Beyond a number game: Flat team structures improve inclusion and performance in diverse scientific teams

Abstract

The promises and perils about scientific team diversity are still debated in the scholarly literature, partly because the importance of underrepresented groups is not fully recognized or valued. In this paper, we summarize two perspectives on team diversity in science: horizontal differences and vertical disparity. Horizontal differences refer to variations across individuals on equal levels, such as differences in gender, nationality, and occupation. Vertical disparity reflects broader social and structural inequalities that limit historically marginalized groups. We introduce team hierarchy, defined as the distribution of power and influence among team members, as a moderating mechanism that helps explain the mixed findings surrounding team diversity and performance. Understanding how hierarchical structures shape diversity is not only important to maximize the benefits of diverse teams but also for enhancing the representation and impact of underrepresented voices. By analyzing 64,038 papers from PloS One and 75,260,139 teams from Microsoft Academic Graph (MAG), our comprehensive study underscores the critical role of team hierarchy in significantly affecting team performance. We also investigate how team hierarchy interacts with team diversity along three dimensions: authors' gender, sector, and country. Interestingly, we find that flat team structures are more positively associated with performance in diverse teams than in homogeneous teams, where members share similar identities. This effect is particularly strong in science compared to social science & arts disciplines. Drawing from social identity and social dominance theories, we propose that flat team structures foster conditions for diverse teams to flourish, enabling minority groups to assume significant roles and wield influential power. Our study contributes valuable insights into team diversity within the scientific community, emphasizing the significance of meaningful inclusion beyond mere numerical representation.