Profile of women's orientations and productions based on data from the Lattes Platform

Authors

  • Monique de Oliveira Santiago Cefet-MG
  • Thiago Magela Rodrigues Dias Cefet-MG
  • Felipe Affonso

DOI:

https://doi.org/10.18225/ci.inf.v49i3.5469

Keywords:

Women in science. Bibliometry. Scientific and technological production. Feminine gender

Abstract

The theme of women in science has been the focus of several studies that seek to understand the role of women and their varied relations with science, bringing approaches that analyze scientific and technological participation and seek to understand their academic trajectory in science. In this context, this paper aimed to analyze the participation of women using as a database the set of PhDs who have curricula registered in the Lattes Platform and whose gender registered in their curriculum is female. After completing the stage of data collection, a set of 125,515 registered curricula with female gender and maximum completed doctorate degree was obtained, distributed in the various areas of scientific knowledge. The data of the female PhDs were grouped as to orientations and bibliographic and technical productions, in which it was possible to analyze the evolution of the scientific and technological production of the set in a temporal way. Studying the various aspects of women in general and particularly in science, in addition to being relevant, presents a characterization of their research, which can contribute to the generation of national scientific indicators and the management of information in the scientific and technological area, as well as supporting the formulation of policies and strategies that enhance the performance of women in academic environments.

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Author Biographies

  • Monique de Oliveira Santiago, Cefet-MG

    Mestranda em Modelagem Matemática e Computacional pelo Centro Federal de Educação Tecnológica de Minas Gerais (CEFET-MG) - Belo Horizonte, MG - Brasil. Especialização em Análise de Dados com BI e Big Data pela Universidade Cruzeiro do Sul (UNICSUL) - Brasil.  Professora da Universidade do Estado de Minas Gerais (UEMG) - Brasil.

  • Thiago Magela Rodrigues Dias, Cefet-MG

    Doutor em Modelagem Matemática e Computacional pela Centro Federal de Educação Tecnológica de Minas Gerais (CEFET-MG), Belo Horizonte, Minas Gerais, Brasil. Professor do Centro Federal de Educação Tecnológica de Minas Gerais (CEFET-MG) - Belo Horizonte, MG - Brasil.

  • Felipe Affonso

    Mestrando em Modelagem Matemática e Computacional pelo Centro Federal de Educação Tecnológica de Minas Gerais (CEFET-MG) - Belo Horizonte, MG - Brasil. Graduação em Engenharia da Computação pela Universidade do Estado de Minas Gerais (UEMG) – Brasil, com período sanduíche em University of Miami (Umiami) - Estados Unidos.

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Published

25/11/2020

Issue

Vol. 49 No. 3 (2020): Data Science in Information Science

Section

Articles

License

Copyright (c) 2020 Monique de Oliveira Santiago, Thiago Magela Rodrigues Dias

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This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

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