Skip to main content
SpringerLink
Log in

Putting personality in context: determinants of research productivity and impact in political science

  • Published:
Scientometrics Aims and scope Submit manuscript

Abstract

Research on the determinants of scholarly productivity is flourishing, driven both by long-standing curiosity about its wide variation, and by recent concern over race and gender inequalities. Beyond standard structural and demographic determinants of research output, some studies point to the role of individual psychology. We contribute to scholarship on personality and productivity by showing not only that personality matters, but when and for whom. Using an original, representative study of faculty from one discipline, political science, we propose and test several hypotheses about the “Big Five” personality determinants of productivity, as gauged through counts of publications, H-index scores, and citations. Controlling for a large number of familiar determinants (e.g., race, gender, rank, and institutional incentives), we find that conscientiousness predicts productivity, but that its effects are conditioned by openness to experience. More precisely, we discover that these two personality traits have compensatory effects, such that openness to experience and conscientiousness each matter most in the absence of the other. In addition, personality has heterogeneous impacts on productivity across different contexts; conscientiousness more strongly affects scholarly output in research-oriented institutions, while collaboration reduces the penalty associated with lack of conscientiousness.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1

Source: PASS data for political science, 2017. Note: The figure shows 76% confidence intervals. Comparison of two 76% confidence intervals is equivalent to a 90% (p = .10, two-tailed) test of statistical significance at the point of overlap. Citations are logged

Fig. 2

Source: PASS Data for Political Science, 2017. Note: The figure shows 76% confidence intervals. Comparison of two 76% confidence intervals is equivalent to a 90% (p = .10, two-tailed) test of statistical significance at the point of overlap. Citations are logged

Fig. 3

Source: PASS Data for Political Science, 2017. Note: The figure shows 76% confidence intervals. Comparison of two 76% confidence intervals is equivalent to a 90% (p = .10, two-tailed) test of statistical significance at the point of overlap. Citations are logged

Similar content being viewed by others

Notes

  1. In their analyses, Grosul and Feist (2014) do not include measures of such attributes as where one earned their doctoral degree, or the character of an individual’s current academic department.

  2. In June, 2017 we conducted a companion study of sociology departments (at the same sampled universities). We discuss those results elsewhere (Djupe et al. 2019).

  3. We had coders collect email addresses from the webpages for these departments. 44 email addresses were not usable.

  4. Simon Hix graciously shared a list that went beyond what was reported in his paper, including 400 departments—this covered almost all of our sample.

  5. We also attempted to replicate this procedure with Google Scholar, but discovered that a large portion of our respondents did not have public profiles there. SSCI counts are much lower than Scholar, but are highly correlated (Martín-Martín et al. 2018).

  6. r(publications, H-index) = .81; r(publications, logged citations) = .71; r(logged citations, H-index) = .84.

  7. The dependent variable for citations is estimated by adding one to the count, before logging. Hence, we exponentiate predicted values and subtract one to obtain predicted effects.

  8. We do not find a statistically significant interaction between conscientiousness and any other personality variables beyond openness.

  9. We obtain a similar pattern of results if we the model the average number of publications (dividing by years since PhD).

  10. We thank Reviewer 1 for suggesting this direction of discussion and analysis.

References

  • Amabile, T. M. (1996). Creativity in context. Boulder: Westview Press.

    Google Scholar 

  • Bakker, B. N., & Lelkes, Y. (2018). Selling ourselves short? How abbreviated measures of personality change the way we think about personality and politics. Journal of Politics,80(4), 1311–1325.

    Google Scholar 

  • Blackburn, R. T., & Lawrence, J. H. (1995). Faculty at work. Baltimore: Johns Hopkins University Press.

    Google Scholar 

  • Dion, M. L., Sumner, J. L., & Mitchell, S. M. (2018). Gendered citation patterns across political science and social science methodology fields. Political Analysis,26(July), 312–327.

    Google Scholar 

  • Djupe, P. A. (2015). Peer reviewing in political science: New survey results. PS: Political Science and Politics, 48(2), 346–351.

    Google Scholar 

  • Djupe, P. A., Smith, A. E., & Sokhey, A. E. (2019). Explaining gender in the journals: How submission practices affect publication patterns in political science. PS: Political Science and Politics,52(January), 71–77.

    Google Scholar 

  • Ericsson, K. A. (1999). Creative expertise as superior reproducible performance: Innovative and flexible aspects of expert performance. Psychological Inquiry,10(4), 329–361.

    Google Scholar 

  • Feist, G. J. (1998). A meta-analysis of personality in scientific and artistic creativity. Personality and Social Psychology Review,2(4), 290–309.

    Google Scholar 

  • Feist, G. J. (2006). How development and personality influence scientific thought, interest, and achievement. Review of General Psychology,10(2), 163–182.

    Google Scholar 

  • Feist, G. J. (2014). Psychometric studies of scientific talent and eminence. In D. K. Simonton (Ed.), The Wiley handbook of genius (pp. 62–86). Chichester: Wiley.

    Google Scholar 

  • Feist, G. J. (2017). Creativity in the physical sciences. In J. C. Kaufman, V. P. Glaveanu, & J. Baer (Eds.), The Cambridge handbook of creativity across domains (pp. 199–225). Cambridge: Cambridge University Press.

    Google Scholar 

  • Fox, M. F., & Milbourne, R. (1999). What determines research output of academic economists? Economic Record,75, 256–267.

    Google Scholar 

  • Goldberg, L. R. (1992). The development of markers for the big-five factor structure. Psychological Assessment,4, 26–42.

    Google Scholar 

  • Gosling, S. D., Rentfrow, P. J., & Swann, W. B., Jr. (2003). A very brief measure of the big five personality domains. Journal of Research in Personality,37(December), 504–528.

    Google Scholar 

  • Grosul, M., & Feist, G. J. (2014). The creative person in science. Psychology of Aesthetics, Creativity, and the Arts,8(1), 30–43.

    Google Scholar 

  • Hattie, J., & Marsh, H. W. (2002). The relation between research productivity and teaching effectiveness. Journal of Higher Education,73(5), 603–641.

    Google Scholar 

  • Hesli, V. L., & Lee, J. M. (2011). Why do some of our colleagues publish more than others? PS: Political Science and Politics,44(April), 393–408.

    Google Scholar 

  • Hirsch, J. E. (2005). An index to quantify an individual’s scientific research output. PNAS,102(46), 16569–16572.

    MATH  Google Scholar 

  • Hix, S. (2004). A global ranking of political science departments. Political Studies Review,2(3), 293–313.

    Google Scholar 

  • John, O. P., Naumann, L. P., & Soto, C. J. (2008). Paradigm shift to the big five trait taxonomy: History, measurement, and conceptual issues. In O. P. John, R. W. Robins, & L. A. Pervin (Eds.), Handbook of personality (pp. 114–158). New York: Guilford Press.

    Google Scholar 

  • Kaufman, S. B., Quilty, L. C., Grazioplene, R. G., Hirsh, J. B., Gray, J. R., Peterson, J. B., et al. (2016). Openness to experience and intellect differentially predict creative achievement in the arts and sciences. Journal of Personality,84(April), 248–258.

    Google Scholar 

  • King, M. M., Bergstrom, C. T., Correll, S. J., Jacquet, J., & West, J. D. (2017). Men set their own cites high: Gender and self-citation across fields and over time. Socius,3(January), 1–22.

    Google Scholar 

  • Klingemann, H., Grofman, B., & Campagna, J. (1989). The political science 400: Citations by Ph.D. cohort and by Ph.D. granting institution. PS: Political Science and Politics,22(June), 258–270.

    Google Scholar 

  • Knol, M. J., Pestman, W. R., & Grobbee, D. E. (2011). The (mis)use of overlap of confidence intervals to assess effect modification. European Journal of Epidemiology,26, 253–254.

    Google Scholar 

  • MacGregor-Fors, I., & Payton, M. E. (2013). Contrasting diversity values: Statistical inferences based on overlapping confidence intervals. PLoS ONE,8(2), e56794.

    Google Scholar 

  • Mahoney, M. J. (1979). Psychology of the scientist: An evaluative review. Social Studies of Science,9, 349–375.

    Google Scholar 

  • Maliniak, D., Powers, R., & Walter, B. F. (2013). The gender citation gap in international relations. International Organization,67(4), 889–922.

    Google Scholar 

  • Martin, B. R. (1996). The use of multiple indicators in the assessment of basic research. Scientometrics,36(3), 343–362.

    MathSciNet  Google Scholar 

  • Martín-Martín, A., Orduna-Malea, E., Thelwall, M., & López-Cózar, E. D. (2018). Google Scholar, Web of Science, and Scopus: A systematic comparison of citations in 252 subject categories. Journal of Informetrics,12(4), 1160–1177.

    Google Scholar 

  • Maske, K. L., Durden, G. C., & Gaynor, P. (2003). Determinants of scholarly productivity among male and female economists. Economic Inquiry,41, 555–564.

    Google Scholar 

  • Masuoka, N., Grofman, B., & Feld, S. L. (2007a). The political science 400: A twenty-year update. PS: Political Science and Politics,40(January), 133–145.

    Google Scholar 

  • Masuoka, N., Grofman, B., & Feld, S. L. (2007b). Ranking departments: A comparison of alternative approaches. PS: Political Science and Politics,40(July), 531–537.

    Google Scholar 

  • McCormick, J. M., & Rice, T. W. (2001). Graduate training and research productivity in the 1990s: A look at who publishes. PS: Political Science and Politics,34(September), 675–680.

    Google Scholar 

  • McCrae, R. R., & Costa, P. T., Jr. (1987). Validation of the Five-factor model of personality across instruments and observers. Journal of Personality and Social Psychology,52, 81–90.

    Google Scholar 

  • McCrae, R. R., & Costa, P. T., Jr. (2003). Personality in adulthood: A five factor theory perspective (2nd ed.). New York: Guilford Press.

    Google Scholar 

  • McDermott, R., Dawes, C., Prom-Wormley, E., Eaves, L., & Hatemi, P. K. (2013). MAOA and aggression: A gene–environment interaction in two populations. Journal of Conflict Resolution,57(6), 1043–1064.

    Google Scholar 

  • Mearsheimer, J. J., & Walt, S. M. (2013). Leaving theory behind: Why simplistic hypothesis testing is bad for International Relations. European Journal of International Relations,19(3), 427–457.

    Google Scholar 

  • Mitchell, S. M., & Hesli, V. L. (2013). Women don’t ask? Women don’t say no? Bargaining and service in the political science profession. PS: Political Science and Politics,46(2), 355–369.

    Google Scholar 

  • Oleynick, V. C., DeYoung, C. G., Hyde, E., Kaufman, S. B., Beaty, R. E., & Silva, P. J. (2017). Openness/intellect: The core of the creative personality. In G. J. Feist, R. Reiter-Palmon, & J. C. Kaufman (Eds.), The Cambridge handbook of creativity and personality research (pp. 9–27). Cambridge: Cambridge University Press.

    Google Scholar 

  • Payton, M. E., Greenstone, M. H., & Schenker, N. (2003). Overlapping confidence intervals or standard error intervals: What do they mean in terms of statistical significance? Journal of Insect Science,3, 34–39.

    Google Scholar 

  • Roberts, B. W., & Mroczek, D. (2008). Personality trait change in adulthood. Current Directions in Psychological Science, 17(January), 31–35.

    Google Scholar 

  • Roettger, W. B. (1978). Strata and stability: Reputations of American political scientists. PS: Political Science and Politics,11(Winter), 6–12.

    Google Scholar 

  • Rushton, J. P., Murray, H. G., & Paunonen, S. V. (1983). Personality, research creativity, and teaching effectiveness in university professors. Scientometrics,5(2), 93–116.

    Google Scholar 

  • Sak, U., Ayvaz, U., Bal-Sezerel, B., & Ozdemir, N. N. (2017). Creativity in the domain of mathematics. In J. C. Kaufman, V. P. Glaveanu, & J. Baer (Eds.), The Cambridge handbook of creativity across domains (pp. 276–298). Cambridge: Cambridge University Press.

    Google Scholar 

  • Simonton, D. K. (1988). Scientific genius. Cambridge: Cambridge University Press.

    Google Scholar 

  • Simonton, D. K. (2009). Varieties of (scientific) creativity: A hierarchical model of domain-specific disposition, development, and achievement. Perspectives on Psychological Science,4(5), 441–452.

    Google Scholar 

  • Simonton, D. K. (2014). Historiometric studies of genius. In D. K. Simonton (Ed.), The Wiley handbook of genius (pp. 87–106). Chichester: Wiley.

    Google Scholar 

  • Somit, Albert, & Tanenhaus, Joseph. (1964). American political science. New York: Atherton.

    Google Scholar 

  • Teele, D., & Thelen, K. (2017). Gender in the journals: Publication patterns in political science. PS: Political Science and Politics,50(2), 433–447.

    Google Scholar 

  • Weisberg, R. W. (2006). Creativity. Hoboken, NJ: Wiley.

    Google Scholar 

  • Wildavsky, A. (1989). Craftways. New Brunswick, NJ: Transaction Publishers.

    Google Scholar 

  • Witte, K. D., & Rogge, N. (2010). To publish or not to publish? On the aggregation and drivers of research performance. Scientometrics,85, 657–680.

    Google Scholar 

Download references

Funding

No grants funded this research, we have no apparent conflicts of interest, the data are not yet available (but can be in the interests of replication—contact the authors).

Author information

Author notes

  1. All authors contributed equally to this work.

Authors and Affiliations

  1. Denison University, Granville, USA

    Paul A. Djupe

  2. Texas A&M University, College Station, USA

    Kim Quaile Hill

  3. Iowa State University, Ames, USA

    Amy Erica Smith

  4. University of Colorado at Boulder, Boulder, USA

    Anand E. Sokhey

Authors
  1. Paul A. Djupe
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Kim Quaile Hill
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Amy Erica Smith
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Anand E. Sokhey
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Paul A. Djupe.

Additional information

Authors are listed in alphabetical order.

Appendix

Appendix

See Tables 2, 3, 4, 5, 6, 7 and Figs. 4, 5.

Table 2 A comparison of sample statistics from three recent surveys of political scientists†
Full size table
Table 3 Variable coding
Full size table
Table 4 Interaction between openness and conscientiousness
Full size table
Table 5 Interaction between conscientiousness and PhD granting department
Full size table
Table 6 Interaction between conscientiousness and network co-authorship
Full size table
Table 7 Negative binomial estimates of articles published in the past year with and without the personality interaction
Full size table
Fig. 4
figure 4

Source: PASS Data for Political Science, 2017

The distribution of the personality dimensions.

Full size image
Fig. 5
figure 5

Source: PASS Data for Political Science, 2017. Note: The figure shows 76% confidence intervals. Comparison of two 76% confidence intervals is equivalent to a 90% (p = .10, two-tailed) test of statistical significance at the point of overlap

The interactive effects of conscientiousness and openness are consistent across ranks.

Full size image

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Djupe, P.A., Hill, K.Q., Smith, A.E. et al. Putting personality in context: determinants of research productivity and impact in political science. Scientometrics 124, 2279–2300 (2020). https://doi.org/10.1007/s11192-020-03592-5

Download citation

  • Received:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11192-020-03592-5

Keywords

JEL Classification

Search

Navigation