Archives des mots-clés : Talal Rahwan

Gender inequality and self-publication are common among academic editors

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Authors : Fengyuan Liu, Petter Holme, Matteo Chiesa, Bedoor AlShebli, Talal Rahwan

Scientific editors shape the content of academic journals and set standards for their fields. Yet, the degree to which the gender makeup of editors reflects that of scientists, and the rate at which editors publish in their own journals, are not entirely understood.

Here, we use algorithmic tools to infer the gender of 81,000 editors serving more than 1,000 journals and 15 disciplines over five decades. Only 26% of authors in our dataset are women, and we find even fewer women among editors (14%) and editors-in-chief (8%).

Career length explains the gender gap among editors, but not editors-in-chief. Moreover, by analysing the publication records of 20,000 editors, we find that 12% publish at least one-fifth, and 6% publish at least one-third, of their papers in the journal they edit.

Editors-in-chief tend to self-publish at a higher rate. Finally, compared with women, men have a higher increase in the rate at which they publish in a journal soon after becoming its editor.

URL : Gender inequality and self-publication are common among academic editors

DOI : https://doi.org/10.1038/s41562-022-01498-1

Ethnic Diversity Increases Scientific Impact

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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.

URL : https://arxiv.org/abs/1803.02282