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

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 pandemic of COVID-19 affected the number of studies done by females, in...

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Main Authors: Eunrang Kwon, Jinhyuk Yun, Jeong-han Kang
Format: Article
Language:English
Published: Elsevier 2023-06-01
Series:Data in Brief
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S2352340923003190
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author Eunrang Kwon
Jinhyuk Yun
Jeong-han Kang
author_facet Eunrang Kwon
Jinhyuk Yun
Jeong-han Kang
author_sort Eunrang Kwon
collection DOAJ
description 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 pandemic of COVID-19 affected the number of studies done by females, in comparison with males. This data is add-on metadata that can be used with raw Microsoft Academic Graph (MAG) from 2016 to 2020 of the Feb 6, 2021 dump. We retrieved open-source metadata from various sources, including LinkedIn, the Johns Hopkins Coronavirus Resource Center, and Google's COVID-19 Community Mobility Reports, and linked bibliographic information to characteristics of the author's environments. It consists of published journals and online preprints, including each author's gender and involvement in the publication, their position through time, the h-index of their institutes, and gender equality in the professional 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).
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spelling doaj.art-9e98c8ef6ee84723b2467a95c767d8102023-06-22T05:03:57ZengElsevierData in Brief2352-34092023-06-0148109200Dataset for the analysis of gendered research productivity affected by early COVID-19 pandemicEunrang Kwon0Jinhyuk Yun1Jeong-han Kang2Department of Sociology, Yonsei University, 50, Yonsei-ro, Seodaemun-gu, Seoul, 03722, (South Korea)School of AI Convergence, Soongsil University, 369, Sangdo-ro, Dongjak-gu, Seoul, 06978, (South Korea); Corresponding authors.Department of Sociology, Yonsei University, 50, Yonsei-ro, Seodaemun-gu, Seoul, 03722, (South Korea); Corresponding authors.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 pandemic of COVID-19 affected the number of studies done by females, in comparison with males. This data is add-on metadata that can be used with raw Microsoft Academic Graph (MAG) from 2016 to 2020 of the Feb 6, 2021 dump. We retrieved open-source metadata from various sources, including LinkedIn, the Johns Hopkins Coronavirus Resource Center, and Google's COVID-19 Community Mobility Reports, and linked bibliographic information to characteristics of the author's environments. It consists of published journals and online preprints, including each author's gender and involvement in the publication, their position through time, the h-index of their institutes, and gender equality in the professional 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).http://www.sciencedirect.com/science/article/pii/S2352340923003190COVID-19Gender inequalityResearch productivityCareerChildcareMicrosoft academic graph
spellingShingle Eunrang Kwon
Jinhyuk Yun
Jeong-han Kang
Dataset for the analysis of gendered research productivity affected by early COVID-19 pandemic
Data in Brief
COVID-19
Gender inequality
Research productivity
Career
Childcare
Microsoft academic graph
title Dataset for the analysis of gendered research productivity affected by early COVID-19 pandemic
title_full Dataset for the analysis of gendered research productivity affected by early COVID-19 pandemic
title_fullStr Dataset for the analysis of gendered research productivity affected by early COVID-19 pandemic
title_full_unstemmed Dataset for the analysis of gendered research productivity affected by early COVID-19 pandemic
title_short Dataset for the analysis of gendered research productivity affected by early COVID-19 pandemic
title_sort dataset for the analysis of gendered research productivity affected by early covid 19 pandemic
topic COVID-19
Gender inequality
Research productivity
Career
Childcare
Microsoft academic graph
url http://www.sciencedirect.com/science/article/pii/S2352340923003190
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