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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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Detalles Bibliográficos
Autores principales: Kwon, Eunrang, Yun, Jinhyuk, Kang, Jeong-han
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10156633/
https://www.ncbi.nlm.nih.gov/pubmed/37162803
http://dx.doi.org/10.1016/j.dib.2023.109200
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author Kwon, Eunrang
Yun, Jinhyuk
Kang, Jeong-han
author_facet Kwon, Eunrang
Yun, Jinhyuk
Kang, Jeong-han
author_sort Kwon, Eunrang
collection PubMed
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 pubmed-101566332023-05-04 Dataset for the analysis of gendered research productivity affected by early COVID-19 pandemic Kwon, Eunrang Yun, Jinhyuk Kang, Jeong-han Data Brief Data Article 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). Elsevier 2023-05-04 /pmc/articles/PMC10156633/ /pubmed/37162803 http://dx.doi.org/10.1016/j.dib.2023.109200 Text en © 2023 The Author(s) https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Data Article
Kwon, Eunrang
Yun, Jinhyuk
Kang, Jeong-han
Dataset for the analysis of gendered research productivity affected by early COVID-19 pandemic
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 Data Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10156633/
https://www.ncbi.nlm.nih.gov/pubmed/37162803
http://dx.doi.org/10.1016/j.dib.2023.109200
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