Authors : Bedoor K AlShebli, Talal Rahwan, Wei Lee Woon
Inspired by the numerous social and economic benefits of diversity, we analyze over 9 million papers and 6 million scientists spanning 24 fields of study, to understand the relationship between research impact and five types of diversity, reflecting (i) ethnicity, (ii) discipline, (iii) gender, (iv) affiliation and (v) academic age.
For each type, we study group diversity (i.e., the heterogeneity of a paper’s set of authors) and individual diversity (i.e., the heterogeneity of a scientist’s entire set of collaborators). Remarkably, of all the types considered, we find that ethnic diversity is the strongest predictor of a field’s scientific impact (r is 0.77 and 0.55 for group and individual ethnic diversity, respectively).
Moreover, to isolate the effect of ethnic diversity from other confounding factors, we analyze a baseline model in which author ethnicities are randomized while preserving all other characteristics.
We find that the relation between ethnic diversity and impact is stronger in the real data compared to the randomized baseline model, regardless of publication year, number of authors per paper, and number of collaborators per scientist.
Finally, we use coarsened exact matching to infer causality, whereby the scientific impact of diverse papers and scientists are compared against closely matched control groups. In keeping with the other results, we find that ethnic diversity consistently leads to higher scientific impact.