessarily for all students. Evaluations of success often are based on outcomes that show high averages. In other words, if many students have learned something, or even a smaller number have learned a lot, educators may have been satisfied. The problem is that there is usually a pattern in the groups of students who receive lower quality opportunities—students of color and students who live in poor areas, urban and rural. This is not acceptable. Consequently, we emphasize the premise that the purpose of education research is to offer rich learning opportunities to all students.

One way to make sure you will be able to convince others of the importance of your study is to consider investigating some aspect of teachers’ shared instructional problems. Historically, researchers in education have set their own research agendas, regardless of the problems teachers are facing in schools. It is increasingly recognized that teachers have had trouble applying to their own classrooms what researchers find. To address this problem, a researcher could partner with a teacher—better yet, a small group of teachers—and talk with them about instructional problems they all share. These discussions can create a rich pool of problems researchers can consider. If researchers pursued one of these problems (preferably alongside teachers), the connection to improving learning opportunities for all students could be direct and immediate. “Grounding a research question in instructional problems that are experienced across multiple teachers’ classrooms helps to ensure that the answer to the question will be of sufficient scope to be relevant and significant beyond the local context” (Cai et al., 2019b , p. 115).

As a beginning researcher, determining the relevance and importance of a research problem is especially challenging. We recommend talking with advisors, other experienced researchers, and peers to test the educational importance of possible research problems and topics of study. You will also learn much more about the issue of research importance when you read Chap. 5 .

Exercise 1.7

Identify a problem in education that is closely connected to improving learning opportunities and a problem that has a less close connection. For each problem, write a brief argument (like a logical sequence of if-then statements) that connects the problem to all students’ learning opportunities.

Part III. Conducting Research as a Practice of Failing Productively

Scientific inquiry involves formulating hypotheses about phenomena that are not fully understood—by you or anyone else. Even if you are able to inform your hypotheses with lots of knowledge that has already been accumulated, you are likely to find that your prediction is not entirely accurate. This is normal. Remember, scientific inquiry is a process of constantly updating your thinking. More and better information means revising your thinking, again, and again, and again. Because you never fully understand a complicated phenomenon and your hypotheses never produce completely accurate predictions, it is easy to believe you are somehow failing.

The trick is to fail upward, to fail to predict accurately in ways that inform your next hypothesis so you can make a better prediction. Some of the best-known researchers in education have been open and honest about the many times their predictions were wrong and, based on the results of their studies and those of others, they continuously updated their thinking and changed their hypotheses.

A striking example of publicly revising (actually reversing) hypotheses due to incorrect predictions is found in the work of Lee J. Cronbach, one of the most distinguished educational psychologists of the twentieth century. In 1955, Cronbach delivered his presidential address to the American Psychological Association. Titling it “Two Disciplines of Scientific Psychology,” Cronbach proposed a rapprochement between two research approaches—correlational studies that focused on individual differences and experimental studies that focused on instructional treatments controlling for individual differences. (We will examine different research approaches in Chap. 4 ). If these approaches could be brought together, reasoned Cronbach ( 1957 ), researchers could find interactions between individual characteristics and treatments (aptitude-treatment interactions or ATIs), fitting the best treatments to different individuals.

In 1975, after years of research by many researchers looking for ATIs, Cronbach acknowledged the evidence for simple, useful ATIs had not been found. Even when trying to find interactions between a few variables that could provide instructional guidance, the analysis, said Cronbach, creates “a hall of mirrors that extends to infinity, tormenting even the boldest investigators and defeating even ambitious designs” (Cronbach, 1975 , p. 119).

As he was reflecting back on his work, Cronbach ( 1986 ) recommended moving away from documenting instructional effects through statistical inference (an approach he had championed for much of his career) and toward approaches that probe the reasons for these effects, approaches that provide a “full account of events in a time, place, and context” (Cronbach, 1986 , p. 104). This is a remarkable change in hypotheses, a change based on data and made fully transparent. Cronbach understood the value of failing productively.

Closer to home, in a less dramatic example, one of us began a line of scientific inquiry into how to prepare elementary preservice teachers to teach early algebra. Teaching early algebra meant engaging elementary students in early forms of algebraic reasoning. Such reasoning should help them transition from arithmetic to algebra. To begin this line of inquiry, a set of activities for preservice teachers were developed. Even though the activities were based on well-supported hypotheses, they largely failed to engage preservice teachers as predicted because of unanticipated challenges the preservice teachers faced. To capitalize on this failure, follow-up studies were conducted, first to better understand elementary preservice teachers’ challenges with preparing to teach early algebra, and then to better support preservice teachers in navigating these challenges. In this example, the initial failure was a necessary step in the researchers’ scientific inquiry and furthered the researchers’ understanding of this issue.

We present another example of failing productively in Chap. 2 . That example emerges from recounting the history of a well-known research program in mathematics education.

Making mistakes is an inherent part of doing scientific research. Conducting a study is rarely a smooth path from beginning to end. We recommend that you keep the following things in mind as you begin a career of conducting research in education.

First, do not get discouraged when you make mistakes; do not fall into the trap of feeling like you are not capable of doing research because you make too many errors.

Second, learn from your mistakes. Do not ignore your mistakes or treat them as errors that you simply need to forget and move past. Mistakes are rich sites for learning—in research just as in other fields of study.

Third, by reflecting on your mistakes, you can learn to make better mistakes, mistakes that inform you about a productive next step. You will not be able to eliminate your mistakes, but you can set a goal of making better and better mistakes.

Exercise 1.8

How does scientific inquiry differ from everyday learning in giving you the tools to fail upward? You may find helpful perspectives on this question in other resources on science and scientific inquiry (e.g., Failure: Why Science is So Successful by Firestein, 2015).

Exercise 1.9

Use what you have learned in this chapter to write a new definition of scientific inquiry. Compare this definition with the one you wrote before reading this chapter. If you are reading this book as part of a course, compare your definition with your colleagues’ definitions. Develop a consensus definition with everyone in the course.

Part IV. Preview of Chap. 2

Now that you have a good idea of what research is, at least of what we believe research is, the next step is to think about how to actually begin doing research. This means how to begin formulating, testing, and revising hypotheses. As for all phases of scientific inquiry, there are lots of things to think about. Because it is critical to start well, we devote Chap. 2 to getting started with formulating hypotheses.

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Hiebert, J., Cai, J., Hwang, S., Morris, A.K., Hohensee, C. (2023). What Is Research, and Why Do People Do It?. In: Doing Research: A New Researcher’s Guide. Research in Mathematics Education. Springer, Cham. https://doi.org/10.1007/978-3-031-19078-0_1

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the meaning of research work

Home Market Research

What is Research: Definition, Methods, Types & Examples

What is Research

The search for knowledge is closely linked to the object of study; that is, to the reconstruction of the facts that will provide an explanation to an observed event and that at first sight can be considered as a problem. It is very human to seek answers and satisfy our curiosity. Let’s talk about research.

Content Index

What is Research?

What are the characteristics of research.

  • Comparative analysis chart

Qualitative methods

Quantitative methods, 8 tips for conducting accurate research.

Research is the careful consideration of study regarding a particular concern or research problem using scientific methods. According to the American sociologist Earl Robert Babbie, “research is a systematic inquiry to describe, explain, predict, and control the observed phenomenon. It involves inductive and deductive methods.”

Inductive methods analyze an observed event, while deductive methods verify the observed event. Inductive approaches are associated with qualitative research , and deductive methods are more commonly associated with quantitative analysis .

Research is conducted with a purpose to:

  • Identify potential and new customers
  • Understand existing customers
  • Set pragmatic goals
  • Develop productive market strategies
  • Address business challenges
  • Put together a business expansion plan
  • Identify new business opportunities
  • Good research follows a systematic approach to capture accurate data. Researchers need to practice ethics and a code of conduct while making observations or drawing conclusions.
  • The analysis is based on logical reasoning and involves both inductive and deductive methods.
  • Real-time data and knowledge is derived from actual observations in natural settings.
  • There is an in-depth analysis of all data collected so that there are no anomalies associated with it.
  • It creates a path for generating new questions. Existing data helps create more research opportunities.
  • It is analytical and uses all the available data so that there is no ambiguity in inference.
  • Accuracy is one of the most critical aspects of research. The information must be accurate and correct. For example, laboratories provide a controlled environment to collect data. Accuracy is measured in the instruments used, the calibrations of instruments or tools, and the experiment’s final result.

What is the purpose of research?

There are three main purposes:

  • Exploratory: As the name suggests, researchers conduct exploratory studies to explore a group of questions. The answers and analytics may not offer a conclusion to the perceived problem. It is undertaken to handle new problem areas that haven’t been explored before. This exploratory data analysis process lays the foundation for more conclusive data collection and analysis.

LEARN ABOUT: Descriptive Analysis

  • Descriptive: It focuses on expanding knowledge on current issues through a process of data collection. Descriptive research describe the behavior of a sample population. Only one variable is required to conduct the study. The three primary purposes of descriptive studies are describing, explaining, and validating the findings. For example, a study conducted to know if top-level management leaders in the 21st century possess the moral right to receive a considerable sum of money from the company profit.

LEARN ABOUT: Best Data Collection Tools

  • Explanatory: Causal research or explanatory research is conducted to understand the impact of specific changes in existing standard procedures. Running experiments is the most popular form. For example, a study that is conducted to understand the effect of rebranding on customer loyalty.

Here is a comparative analysis chart for a better understanding:

 
Approach used Unstructured Structured Highly structured
Conducted throughAsking questions Asking questions By using hypotheses.
TimeEarly stages of decision making Later stages of decision makingLater stages of decision making

It begins by asking the right questions and choosing an appropriate method to investigate the problem. After collecting answers to your questions, you can analyze the findings or observations to draw reasonable conclusions.

When it comes to customers and market studies, the more thorough your questions, the better the analysis. You get essential insights into brand perception and product needs by thoroughly collecting customer data through surveys and questionnaires . You can use this data to make smart decisions about your marketing strategies to position your business effectively.

To make sense of your study and get insights faster, it helps to use a research repository as a single source of truth in your organization and manage your research data in one centralized data repository .

Types of research methods and Examples

what is research

Research methods are broadly classified as Qualitative and Quantitative .

Both methods have distinctive properties and data collection methods .

Qualitative research is a method that collects data using conversational methods, usually open-ended questions . The responses collected are essentially non-numerical. This method helps a researcher understand what participants think and why they think in a particular way.

Types of qualitative methods include:

  • One-to-one Interview
  • Focus Groups
  • Ethnographic studies
  • Text Analysis

Quantitative methods deal with numbers and measurable forms . It uses a systematic way of investigating events or data. It answers questions to justify relationships with measurable variables to either explain, predict, or control a phenomenon.

Types of quantitative methods include:

  • Survey research
  • Descriptive research
  • Correlational research

LEARN MORE: Descriptive Research vs Correlational Research

Remember, it is only valuable and useful when it is valid, accurate, and reliable. Incorrect results can lead to customer churn and a decrease in sales.

It is essential to ensure that your data is:

  • Valid – founded, logical, rigorous, and impartial.
  • Accurate – free of errors and including required details.
  • Reliable – other people who investigate in the same way can produce similar results.
  • Timely – current and collected within an appropriate time frame.
  • Complete – includes all the data you need to support your business decisions.

Gather insights

What is a research - tips

  • Identify the main trends and issues, opportunities, and problems you observe. Write a sentence describing each one.
  • Keep track of the frequency with which each of the main findings appears.
  • Make a list of your findings from the most common to the least common.
  • Evaluate a list of the strengths, weaknesses, opportunities, and threats identified in a SWOT analysis .
  • Prepare conclusions and recommendations about your study.
  • Act on your strategies
  • Look for gaps in the information, and consider doing additional inquiry if necessary
  • Plan to review the results and consider efficient methods to analyze and interpret results.

Review your goals before making any conclusions about your study. Remember how the process you have completed and the data you have gathered help answer your questions. Ask yourself if what your analysis revealed facilitates the identification of your conclusions and recommendations.

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What Makes Work Meaningful?

  • Evgenia I. Lysova,
  • Luke Fletcher,
  • Sabrine El Baroudi

the meaning of research work

Research shows that being more aware of yourself and your surroundings is key.

How do you make your work more meaningful? Prior studies have focused on understanding the factors that contribute to making work meaningful overall, such as having more autonomy or being able to job craft. But these are individual actions that don’t easily translate into how we experience meaningfulness every day. It can also be difficult for early career professionals as you can’t just decide to drop every uninspiring task from your to-do list in an attempt to experience more meaning in your role.

  • Research shows that being in a state of awareness can help. In a state of awareness (of yourself and your wider work environment), people are more willing and able to be creative in how they think and deal with challenges and other work-related problems. Awareness also helps you come up with better solutions, interpret signals from others around you, and adapt to changing circumstances. This, in turn, can facilitate a sense of meaning because it enables you to think and behave in ways that help you see the value, worth, and impact within everyday work tasks and interactions.
  • To become more aware, start by practicing mindfulness. Mindfulness helps us learn to recognize and acknowledge what’s going on in the mind, moment by moment, increases awareness, and decreases rumination. It also promotes cognitive flexibility, all of which lead to greater meaning-making.
  • Journaling is a great way to build awareness into your everyday work life. Before you end the day, ask yourself, “What did I find meaningful today,” and write it down. You can do this not only for yourself but also for your colleagues. Consider weaving awareness into group discussions and conversations at work.
  • Investing more in one’s relationships is important to feel happy and fulfilled at work, as our findings suggest. As an individual, you can respectfully engage with others at work through active listening and showing appreciation. These behaviors could then also enable greater psychological safety in the work environment as they help promote a sense of belonging at work that prior research shows is critical for meaningfulness

We all search for meaning in our lives, and many of us find it through our work . In fact, research shows that meaningfulness is more important to us than any other aspect of our jobs — including pay and rewards, opportunities for promotion, and working conditions. When we experience our work as meaningful, we’re more engaged, committed, and satisfied. When we don’t, we’re more willing to quit , and this is especially true for younger workers .

the meaning of research work

  • Evgenia I. Lysova an Associate Professor in Organizational Behavior at the Management and Organization department of Vrije Universiteit Amsterdam, the Netherlands. Her main research interests concern the topic of meaningful work, work as a calling, careers, and Corporate Social Responsibility. She is on a mission to enable and sustain greater experiences of meaningfulness in individuals’ work and careers with the help of organizations.
  • LF Luke Fletcher is an Associate Professor in Human Resource Management at the University of Bath’s School of Management, UK. His research interests span both organizational psychology and strategic human resource management, and include topics such as meaningful work, employee engagement, diversity and inclusion, and LGBT+ workers.
  • SB Sabrine El Baroudi is an Assistant Professor in Organizational Behavior and Human Resource Management at the Department of Management and Organization, Vrije Universiteit Amsterdam, the Netherlands. She is also a director of the VU Knowledge Hub for Feedback Culture. Her main research interests are proactive work and career behaviors, feedback, meaningful work, and other (green) HRM-related topics. She is particularly interested in examining how these topics influence performance and work behaviors at different organizational levels; that is, individual, team, and organizational levels.

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Methodology

Research Methods | Definitions, Types, Examples

Research methods are specific procedures for collecting and analyzing data. Developing your research methods is an integral part of your research design . When planning your methods, there are two key decisions you will make.

First, decide how you will collect data . Your methods depend on what type of data you need to answer your research question :

  • Qualitative vs. quantitative : Will your data take the form of words or numbers?
  • Primary vs. secondary : Will you collect original data yourself, or will you use data that has already been collected by someone else?
  • Descriptive vs. experimental : Will you take measurements of something as it is, or will you perform an experiment?

Second, decide how you will analyze the data .

  • For quantitative data, you can use statistical analysis methods to test relationships between variables.
  • For qualitative data, you can use methods such as thematic analysis to interpret patterns and meanings in the data.

Table of contents

Methods for collecting data, examples of data collection methods, methods for analyzing data, examples of data analysis methods, other interesting articles, frequently asked questions about research methods.

Data is the information that you collect for the purposes of answering your research question . The type of data you need depends on the aims of your research.

Qualitative vs. quantitative data

Your choice of qualitative or quantitative data collection depends on the type of knowledge you want to develop.

For questions about ideas, experiences and meanings, or to study something that can’t be described numerically, collect qualitative data .

If you want to develop a more mechanistic understanding of a topic, or your research involves hypothesis testing , collect quantitative data .

Qualitative to broader populations. .
Quantitative .

You can also take a mixed methods approach , where you use both qualitative and quantitative research methods.

Primary vs. secondary research

Primary research is any original data that you collect yourself for the purposes of answering your research question (e.g. through surveys , observations and experiments ). Secondary research is data that has already been collected by other researchers (e.g. in a government census or previous scientific studies).

If you are exploring a novel research question, you’ll probably need to collect primary data . But if you want to synthesize existing knowledge, analyze historical trends, or identify patterns on a large scale, secondary data might be a better choice.

Primary . methods.
Secondary

Descriptive vs. experimental data

In descriptive research , you collect data about your study subject without intervening. The validity of your research will depend on your sampling method .

In experimental research , you systematically intervene in a process and measure the outcome. The validity of your research will depend on your experimental design .

To conduct an experiment, you need to be able to vary your independent variable , precisely measure your dependent variable, and control for confounding variables . If it’s practically and ethically possible, this method is the best choice for answering questions about cause and effect.

Descriptive . .
Experimental

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Research methods for collecting data
Research method Primary or secondary? Qualitative or quantitative? When to use
Primary Quantitative To test cause-and-effect relationships.
Primary Quantitative To understand general characteristics of a population.
Interview/focus group Primary Qualitative To gain more in-depth understanding of a topic.
Observation Primary Either To understand how something occurs in its natural setting.
Secondary Either To situate your research in an existing body of work, or to evaluate trends within a research topic.
Either Either To gain an in-depth understanding of a specific group or context, or when you don’t have the resources for a large study.

Your data analysis methods will depend on the type of data you collect and how you prepare it for analysis.

Data can often be analyzed both quantitatively and qualitatively. For example, survey responses could be analyzed qualitatively by studying the meanings of responses or quantitatively by studying the frequencies of responses.

Qualitative analysis methods

Qualitative analysis is used to understand words, ideas, and experiences. You can use it to interpret data that was collected:

  • From open-ended surveys and interviews , literature reviews , case studies , ethnographies , and other sources that use text rather than numbers.
  • Using non-probability sampling methods .

Qualitative analysis tends to be quite flexible and relies on the researcher’s judgement, so you have to reflect carefully on your choices and assumptions and be careful to avoid research bias .

Quantitative analysis methods

Quantitative analysis uses numbers and statistics to understand frequencies, averages and correlations (in descriptive studies) or cause-and-effect relationships (in experiments).

You can use quantitative analysis to interpret data that was collected either:

  • During an experiment .
  • Using probability sampling methods .

Because the data is collected and analyzed in a statistically valid way, the results of quantitative analysis can be easily standardized and shared among researchers.

Research methods for analyzing data
Research method Qualitative or quantitative? When to use
Quantitative To analyze data collected in a statistically valid manner (e.g. from experiments, surveys, and observations).
Meta-analysis Quantitative To statistically analyze the results of a large collection of studies.

Can only be applied to studies that collected data in a statistically valid manner.

Qualitative To analyze data collected from interviews, , or textual sources.

To understand general themes in the data and how they are communicated.

Either To analyze large volumes of textual or visual data collected from surveys, literature reviews, or other sources.

Can be quantitative (i.e. frequencies of words) or qualitative (i.e. meanings of words).

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If you want to know more about statistics , methodology , or research bias , make sure to check out some of our other articles with explanations and examples.

  • Chi square test of independence
  • Statistical power
  • Descriptive statistics
  • Degrees of freedom
  • Pearson correlation
  • Null hypothesis
  • Double-blind study
  • Case-control study
  • Research ethics
  • Data collection
  • Hypothesis testing
  • Structured interviews

Research bias

  • Hawthorne effect
  • Unconscious bias
  • Recall bias
  • Halo effect
  • Self-serving bias
  • Information bias

Quantitative research deals with numbers and statistics, while qualitative research deals with words and meanings.

Quantitative methods allow you to systematically measure variables and test hypotheses . Qualitative methods allow you to explore concepts and experiences in more detail.

In mixed methods research , you use both qualitative and quantitative data collection and analysis methods to answer your research question .

A sample is a subset of individuals from a larger population . Sampling means selecting the group that you will actually collect data from in your research. For example, if you are researching the opinions of students in your university, you could survey a sample of 100 students.

In statistics, sampling allows you to test a hypothesis about the characteristics of a population.

The research methods you use depend on the type of data you need to answer your research question .

  • If you want to measure something or test a hypothesis , use quantitative methods . If you want to explore ideas, thoughts and meanings, use qualitative methods .
  • If you want to analyze a large amount of readily-available data, use secondary data. If you want data specific to your purposes with control over how it is generated, collect primary data.
  • If you want to establish cause-and-effect relationships between variables , use experimental methods. If you want to understand the characteristics of a research subject, use descriptive methods.

Methodology refers to the overarching strategy and rationale of your research project . It involves studying the methods used in your field and the theories or principles behind them, in order to develop an approach that matches your objectives.

Methods are the specific tools and procedures you use to collect and analyze data (for example, experiments, surveys , and statistical tests ).

In shorter scientific papers, where the aim is to report the findings of a specific study, you might simply describe what you did in a methods section .

In a longer or more complex research project, such as a thesis or dissertation , you will probably include a methodology section , where you explain your approach to answering the research questions and cite relevant sources to support your choice of methods.

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the meaning of research work

What Is A Research (Scientific) Hypothesis? A plain-language explainer + examples

By:  Derek Jansen (MBA)  | Reviewed By: Dr Eunice Rautenbach | June 2020

If you’re new to the world of research, or it’s your first time writing a dissertation or thesis, you’re probably noticing that the words “research hypothesis” and “scientific hypothesis” are used quite a bit, and you’re wondering what they mean in a research context .

“Hypothesis” is one of those words that people use loosely, thinking they understand what it means. However, it has a very specific meaning within academic research. So, it’s important to understand the exact meaning before you start hypothesizing. 

Research Hypothesis 101

  • What is a hypothesis ?
  • What is a research hypothesis (scientific hypothesis)?
  • Requirements for a research hypothesis
  • Definition of a research hypothesis
  • The null hypothesis

What is a hypothesis?

Let’s start with the general definition of a hypothesis (not a research hypothesis or scientific hypothesis), according to the Cambridge Dictionary:

Hypothesis: an idea or explanation for something that is based on known facts but has not yet been proved.

In other words, it’s a statement that provides an explanation for why or how something works, based on facts (or some reasonable assumptions), but that has not yet been specifically tested . For example, a hypothesis might look something like this:

Hypothesis: sleep impacts academic performance.

This statement predicts that academic performance will be influenced by the amount and/or quality of sleep a student engages in – sounds reasonable, right? It’s based on reasonable assumptions , underpinned by what we currently know about sleep and health (from the existing literature). So, loosely speaking, we could call it a hypothesis, at least by the dictionary definition.

But that’s not good enough…

Unfortunately, that’s not quite sophisticated enough to describe a research hypothesis (also sometimes called a scientific hypothesis), and it wouldn’t be acceptable in a dissertation, thesis or research paper . In the world of academic research, a statement needs a few more criteria to constitute a true research hypothesis .

What is a research hypothesis?

A research hypothesis (also called a scientific hypothesis) is a statement about the expected outcome of a study (for example, a dissertation or thesis). To constitute a quality hypothesis, the statement needs to have three attributes – specificity , clarity and testability .

Let’s take a look at these more closely.

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the meaning of research work

Hypothesis Essential #1: Specificity & Clarity

A good research hypothesis needs to be extremely clear and articulate about both what’ s being assessed (who or what variables are involved ) and the expected outcome (for example, a difference between groups, a relationship between variables, etc.).

Let’s stick with our sleepy students example and look at how this statement could be more specific and clear.

Hypothesis: Students who sleep at least 8 hours per night will, on average, achieve higher grades in standardised tests than students who sleep less than 8 hours a night.

As you can see, the statement is very specific as it identifies the variables involved (sleep hours and test grades), the parties involved (two groups of students), as well as the predicted relationship type (a positive relationship). There’s no ambiguity or uncertainty about who or what is involved in the statement, and the expected outcome is clear.

Contrast that to the original hypothesis we looked at – “Sleep impacts academic performance” – and you can see the difference. “Sleep” and “academic performance” are both comparatively vague , and there’s no indication of what the expected relationship direction is (more sleep or less sleep). As you can see, specificity and clarity are key.

A good research hypothesis needs to be very clear about what’s being assessed and very specific about the expected outcome.

Hypothesis Essential #2: Testability (Provability)

A statement must be testable to qualify as a research hypothesis. In other words, there needs to be a way to prove (or disprove) the statement. If it’s not testable, it’s not a hypothesis – simple as that.

For example, consider the hypothesis we mentioned earlier:

Hypothesis: Students who sleep at least 8 hours per night will, on average, achieve higher grades in standardised tests than students who sleep less than 8 hours a night.  

We could test this statement by undertaking a quantitative study involving two groups of students, one that gets 8 or more hours of sleep per night for a fixed period, and one that gets less. We could then compare the standardised test results for both groups to see if there’s a statistically significant difference. 

Again, if you compare this to the original hypothesis we looked at – “Sleep impacts academic performance” – you can see that it would be quite difficult to test that statement, primarily because it isn’t specific enough. How much sleep? By who? What type of academic performance?

So, remember the mantra – if you can’t test it, it’s not a hypothesis 🙂

A good research hypothesis must be testable. In other words, you must able to collect observable data in a scientifically rigorous fashion to test it.

Defining A Research Hypothesis

You’re still with us? Great! Let’s recap and pin down a clear definition of a hypothesis.

A research hypothesis (or scientific hypothesis) is a statement about an expected relationship between variables, or explanation of an occurrence, that is clear, specific and testable.

So, when you write up hypotheses for your dissertation or thesis, make sure that they meet all these criteria. If you do, you’ll not only have rock-solid hypotheses but you’ll also ensure a clear focus for your entire research project.

What about the null hypothesis?

You may have also heard the terms null hypothesis , alternative hypothesis, or H-zero thrown around. At a simple level, the null hypothesis is the counter-proposal to the original hypothesis.

For example, if the hypothesis predicts that there is a relationship between two variables (for example, sleep and academic performance), the null hypothesis would predict that there is no relationship between those variables.

At a more technical level, the null hypothesis proposes that no statistical significance exists in a set of given observations and that any differences are due to chance alone.

And there you have it – hypotheses in a nutshell. 

If you have any questions, be sure to leave a comment below and we’ll do our best to help you. If you need hands-on help developing and testing your hypotheses, consider our private coaching service , where we hold your hand through the research journey.

the meaning of research work

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16 Comments

Lynnet Chikwaikwai

Very useful information. I benefit more from getting more information in this regard.

Dr. WuodArek

Very great insight,educative and informative. Please give meet deep critics on many research data of public international Law like human rights, environment, natural resources, law of the sea etc

Afshin

In a book I read a distinction is made between null, research, and alternative hypothesis. As far as I understand, alternative and research hypotheses are the same. Can you please elaborate? Best Afshin

GANDI Benjamin

This is a self explanatory, easy going site. I will recommend this to my friends and colleagues.

Lucile Dossou-Yovo

Very good definition. How can I cite your definition in my thesis? Thank you. Is nul hypothesis compulsory in a research?

Pereria

It’s a counter-proposal to be proven as a rejection

Egya Salihu

Please what is the difference between alternate hypothesis and research hypothesis?

Mulugeta Tefera

It is a very good explanation. However, it limits hypotheses to statistically tasteable ideas. What about for qualitative researches or other researches that involve quantitative data that don’t need statistical tests?

Derek Jansen

In qualitative research, one typically uses propositions, not hypotheses.

Samia

could you please elaborate it more

Patricia Nyawir

I’ve benefited greatly from these notes, thank you.

Hopeson Khondiwa

This is very helpful

Dr. Andarge

well articulated ideas are presented here, thank you for being reliable sources of information

TAUNO

Excellent. Thanks for being clear and sound about the research methodology and hypothesis (quantitative research)

I have only a simple question regarding the null hypothesis. – Is the null hypothesis (Ho) known as the reversible hypothesis of the alternative hypothesis (H1? – How to test it in academic research?

Tesfaye Negesa Urge

this is very important note help me much more

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Greater Good Science Center • Magazine • In Action • In Education

Happiness Defined

What is happiness.

Coming up with a formal definition of happiness can be tricky. After all, shouldn’t we just know it when we feel it? In fact, we often use the term to describe a range of positive emotions, including amusement, joy, pride, and contentment.

But to understand the causes and effects of happiness, researchers first need to define it. For most, the term happiness is interchangeable with “subjective well-being,” which is typically measured by asking people about how satisfied they feel with their lives (evaluative), how much positive and negative emotion they tend to feel (affective), and their sense of meaning and purpose (eudaimonic). In her 2007 book The How of Happiness , positive psychology researcher Sonja Lyubomirsky elaborates, describing happiness as “the experience of joy, contentment, or positive well-being, combined with a sense that one’s life is good, meaningful, and worthwhile.”

However, it’s important to note that social and cultural factors also influence how we think about happiness. For example, studies by William Tov and others have found that people from cultures that embrace more collectivist ideals think about happiness more in terms of harmony and contentment, while more individualistic-minded people connect it to feelings of exuberance and joy. Happiness levels are also shaped by social groups, like families; happier people increase the happiness of people around them.

Though people around the world have different ways of thinking about happiness and perhaps even experience it in different ways, most involve feeling positive generally and about life overall.

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Why Practice It?

Many studies have found that happiness actually improves other aspects of our lives. Here is an overview of some of the good stuff that research has linked to happiness.

  • Happiness is good for our health : Happier people are less likely to get sick, and they live longer.
  • Happiness is associated with more satisfying romantic relationships as well as stronger friendships .
  • Happier people make more money and are more productive at work .
  • Happier people are more generous .
  • Happier people cope better with stress and trauma .
  • Happier people are more creative and are better able to see the big picture .

Of course, there will be times in life when happiness feels out of reach. That’s OK. Our unpleasant emotions are appropriate responses to difficult situations; they’re there to guide our responses and help us make meaning from challenges and adversity.

Indeed, there is a great deal of research suggesting that trying to feel or falsely express happiness in bad situations is harmful to mental and physical health—and that striving to feel constantly happy can actually diminish your overall happiness in life. Multiple studies suggest that experiencing and embracing a range of emotions, not just the positive ones, is good for our mental and physical health. It’s also important to note that injury and illness can make happiness harder to achieve. For example, concussions and long COVID are both associated with depression.

In short, happiness in life is a worthy aspiration, and there are benefits to feeling happy—but it’s not realistic or healthy to expect a constant stream of positive emotions. When you do feel unhappy, it’s important to listen to that signal. Perhaps it’s time to change what you’re doing or thinking, seek support from a friend or therapist, or work to address a challenge you are facing. During especially hard times in life, suggests the research, you might look for meaning or psychological richness in your experiences, instead of trying to force yourself to be happier.

“Aim for noticing how you really feel right at that moment—and embrace all your diverse feelings,” suggests James Baraz. This will pave the way to happiness down the line.

How Do I Cultivate It?

Our happiness is shaped by genetics, life experience, social forces,  and culture, as well as individual choices. While your control over most of those domains is limited, there are steps you can take on a personal level to increase your chances of experiencing happiness in life. And all of us can act to change culture and address inequalities that affect happiness on a collective level.

Here are some of the keys to happiness identified by researchers, along with some specific, science-based activities for strengthening skills of happiness, in ourselves and in society.

Build relationships: Perhaps the dominant finding from happiness research is that social connections are fundamental. Try these practices to strengthen trust, mutual support, and affection in your relationships:

  • Best Possible Self for Relationships : Imagine your relationship going as well as it possibly could.
  • Mental Subtraction of Relationships : Visualize what your life would be like without the people around you.
  • Gift of Time : Invest in your relationships by spending quality time with people you care about.
  • Learn more ways to strengthen relationships on our website Greater Good in Action.

Practice different kinds of appreciation. Life can be hard, because negative events and emotions are inevitable. But we can bolster our resilience by shining the light of our attention on the good things.

  • Savoring Walk : Take a walk and pay attention to positive feelings and experiences, to deepen and extend them.
  • Gratitude : Count your blessings on a regular basis, whether by writing a letter, keeping a journal, or just saying thanks.
  • Time Capsule : Create a collection of positive experiences to surprise your future self.
  • Mental Subtraction of Positive Events : Visualize what your life would be like without the good things you have.

Pay attention. Studies find that people who practice mindfulness —the moment-by-moment awareness of our thoughts, feelings, and external circumstances—score higher on measures of happiness, and lower on measures of anxiety and distress.

  • Mindful Breathing : This meditation is the most basic way to cultivate mindful attention.
  • Raisin Meditation : You can put your busy life on pause by spending a few minutes feeling and tasting a raisin in your mouth.
  • Self-Compassion Break : Stressed? Self-critical? Take just a moment to speak kindly to yourself.
  • Get more mindfulness exercises on Greater Good in Action.

Practice kindness. Researchers believe generosity feels good because it highlights and incentivizes positive social interactions and strengthens the social bonds that support happiness. Here are some ways to be kind.

  • Do nice things for other people: Neuroscience research shows that when we do nice things for others, our brains light up in areas associated with pleasure and reward.
  • Compassion Meditation : This meditation fosters feelings of compassion and concern for others by training you to notice suffering and strive to alleviate it.
  • Spend money on other people: Similarly, research by Elizabeth Dunn and her colleagues finds that people report greater happiness when they spend money on others than when they spend it on themselves.
  • Learn more ways to practice kindness at Greater Good in Action.

Move your body—and then rest. Exercise isn’t just good for our bodies; it’s good for our happiness. So is sleep!

  • Get physical: Studies show that regular physical activity increases happiness and self-esteem, reduces anxiety and stress, and can even lift symptoms of depression. “Exercise may very well be the most effective instant happiness booster of all activities,” writes Sonja Lyubomirsky in The How of Happiness .
  • Spend time in nature : People who are more connected to nature tend to experience more positive emotions, vitality, and life satisfaction.
  • Then get rest: Research has consistently linked lower sleep to lower happiness . What’s more, a study of more than 900 women, led by psychologist Daniel Kahneman, found that getting just one more hour of sleep each night might have a greater effect on happiness than getting a $60,000 raise.

Address inequalities. More egalitarian countries consistently rank among the happiest in the world—and there is evidence that economic, racial, and gender inequality hurts the happiness of disadvantaged groups . Fortunately, there are steps we can take to address these inequalities.

  • Remove barriers to voting. Inequality depresses the vote of low-income people, which reduces their political power. You can help address that situation by supporting organizations dedicated to voter mobilization and reform.
  • Work against racial prejudice and xenophobia. There are many research-tested ways to address racial inequality , on individual and collective levels.
  • Work for gender and LGBTQ+ equality. There are also evidence-based ways to reduce inequality between men and women, and to expand and protect the human rights of gay, lesbian, bisexual, transgender, and queer people.
  • Support efforts to address poverty. “Economic wealth matters across cultures,” says researcher William Tov. “In every culture, wealthier people generally are happier than less wealthy people.” Fortunately, volunteering and political activism—or more specifically, the sense of meaning and purpose those involve— seem to be good for both mental and physical health . If we can help our society address poverty, says the evidence, then everyone benefits .

Of course, happiness-boosting activities don’t work equally well for everyone . Understanding yourself better can help you choose practices and exercises that align with your personality, your situation, and your goals.

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Feature Article: The Question of Who You Are

The Science and Technology Directorate (S&T) and the U.S. Citizenship and Immigration Service (USCIS) have joined forces to issue digital credentials using openly developed, free to implement internet standards. Here’s what this means and why it matters.

One of the critical challenges of our technology-driven, interconnected world is identity.

A digital mockup of a resident alien card issued by the U.S. Citizenship & Immigration Services. Top to bottom it reads, "Back" with a blue arrow. Below that it reads, " Privacy enhancing credential. This credential is able to selectively disclose claims. Learn more." Below that, it reads, "U.S. Permanent Resident", green check mark, "verified". Below that it reads, "Name Claudine Marcelline, Date of Birth, 4/12/1989, Sex F, Country of Birth, Utopia, Category IR1, USCIS#000-000-000, Resident since 5/20/2018." A background image of the U.S. flag and the Statue of Liberty and a seal reading "U.S. Department of Homeland Security", below that "U.S. Citizenship & Immigration Services demo.uscis.gov”.

Without even speaking a word, we identify ourselves every day and in many different ways. Perhaps you enter a PIN to sign-in to a bank account or use a password to login to your health benefits. You scan your own face to unlock your phone to access some of the apps running on it. You swipe an ID card with a magnetic stripe to enter your office building. And of course, when you travel or work abroad, you must identify yourself with a passport. But what are you sharing when you identify yourself? Where does that identifying number or document come from, and who controls access to it?

S&T is working to help make your identity more secure, and to put control over your privacy and personal information into your own hands. Jared Goodwin, Chief of the Document Management Division within the Office of Intake and Document Production (OIDP) at USCIS, was also working on these issues. OIDP is tasked with the production of all immigration documents—they design the documents and acquire the vendors to produce them. USCIS wants to be able to issue digital credentials, like a green card, to a smartphone, which would be easier to carry and use, more secure, and it could be supported online. Actions like renewing and modifying immigration status would not require standing in line at an office somewhere.

Jared discovered S&T’s Silicon Valley Innovation Program was exploring similar solutions. “They’re going out to industry to look for ways to partner with agencies to prevent forgery and the counterfeiting of certificates and licenses,” he said. Jared contacted SVIP and the solution that they settled on together is to use two openly developed, global standards called Verifiable Credentials Data Model (VCDM) and Decentralized Identifiers (DID).

Created by the World Wide Web Consortium (W3C), a global standards development organization, with the support of S&T, USCIS, and many other like-minded partners, these standards describe how a secure, privacy respecting digital credentialing process can be implemented.

DIDs are unique identifiers that can be assigned to organizations, devices, or people. A DID, unlike a social security number, functions solely as an identifier and cannot be used for verification, as that role is deliberately separated and implemented using public key cryptography.

VCDM is a way to express credentials in a way that is cryptographically secure, privacy respecting, and machine verifiable. In addition, this standard enables a person to minimize the disclosure of personal data by implementing selective disclosure capabilities.

Selective disclosure allows digital credentials to contain many pieces of information but gives the user discretion to share only the specific information required for a particular transaction with the government or non-government entities, rather than disclosing the entire contents of the credential. So, the ability to selectively share, with consent, only pieces of information needed for a particular encounter is a highly desired capability.

Diagram of the Decentralized Identifiers (DiD) process showing an Issuer provisioning credentials to a Digital Wallet Holder, which selectively discloses credentials and verifies the binding to a presenting human. The Verifier then retrieves metadata from the metadata resolver, which publishes the metadata to the Issuer. In the upper left it reads, “Issuer” above a building and “Provision” below. To the right of that, it reads, “Issuance Protocol”. To the right of that it reads, “Digital Wallet Holder” above and “Manage” below. To the right of that it reads, “Exchange Protocol”. To the right of that it reads, “Verifier” above and “Verify” below. Below that it reads, “Retrieve Metadata (Public Keys, Credential Status) from issuer to check for integrity, validity and provenance.” To the left of that it reads “Metadata Resolver” above “Resolve”. To the left of that and below the initial starting point it reads, “Publish Metadata (Public Keys, Credential Status) to allow verifiers to check for integrity, validity and provenance”.

Consider this example: a customer attempts to purchase a six-pack of beer at a convenience store. The way it works now, the cashier asks for an ID to verify the customer is old enough to buy liquor, but when they hand over their driver’s license…what else are they handing over?

Think about that very common transaction for a moment: a state-issued document from a department of motor vehicles, which is intended to demonstrate the qualification to drive a car, is presented to verify that you are older than 21. This document shares your date of birth, address, ID number, organ donation status, if you need to wear glasses, even your height and weight.

Part of the promise of the W3C standards is the ability to share only the data required for a transaction. In the scenario above, when the cashier asks for proof that you are older than 21, the customer could use the digital Permanent Resident Card on their phone to prove their verified age without sharing any other information (not even a specific date of birth). This is an important step towards putting privacy back in the hands of the people.

The DHS Privacy Office , charged with “embedding and enforcing privacy protections and transparency in all DHS activities,” has been brought into the process to review the W3C VCDM/DID framework and advise on any potential issues. 

“Beyond ensuring global interoperability, standards developed by the W3C undergo wide reviews that ensure that they incorporate security, privacy, accessibility, and internationalization,” said SVIP Managing Director Melissa Oh, “by helping implement these standards in our digital credentialing efforts, S&T, through SVIP, is helping to ensure that the technologies we use make a difference for people in how they secure their digital transactions and protect their privacy.”

“Going forward, the government wants to ensure individuals have agency and control over their digital interactions,” said Goodwin. “The user should be able to own their identity and decide when to share it, and we don’t want a system that has to reach back to an agency for verification.”

Thanks to the work of SVIP, USCIS and many others, digital credentials using W3C VCDM and W3C DID standards are going to become more and more common in the near future. The work will make a big difference preventing identity theft and forgery, allowing individuals to control their own personal information and privacy, especially online.

For related media inquiries, please contact [email protected] .

  • Science and Technology
  • Credentialing
  • U.S. Citizenship and Immigration Services (USCIS)

IMAGES

  1. RESEARCH Scientific research work and students research activity

    the meaning of research work

  2. What is Research? Definition , Purpose & Typical Research step?

    the meaning of research work

  3. PPT

    the meaning of research work

  4. What is Research?

    the meaning of research work

  5. (PDF) Significance of Research Process in Research Work

    the meaning of research work

  6. Module 1: Introduction: What is Research?

    the meaning of research work

VIDEO

  1. WHAT IS RESEARCH? TAGALOG

  2. What is Research? Urdu / Hindi

  3. LECTURE 1. THE MEANING OF RESEARCH

  4. Research Meaning

  5. What is research

  6. What is Research Design

COMMENTS

  1. On the meaning of work: A theoretical integration and review

    Research in this tradition has tended to focus on how employees make or find positive meaning in their work, even, for example, in work that is typically considered undesirable (Wrzesniewski and Dutton, 2001, Wrzesniewski et al., 2003). 4 However, the use of the word "meaning" in the meaning of work literature primarily denotes positive ...

  2. What factors contribute to the meaning of work? A validation of Morin's

    The first theoretical model for the meaning of work was based on research in the MOW project (MOW International Research team, 1987), considered the "most empirically rigorous research ever undertaken to understand, both within and between countries, the meanings people attach to their work roles" (Brief, 1991, p. 176). This view suggests ...

  3. A Review of the Empirical Literature on Meaningful Work: Progress and

    This discourse focuses upon ethical concerns regarding whether work is "good" or "bad" and whether the meaning of work as compulsion has crowded out the meaning of work as free, expressive, and creative action (Spencer, 2009). Future research within HRD could explore the interrelationship or differences between the "meaning of" and ...

  4. On the meaning of work: A theoretical integration and review

    Abstract. The meaning of work literature is the product of a long tradition of rich inquiry spanning many disciplines. Yet, the field lacks overarching structures that would facilitate greater integration, consistency, and understanding of this body of research. Current research has developed in ways that have created relatively independent ...

  5. PDF The meaning of work

    Work holds different meanings for differ-ent people. For some people, work is a means to a financial end (a job), an unfortunate necessity of life that provides a paycheck and funds life's more ...

  6. Work and the good life: How work contributes to meaning in life

    The research on meaning in work could also be benefitted by a larger focus on the specific factors that contribute to making work feel meaningful. Research on meaningful work has largely focused on defining what meaningful work entails and identifying positive organizational outcomes of meaningful work (e.g., Fairlie, 2010 , Lips-Wiersma and ...

  7. What factors contribute to the meaning of work? A ...

    Considering the recent and current evolution of work and the work context, the meaning of work is becoming an increasingly relevant topic in research in the social sciences and humanities, particularly in psychology. In order to understand and measure what contributes to the meaning of work, Morin constructed a 30-item questionnaire that has become predominant and has repeatedly been used in ...

  8. On the Meaning of Work: A Theoretical Integration and Review

    Abstract. The meaning of work literature is the product of a long tradition of rich inquiry spanning many disciplines. Yet, the field lacks overarching structures that would facilitate greater ...

  9. The Meaning of Work

    The concept of work centrality suggests that the meaningfulness of work is related to how important work is in relation to other aspects of a person's life (e.g., family, leisure, faith , community). The more important or central work is to a person's life, the more positive is the meaning ascribed to this work.

  10. Notes on the Meaning of Work: Labor, Work, and Action in the 21st

    Abstract. There is growing evidence that the nature of work is evolving, with the emergence of new forms such as open innovation and crowdsourcing, freelancing and the gig economy and artificial intelligence, and robotics. Debates about the consequences of these changes are flourishing. However, it seems that what work means for different ...

  11. (PDF) Creating Meaning and Purpose at Work

    job or work is harmonious with meaning and purpose in the worker's life as a whole, or. alternatively, helps workers build more meaning in their lives. In the largest circle is the. degree to ...

  12. The meaning of working.

    This volume provides a first analysis and summary of findings from the MOW research project. The first three chapters describe the reasons, theoretical bases, and methodological approaches utilized in the Meaning Of Working (MOW)-study. Chapters 4-13 provide the body of major findings. They deal with an analysis of the main dimensions of the empirically identified work meanings . . . their ...

  13. Is this work? Revisiting the definition of work in the 21st century

    6.3 Work as ubiquitous. Quey (1968, p. 223) defined work as "purposeful mental and physical human activity which deliberately points beyond the present". Richardson broadened the definition of work as "embedded in family and personal lives, as well as in paid employment" ( 1993 p. 431).

  14. To Work or Not to Work: Construction of Meaning of Work and Making Work

    To Work or Not to Work: Construction of Meaning of Work and Making Work Choices. M V Anuradha, E S Srinivas, Manish Singhal, and S Ramnarayan. includes research articles that focus on the analysis and resolution of managerial and academic issues based on analytical and empirical or case research. Executive Summary. KEY WORDS.

  15. What Is Research, and Why Do People Do It?

    Abstractspiepr Abs1. Every day people do research as they gather information to learn about something of interest. In the scientific world, however, research means something different than simply gathering information. Scientific research is characterized by its careful planning and observing, by its relentless efforts to understand and explain ...

  16. What Is a Research Design

    A research design is a strategy for answering your research question using empirical data. Creating a research design means making decisions about: Your overall research objectives and approach. Whether you'll rely on primary research or secondary research. Your sampling methods or criteria for selecting subjects. Your data collection methods.

  17. What is Research

    Research is the careful consideration of study regarding a particular concern or research problem using scientific methods. According to the American sociologist Earl Robert Babbie, "research is a systematic inquiry to describe, explain, predict, and control the observed phenomenon. It involves inductive and deductive methods.".

  18. What is Research? Definition, Types, Methods and Process

    Research is defined as a meticulous and systematic inquiry process designed to explore and unravel specific subjects or issues with precision. This methodical approach encompasses the thorough collection, rigorous analysis, and insightful interpretation of information, aiming to delve deep into the nuances of a chosen field of study.

  19. Research

    Original research, also called primary research, is research that is not exclusively based on a summary, review, or synthesis of earlier publications on the subject of research.This material is of a primary-source character. The purpose of the original research is to produce new knowledge rather than present the existing knowledge in a new form (e.g., summarized or classified).

  20. What Makes Work Meaningful?

    In fact, research shows that meaningfulness is more important to us than any other aspect of our jobs — including pay and rewards, opportunities for promotion, and working conditions. When we ...

  21. Research Methods

    Research methods are specific procedures for collecting and analyzing data. Developing your research methods is an integral part of your research design. When planning your methods, there are two key decisions you will make. First, decide how you will collect data. Your methods depend on what type of data you need to answer your research question:

  22. What Is A Research Hypothesis? A Simple Definition

    A research hypothesis (also called a scientific hypothesis) is a statement about the expected outcome of a study (for example, a dissertation or thesis). To constitute a quality hypothesis, the statement needs to have three attributes - specificity, clarity and testability. Let's take a look at these more closely.

  23. What we can VERIFY about Project 2025

    During the BET Awards on June 30, host Taraji P. Henson told viewers to do their research on Project 2025, saying, "It's time for us to play chess, not checkers. It's about making decisions that will affect us as human beings, our careers, our next generations to come.

  24. Happiness Definition

    Here is an overview of some of the good stuff that research has linked to happiness. Happiness is good for our health: Happier people are less likely to get sick, and they live longer. Happiness is associated with more satisfying romantic relationships as well as stronger friendships. Happier people make more money and are more productive at work.

  25. PDF Unit: 01 Research: Meaning, Types, Scope and Significance

    Understand research design and the process of research design. Formulate a research problem and state it as a hypothesis. 1.3 MEANING OF RESEARCH Research is a process to discover new knowledge to find answers to a question. The word research has two parts re (again) and search (find) which denote that we are taking up an

  26. Feature Article: The Question of Who You Are

    Thanks to the work of SVIP, USCIS and many others, digital credentials using W3C VCDM and W3C DID standards are going to become more and more common in the near future. The work will make a big difference preventing identity theft and forgery, allowing individuals to control their own personal information and privacy, especially online.