Female Representation in Retracted Scientific Publications: A Study of Authorship and Collaboration

Authors

  • Kiran Sharma [1]Schools of Engineering and Technology, BML Munjal University, Gurugram, Haryana, INDIA. and [2]Center for Advanced Data and Computational Science, BML Munjal University, Gurugram, Haryana, INDIA.
  • Satyam Mukherjee School of Management and Entrepreneurship, Shiv Nadar University, Greater Noida, Uttar Pradesh, INDIA.
  • Harsha V. Garine Charles W. Davidson College of Engineering, San Jose State University, California, UNITED STATES.

DOI:

https://doi.org/10.5530/jcitation.20250143

Keywords:

Female Authorship, Gender Disparity, Male-Female Collaboration, Retraction

Abstract

Numerous studies in the literature have emphasized the underrepresentation of women in the scientific field, leading to their underrepresentation in prestigious publications, authorship roles, and collaborations. At the same time, the involvement of women in scientific misconduct is also increasingly attracting the attention of the scientific community. This motivated the present study to explore female collaboration and authorship positions in retracted publications. To conduct the analysis, 3750 retracted scientific papers were extracted from the Web of Science, and the respective gender of each author was identified. The evaluation included the year-wise representation of female authors, females at various authorship positions, collaboration, and female-to-male odds ratio. In all, 26.43% of authorship is held by women, and the share of male-female collaborative retracted publications is 55.11%. To conclude, women are less likely to hold the last authorship and more likely to hold the middle authorship position in retracted publications

The Flowchart Represents the Data Selection, Filtration and Gender Estimation Process.

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Published

2025-04-24

How to Cite

Sharma, K., Mukherjee, S. ., & Garine, H. V. . (2025). Female Representation in Retracted Scientific Publications: A Study of Authorship and Collaboration. Journal of Data Science, Informetrics, and Citation Studies, 4(1), 103–106. https://doi.org/10.5530/jcitation.20250143