Resources and Insights about Gender Diversity in (R&D) Teams

An increasing amount of work in science, research and development happens collaboratively. The trend towards collective efforts in knowledge production is clearly visible by looking at the rise of co-authored papers over the last decades (Wuchty, Jones, & Uzzi, 2007)⁠.  However, to which degree gender diversity affects these research collaborations is an open question currently addressed in Europe (the H2020 project GEDII) or planned to be addressed in the US (Valantine & Collins, 2015). 

Naturally, the research productivity, quality and innovation of research and development teams are affected by many different factors besides the gender composition of their groups. Team size, the history of previous collaborations, or the tenure of team members all contribute to different degrees to the research performance. There is an extremely rich research tradition that spans prominently the management-, social psychology-, small group-, and diversity- literature. From what we know, there is some evidence that gender diversity affects team outcomes.

The evidence is mixed!

Thus, in a paper published in 2010 in Science, Anita Woolley and co-authors argued that  the “collective intelligence” factor of human groups correlates with the proportion of women in the group (Woolley, Chabris, Pentland, Hashmi, & Malone, 2010)⁠. As Woolley and co-authors argue, the collective intelligence of the group depends less on the sum of individual IQs of group members but rather how well the group manages to voice and integrate the perspectives of all its participants. Groups with a more balanced distribution of “on-air” time outperformed those working groups where few (mostly male) individuals dominated the conversation.

There is some evidence that gender-heterogeneous teams produce  higher quality publications. As the study by Campbell et al. (2013)  argues, peer-reviewed publications with gender-heterogeneous authorship teams received 34% more citations than publications produced by gender-uniform authorship teams working at the US based National Center for Ecological Analysis and Synthesis. Gender diversity has been found to correlate further with “radicalness” of innovation (Díaz-García, González-Moreno, & Sáez-Martínez, 2013)⁠ or to have a higher innovation potential (Østergaard, Timmermans, & Kristinsson, 2011; The Lehman Brothers Centre for Women in Business, 2007)⁠. However, as others have shown, the results are not consistent (Bowers, Pharmer, & Salas, 2000; Mannix & Sauer, 2006; Shore et al., 2009; van Knippenberg & Schippers, 2007; Webber & Donahue, 2001; Williams & O’Reilly, 1998)⁠. This suggests that any straight forward explorations regarding “direct diversity-performance relationships seems to have been laid to rest” (Haas, 2010).

Examining more closely how gender diversity affects research teams, several factors need to be considered (see for example also Bear & Woolley, 2011)⁠. The basic dialectic underlying much thinking about diversity in work groups stipulates that diverse groups might hamper performance due to increased costs of coordination and negotiation between highly different members. Heterogeneous groups on the other hand might outperform their more homogeneous counterparts due to the more varied (information) resources and better quality decision making available (van Knippenberg & Schippers, 2007)⁠. In order for research teams to perform “well”, they have to have access to diverse resources (ideas, non-redundant information) and be able to integrate and process those resources within the existing confinements of their team and organization.  Importantly, it has been recognized that the organizational diversity and gender equality policy plays an important part not just in recruiting a more diverse workforce but also in enabling employees to recognize diversity and take advantage of it (Hentschel, Shemla, Wegge, & Kearney, 2013)⁠.

How does gender diversity affect teams?

First, a crucial contribution for understanding how gender affects team work is available through the work of Cecilia Ridgeway on “expectation-states theory”  (Ridgeway & Smith-Lovin, 1999; Ridgeway, 2007, 2011). In a nutshell, expectation-states theory explains how differences in status based on gender affect group processes negatively. Gender stereotypes have diffuse general status beliefs attached to them – men are seen as more agentic and competent than women. Women appear as less competent, but better in care giving and communal tasks, although these tasks are less valued (Fiske, Cuddy, Glick, & Xu, 2002; Glick et al., 2004)⁠. Thus, being white and a man is associated with a higher status than being a woman or belonging to a minority (DiTomaso, Post, Smith, Farris, & Cordero, 2007 ); Haines, Deaux, & Lofaro, 2016⁠. Now, “the theory implies that compared with those lower in status, high-status actors are  granted more (and take more) action opportunities, make more task contributions (performance outputs), have their contributions evaluated more positively, and exercise more influence.” (Simpson, Willer, & Ridgeway, 2012, p. 154)⁠. Gendered status beliefs are in danger of introducing systematic bias to research groups because it is not necessarily those that have the most relevant knowledge that speak up for a given task, but those that have the highest status.

The degree to which differential status beliefs  influence the task at hand depends on contextual factors. Gendered competency expectations are stronger for tasks that are equally strongly gender typed such as childcare, the military, nursing, or engineering. For R&D teams this can be readily seen in relation to the disciplinary context: in disciplines that are more gender stereotyped and where women are underrepresented, the expertise of women is less recognized than in disciplines where the proportion of women and men is more balanced (Joshi, 2014)⁠.

Second, a consequence of the previously mentioned research by Woolley and colleagues is, that differences in terms of “social sensitivity” between women and men affect group processes in important ways. Social sensitivity or “social perceptiveness” captures individuals' ability to attribute mental states such as goals and beliefs, intentions, desires to others as different from one's own mental states. Women score better on the “Reading the Mind in the Eyes” test and hence perform better when it comes to recognize others nonverbal emotional expressions and mental states (Woolley, Aggarwal, & Malone, 2015)⁠. Since these “other-directed” social skills are at the foundation for establishing a health collaboration climate, teams with a higher proportion of women are better positioned to establish an environment where diverse perspectives can be voiced and integrated. Along these lines and based on research on sex differences for affective empathy between women and men (Christov-Moore et al., 2014)⁠, others have stressed the importance of “empathy” to understand the impact of diversity on group performance (Roberge, 2013). Those social skills are important to build up a climate of “trust” and “psychological safety” - two factors that favor prominently in much of the literature on small groups and team performance. Again, the basic rationale is that team members need to feel safe and trust each other in order to speak up and share their sometimes risky, innovative ideas.

Third, quite a bit of research has documented the effects of “homophily” in science in terms of disadvantages for women's careers (Ibarra, 1992, 1993; Kanter, 1977)⁠. Recent research on “deference” in teams has come to parallel conclusions, showing how “social affinity” ties among team members affects team performance. Advice seeking in teams is not necessarily oriented to those with the best expertise but also influenced by the social bonds among team members - which can introduce bias in the form of “group think” for example. Very specifically, social affinity ties based on  educational level,  ethnicity and gender influences who defers to whom with detrimental consequences for performance: “Teams that rely on task-based deference perform better than those that rely on social affinity-based deference” (Joshi & Knight, 2015, p. 79)⁠.  

Taking together these three points suggests already a more complex picture on gender diversity in research teams.  Homophily but also gendered status beliefs and power relations in general can bias the information sharing in groups, silencing important diverging and “fresh” perspectives in favor of the established status quo. At the same time, the proportion of women in groups can favor a more participative and “safe” team climate that precisely allows for the emergence of more innovative ideas. Which element becomes more influential depends probably many times on other contextual factors such as the shared history of group members or the precise moment a team finds itself in a project or development cycle.

Assessing the impact of gender diversity on research teams is definitely not as straight forward as establishing the proportion of women and men in the group. The whole situation is much more complex without even having touched upon the question research assessment, i.e. excellence! Standard bibliometric indicators are available such as publication count or citation impact, but to which degree are these themselves gendered or prone to gender bias? How do impact measures change when other performance indicators such as “altmetrics” or the “care” for future generations of scientists are considered? What more, there is certainly a need to critically reflect upon the very quest for “performance” itself which seems to be at odds with a feminist ethics of care: the acceleration and marketization of scientific production  in the neoliberal university runs counter to the space of genuine engagement with knowledge and the care with students (Mountz et al., 2015). After all, what innovation and creativity requires is less events driven by planned clock time than events driven by serendipity and opportune moments, i.e. less chronos and more kairos (Garud, Gehman, & Kumaraswamy, 2011).

The question regarding gender diversity in research teams thus provides an exciting window upon contemporary processes in science itself: how can the quality of science with and for society be assessed with and beyond the “metric tide”? How is scientific production and collaboration changing – and persistently gendered? How is gender inequality continuously enacted through status beliefs and competency expectations?  Examining “teams” from a gender perspective provides  an exciting opportunity to revisit results from research on work groups, gendered organizations and interaction in the light of contemporary processes of gendered knowledge production.

Note: many resources related to team science can be found at the US National Cancer Institute's website on the Team Science Toolkit. A good starting point furthermore is the Science of Team Science group on Mendeley.

 

References

Bear, J. B., & Woolley, A. W. (2011). The role of gender in team collaboration and performanceInterdisciplinary Science Reviews36(2), 146–153. http://doi.org/10.1179/030801811X13013181961473 

Bowers, C. A., Pharmer, J. A., & Salas, E. (2000). When Member Homogeneity is Needed in Work Teams: A Meta-AnalysisSmall Group Research31(3), 305–327. http://doi.org/10.1177/104649640003100303

Campbell, L. G., Mehtani, S., Dozier, M. E., & Rinehart, J. (2013). Gender-heterogeneous working groups produce higher quality science. PloS One8(10), e79147. http://doi.org/10.1371/journal.pone.0079147

Christov-Moore, L., Simpson, E. A., Coudé, G., Grigaityte, K., Iacoboni, M., & Ferrari, P. F. (2014). Empathy: gender effects in brain and behaviorNeuroscience and Biobehavioral Reviews46 Pt 4(P4), 604–27. http://doi.org/10.1016/j.neubiorev.2014.09.001

Díaz-García, C., González-Moreno, A., & Sáez-Martínez, F. J. (2013). Gender diversity within R&D teams: Its impact on radicalness of innovationInnovation: Management, Policy & Practice15(2), 149–160. http://doi.org/10.5172/impp.2013.15.2.149

DiTomaso, N., Post, C., Smith, D. R., Farris, G. F., & Cordero, R. (2007). Effects of Structural Position on Allocation and Evaluation Decisions for Scientists and Engineers in Industrial R&DAdministrative Science Quarterly52(2), 175–207. http://doi.org/10.2189/asqu.52.2.175

Fiske, S. T., Cuddy, A. J. C., Glick, P., & Xu, J. (2002). A model of (often mixed) stereotype content: competence and warmth respectively follow from perceived status and competitionJournal of Personality and Social Psychology82(6), 878–902.

Garud, R., Gehman, J., & Kumaraswamy, A. (2011). Complexity Arrangements for Sustained Innovation: Lessons from 3M CorporationOrganization Studies32(6), 737–767. http://doi.org/10.1177/0170840611410810 http://www.genderportal.eu/resources/complexity-arrangements-sustained-i...

Glick, P., Lameiras, M., Fiske, S. T., Eckes, T., Masser, B., Volpato, C., … Wells, R. (2004). Bad but bold: Ambivalent attitudes toward men predict gender inequality in 16 nations. Journal of Personality and Social Psychology86(5), 713–28. http://doi.org/10.1037/0022-3514.86.5.713

Haas, H. (2010). How can we explain mixed effects of diversity on team performance? A review with emphasis on context. Equality, Diversity and Inclusion: An International Journal29(5), 458–490. http://doi.org/10.1108/02610151011052771

Haines, E. L., Deaux, K., & Lofaro, N. (2016). The Times They Are a-Changing ... or Are They Not? A Comparison of Gender Stereotypes, 1983-2014. Psychology of Women Quarterly, 0361684316634081–. http://doi.org/10.1177/0361684316634081

Hentschel, T., Shemla, M., Wegge, J., & Kearney, E. (2013). Perceived Diversity and Team Functioning: The Role of Diversity Beliefs and Affect. Small Group Research44(1), 33–61. http://doi.org/10.1177/1046496412470725

Ibarra, H. (1992). Homophily and Differential Returns: Sex Differences in Network Structure and Access in an Advertising FirmAdministrative Science Quarterly37(3), 422–447.

Ibarra, H. (1993). Personal Networks of Women and Minorities in Management: a Conceptual Framework. Academy of Management Review18(1), 56–87. http://doi.org/10.5465/AMR.1993.3997507

Joshi, A. (2014). By Whom and When Is Women’s Expertise Recognized? The Interactive Effects of Gender and Education in Science and Engineering Teams. Administrative Science Quarterly59(2), 202–239. http://doi.org/10.1177/0001839214528331

Joshi, A., & Knight, A. P. (2015). Who Defers to Whom and Why? Dual Pathways Linking Demographic Differences and Dyadic Deference to Team EffectivenessAcademy of Management Journal58(1), 59–84. http://doi.org/10.5465/amj.2013.0718

Kanter, R. (1977). Men and women of the corporation. New York: Basic Books. http://www.genderportal.eu/resources/men-and-women-corporation     ...

Mannix, E. A., & Sauer, S. J. (2006). Status and Power in Organizational Group Research: Acknowledging the Pervasiveness of Hierarchy. Advances in Group Processes23, 149–182. http://doi.org/10.1016/S0882-6145(06)23006-6

Mountz, A., Bonds, A., Mansfield, B., Loyd, J., Hyndman, J., Walton-Roberts, M., … Curran, W. (2015, August 18). For Slow Scholarship: A Feminist Politics of Resistance through Collective Action in the Neoliberal UniversityACME: An International E-Journal for Critical Geographies.

http://www.genderportal.eu/resources/slow-scholarship-feminist-politics-...

Østergaard, C. R., Timmermans, B., & Kristinsson, K. (2011). Does a different view create something new? The effect of employee diversity on innovationResearch Policy40(3), 500–509. http://doi.org/10.1016/j.respol.2010.11.004 

Ridgeway, C. L. (2007). Gender as a Group Process: Implications for the Persistence of Inequality. In S. J. Correll (Ed.), Social Psychology of Gender (Vol. 24, pp. 311–333). Bingley: Emerald Group Publishing Limited. http://www.genderportal.eu/resources/gender-group-process-implications-p...

Ridgeway, C. L. (2011). Framed by Gender. How Gender Inequality Persists in the Modern World. New York: Oxford University Press. http://www.genderportal.eu/resources/framed-gender-how-gender-inequality...

Ridgeway, C. L., & Smith-Lovin, L. (1999). The Gender System and InteractionAnnual Review of Sociology25(1), 191–216. http://doi.org/10.1146/annurev.soc.25.1.191 

Roberge, M.-É. (2013). A Multi-Level Conceptualization of Empathy to Explain How Diversity Increases Group Performance. International Journal of Business and Management8(3), p122. http://doi.org/10.5539/ijbm.v8n3p122

http://www.genderportal.eu/resources/multi-level-conceptualization-empat...

Shore, L. M., Chung-Herrera, B. G., Dean, M. a., Ehrhart, K. H., Jung, D. I., Randel, A. E., & Singh, G. (2009). Diversity in organizations: Where are we now and where are we going? Human Resource Management Review19(2), 117–133. http://doi.org/10.1016/j.hrmr.2008.10.004

Simpson, B., Willer, R., & Ridgeway, C. L. (2012). Status Hierarchies and the Organization of Collective Action. Sociological Theory30(3), 149–166. http://doi.org/10.1177/0735275112457912

Singer, T. (2006). The neuronal basis and ontogeny of empathy and mind reading: review of literature and implications for future research. Neuroscience and Biobehavioral Reviews30(6), 855–63. http://doi.org/10.1016/j.neubiorev.2006.06.011

The Lehman Brothers Centre for Women in Business. (2007). Innovative Potential : Men and Women in TeamsWomen in Business

Valantine, H. A., & Collins, F. S. (2015). National Institutes of Health addresses the science of diversityProceedings of the National Academy of Sciences of the United States of America112(40), 12240–2. http://doi.org/10.1073/pnas.1515612112

http://www.genderportal.eu/resources/national-institutes-health-addresse...

van Knippenberg, D., & Schippers, M. C. (2007). Work group diversity. Annual Review of Psychology58, 515–41. http://doi.org/10.1146/annurev.psych.58.110405.085546

Webber, S. S., & Donahue, L. M. (2001). Impact of highly and less job-related diversity on work group cohesion and performance: a meta-analysis. Journal of Management27(2), 141–162. http://doi.org/10.1177/014920630102700202

Williams, K. Y., & O’Reilly, C. A. (1998). Demography and diversity in organizations: A review of 40 years of research. In B. M. Staw & L. L. Cummings (Eds.), Research In Organizational Behavior (Vol. 20, pp. 77–140). JAI Press.

Woolley, A. W., Chabris, C. F., Pentland, A., Hashmi, N., & Malone, T. W. (2010). Evidence for a Collective Intelligence Factor in the Performance of Human GroupsScience330(October), 686–688.

Wuchty, S., Jones, B. F., & Uzzi, B. (2007). The increasing dominance of teams in production of knowledge. Science (New York, N.Y.)316(5827), 1036–9. http://doi.org/10.1126/science.1136099

 

Blog Category: 

Share this post