Improving diversity and inclusivity in scientific publishing: can ‘editormetrics’ help?
Membership on a journal’s editorial board can translate into meaningful career growth and confer prestige for researchers. However, journal editors must make judgement calls that may, at times, be unintentionally biased.
To enable insights into the editorial composition of journals and the potential biases influencing editorial decisions, Andreas Pacher, Tamara Heck, and Kerstin Schoch have created Open Editors, a dataset containing public information on nearly half a million journal editors across 6,833 journals run by 22 academic publishers. For each editor or editorial board member, the following data—or ‘editormetrics’—are collected:
- institutional affiliation
- editorial position
- journal name
- URL linking to the journal’s editorial board information
- date of data collection (‘web-scraping’).
The initiative, first outlined in a SocArXiv preprint article in March 2021, has received support from researchers, who believe that it will improve transparency around decision-making in scientific publishing. For instance, it could shed light on gender bias among editorial boards, encouraging publishers to improve equity within these groups. The database could also make it easier to verify key facts such as the editors’ authentic affiliation with the journal, to help identify predatory journals. Aligned with industry efforts toward greater open science, Open Editors is freely available and will be updated annually through at least 2023.
The authors note that “editormetric analyses aim to detect biases and inequalities that are sustained by editorial power within the scientific publication system”.
Pacher and colleagues suggest that the editormetrics they have collected would be even more valuable, and inform on more aspects of diversity, when linked with other datasets. We look forward to seeing how researchers use Open Editors and how these analyses help to improve equity in scientific publishing.
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