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No evidence of citation bias as a determinant of STEM gender disparities in US biochemistry, genetics and molecular biology research

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  • Mike Thelwall

    (University of Wolverhampton)

  • Tamara Nevill

    (University of Wolverhampton)

Abstract

The lack of females in many Science Technology, Engineering and Mathematics (STEM) subjects in the USA is an ongoing concern, with many initiatives attempting to redress this imbalance. Some life sciences are apparently areas of relatively good practice, with higher proportions of female researchers than most other STEM subjects. This paper assesses gender differences in research contributions to 14 biochemistry, genetics or molecular biology specialisms in the USA 1996–2014/8, seeking evidence of trends in publishing and citation impact that may give insights into female success. With four exceptions (biochemistry, biophysics, biotechnology, and structural biology), the fields achieved or maintained at least 40% female first authors by 2018, with developmental biology and endocrinology both attaining female first author majorities. A regression analysis found close to gender parity overall in citation impact but a small male first author citation advantage in more fields than the opposite: an up to 3% increase in logged citation ratio to the world mean. This was partly due to males first authoring with larger teams. Fields with relatively many females did not favour female-led research with more citations, however.

Suggested Citation

  • Mike Thelwall & Tamara Nevill, 2019. "No evidence of citation bias as a determinant of STEM gender disparities in US biochemistry, genetics and molecular biology research," Scientometrics, Springer;Akadémiai Kiadó, vol. 121(3), pages 1793-1801, December.
    • Handle: RePEc:spr:scient:v:121:y:2019:i:3:d:10.1007_s11192-019-03271-0
    DOI: 10.1007/s11192-019-03271-0
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    References listed on IDEAS

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    1. Tove Faber Frandsen & Rasmus Højbjerg Jacobsen & Jakob Ousager, 2020. "Gender gaps in scientific performance: a longitudinal matching study of health sciences researchers," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(2), pages 1511-1527, August.
    2. Xiang Zheng & Jiajing Chen & Erjia Yan & Chaoqun Ni, 2023. "Gender and country biases in Wikipedia citations to scholarly publications," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 74(2), pages 219-233, February.

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