Dataset for the analysis of gendered research productivity affected by early COVID-19 pandemic

Abstract

In many countries, COVID-19 has made it harder for women to study because they are expected to do more housework and care for children. This article encompasses different data sources that can be used to figure out how the early pan-demic of COVID-19 affected the number of studies done by females, in comparison with males. This data is add-on meta -data that can be used with raw Microsoft Academic Graph (MAG) from 2016 to 2020 of the Feb 6, 2021 dump. We re-trieved open-source metadata from various sources, includ-ing LinkedIn, the Johns Hopkins Coronavirus Resource Cen-ter, and Google's COVID-19 Community Mobility Reports, and linked bibliographic information to characteristics of the au-thor's environments. It consists of published journals and on-line preprints, including each author's gender and involve-ment in the publication, their position through time, the h -index of their institutes, and gender equality in the profes-sional labor market at the country level. For each record of papers, the data also includes the information of the papers, e.g., title and field of study. By gathering this evidence, our data can support the fact diversity in science is more than just the number of active members of different groups. It should also examine minority participation in science. Our data may help scholars understand diversity in science and advance it. The article "The effect of the COVID-19 pandemic on gendered research productivity and its correlates" uses this data as the principal source (Kwon, Yun & Kang, 2021). (c) 2023 The Author(s). Published by Elsevier Inc. This is an open access article under the CC BY license ( http://creativecommons.org/licenses/by/4.0/)