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Part 1: Document Description
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Citation |
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Title: |
Replication Data for: "The Gendered Division of Labor in Brazilian Political Science Journals" |
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Identification Number: |
doi:10.7910/DVN/O1SJV5 |
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Distributor: |
Harvard Dataverse |
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Date of Distribution: |
2021-06-16 |
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Version: |
1 |
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Bibliographic Citation: |
Candido, Marcia Rangel; Campos, Luiz Augusto; Feres, João, 2021, "Replication Data for: "The Gendered Division of Labor in Brazilian Political Science Journals"", https://doi.org/10.7910/DVN/O1SJV5, Harvard Dataverse, V1, UNF:6:EAXXK0LLWisty19Dp5PD7g== [fileUNF] |
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Citation |
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Title: |
Replication Data for: "The Gendered Division of Labor in Brazilian Political Science Journals" |
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Identification Number: |
doi:10.7910/DVN/O1SJV5 |
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Authoring Entity: |
Candido, Marcia Rangel (Universidade do Estado do Rio de Janeiro, Institute of Social and Political Studies, Rio de Janeiro/RJ, Brazil) |
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Campos, Luiz Augusto (Universidade do Estado do Rio de Janeiro, Institute of Social and Political Studies, Rio de Janeiro/RJ, Brazil) |
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Feres, João (Universidade do Estado do Rio de Janeiro, Institute of Social and Political Studies, Rio de Janeiro/RJ, Brazil) |
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Distributor: |
Harvard Dataverse |
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Access Authority: |
Candido, Marcia Rangel |
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Depositor: |
Martins, Debora |
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Date of Deposit: |
2021-05-25 |
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Holdings Information: |
https://doi.org/10.7910/DVN/O1SJV5 |
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Study Scope |
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Keywords: |
Social Sciences, Political science, gendered division of labor, topics in political science, inequalities, journals |
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Abstract: |
This article analyzes the gendered division of labor in Brazilian political science. We seek to answer two questions: what are the predominant topics in political science that are being published in the discipline’s journals? How are women and men’s authorship distributed in these journals? The methodology involved three stages. First, we built a corpus with 2,363 articles that were classified as ‘political science and international relations’ by the Coordination for the Improvement for Higher Education Personnel (Coordenação de Aperfeiçoamento de Pessoal de Nível Superior – CAPES) and published in the most prominent Brazilian journals between 2005 and 2018. Next, we scraped abstracts and other bibliographic information from publications in the Scientific Electronic Library Online (SciELO) platform and used a topic modeling technique to identify the most recurrent topics. Finally, we associated the identified topics with the authors’ gender. The data was examined based on two specific types of the gendered division of labor: the ‘horizontal’ and the ‘vertical’. Our results show that women and men as first authors tend to cluster around specific topics (horizontal division), but we did not find a tendency in journals to reject works on the topics in which women are better represented. In other words, differently from what was found by the international literature, the Brazilian journals in our sample do not seem to grant a lower status to these topics (vertical division). It is noteworthy, however, that men are the majority of first authors in all topics, including feminism. |
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Methodology and Processing |
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Sources Statement |
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Data Access |
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Notes: |
<a href="http://creativecommons.org/publicdomain/zero/1.0">CC0 1.0</a> |
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Other Study Description Materials |
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Related Publications |
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Citation |
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Title: |
Braz. political sci. rev.2021;15(3):e0002 |
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Identification Number: |
10.1590/1981-3821202100030002 |
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Bibliographic Citation: |
Braz. political sci. rev.2021;15(3):e0002 |
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File Description--f4745914 |
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File: 2020-0025_graficos.tab |
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Notes: |
UNF:6:yA1rwHn9PU7MlKvLvdhxqw== |
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File Description--f4745902 |
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File: base_Scielo_CP_2005-2018.tab |
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Notes: |
UNF:6:jzbOtyySXK7JAe7ByZKSYQ== |
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File Description--f4745916 |
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File: base_Scielo_CP_2005-2018_Topicos.tab |
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Notes: |
UNF:6:yA1rwHn9PU7MlKvLvdhxqw== |
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File Description--f4745911 |
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File: output_20termsToTopicos.tab |
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Notes: |
UNF:6:KVcmzWsuudXkDCsd35F9+A== |
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File Description--f4745900 |
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File: sem_genero-edit m.tab |
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Notes: |
UNF:6:7MYqc9QPePBTzy/HpGT+7g== |
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Variables |
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Summary Statistics: Valid 2363.0; Min. 300.0; Max. 3067.0; Mean 922.2738044858238; StDev 428.96031085021866 Variable Format: numeric Notes: UNF:6:dI3rFjzWcJaHDBVgtRC3EQ== |
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Summary Statistics: Max. 3067.0; Min. 300.0; StDev 428.96031085021866; Mean 922.2738044858238; Valid 2363.0; Variable Format: numeric Notes: UNF:6:dI3rFjzWcJaHDBVgtRC3EQ== |
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Summary Statistics: Max. 15.0; StDev 4.4955415366545; Mean 7.393144308083032; Valid 2363.0; Min. 1.0; Variable Format: numeric Notes: UNF:6:BlfHbHw48D7hFd69WP74Fg== |
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Summary Statistics: Min. 304.0; Valid 55.0; Mean 843.690909090909; StDev 393.85388683505994; Max. 1825.0; Variable Format: numeric Notes: UNF:6:nyCLvmu+hfjCGy34+lSSqg== |
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Label: |
.RData |
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Notes: |
application/x-rlang-transport |
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Label: |
base_Scielo_CP_2005-2018_Resumos.csv |
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Notes: |
text/csv |
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Label: |
output_DocsToTopics.csv |
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Notes: |
text/csv |
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Label: |
output_RplotKdeTopicos.pdf |
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Notes: |
application/pdf |
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Label: |
output_TopicProbs.csv |
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Notes: |
text/csv |
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Label: |
README.txt |
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Notes: |
text/plain |
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Label: |
script_CamposModelagemTopicos.R |
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Notes: |
type/x-r-syntax |