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Research production in high-impact journals of contemporary neuroscience: A gender analysis

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  • González-Álvarez, Julio
  • Cervera-Crespo, Teresa

Abstract

Neuroscience or Neural Science is a very active and interdisciplinary field that seeks to understand the brain and the nervous system. In spite of important advances made in recent decades, women are still underrepresented in neuroscience research output as a consequence of gender inequality in science overall. This study carries out a scientometric analysis of the 30 neuroscience journals (2009–2010) with the highest impact in the Web of Science database (Thomson Reuters) in order to quantitatively examine the current contribution of women in neuroscientific production, their pattern of research collaboration, scientific content, and the analysis of scientific impact from a gender perspective. From a total of 66,937 authorships, gender could be identified in 53,351 (79.7%) of them. Results revealed that 67.1% of the authorships corresponded to men and 32.9% to women. In relative terms, women tend to be concentrated in the first position of the authorship by-line (which could be a reflection of new female incorporations into neuroscience research publishing their first studies), and much less in the last (senior) position. This double pattern suggests that age probably plays a role in (partly) explaining gender asymmetry, both in science in general and in neuroscience in particular.

Suggested Citation

  • González-Álvarez, Julio & Cervera-Crespo, Teresa, 2017. "Research production in high-impact journals of contemporary neuroscience: A gender analysis," Journal of Informetrics, Elsevier, vol. 11(1), pages 232-243.
  • Handle: RePEc:eee:infome:v:11:y:2017:i:1:p:232-243
    DOI: 10.1016/j.joi.2016.12.007
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    1. Vincent Larivière & Chaoqun Ni & Yves Gingras & Blaise Cronin & Cassidy R. Sugimoto, 2013. "Bibliometrics: Global gender disparities in science," Nature, Nature, vol. 504(7479), pages 211-213, December.
    2. Maite Barrios & Anna Villarroya & Ángel Borrego, 2013. "Scientific production in psychology: a gender analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 95(1), pages 15-23, April.
    3. Pleun Arensbergen & Inge van der Weijden & Peter Besselaar, 2012. "Gender differences in scientific productivity: a persisting phenomenon?," Scientometrics, Springer;Akadémiai Kiadó, vol. 93(3), pages 857-868, December.
    4. Hajar Sotudeh & Nahid Khoshian, 2014. "Gender differences in science: the case of scientific productivity in Nano Science & Technology during 2005–2007," Scientometrics, Springer;Akadémiai Kiadó, vol. 98(1), pages 457-472, January.
    5. Wolfgang Glänzel & Rickard Danell & Olle Persson, 2003. "The decline of Swedish neuroscience: Decomposing a bibliometric national science indicator," Scientometrics, Springer;Akadémiai Kiadó, vol. 57(2), pages 197-213, June.
    6. Helen Shen, 2013. "Inequality quantified: Mind the gender gap," Nature, Nature, vol. 495(7439), pages 22-24, March.
    7. Rørstad, Kristoffer & Aksnes, Dag W., 2015. "Publication rate expressed by age, gender and academic position – A large-scale analysis of Norwegian academic staff," Journal of Informetrics, Elsevier, vol. 9(2), pages 317-333.
    8. Marsh, Herbert W. & Jayasinghe, Upali W. & Bond, Nigel W., 2011. "Gender differences in peer reviews of grant applications: A substantive-methodological synergy in support of the null hypothesis model," Journal of Informetrics, Elsevier, vol. 5(1), pages 167-180.
    9. Hildrun Kretschmer & Ramesh Kundra & Donald deB. Beaver & Theo Kretschmer, 2012. "Gender bias in journals of gender studies," Scientometrics, Springer;Akadémiai Kiadó, vol. 93(1), pages 135-150, October.
    10. Juan Zhang & Qi Yu & Fashan Zheng & Chao Long & Zuxun Lu & Zhiguang Duan, 2016. "Comparing keywords plus of WOS and author keywords: A case study of patient adherence research," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 67(4), pages 967-972, April.
    11. Jevin D West & Jennifer Jacquet & Molly M King & Shelley J Correll & Carl T Bergstrom, 2013. "The Role of Gender in Scholarly Authorship," PLOS ONE, Public Library of Science, vol. 8(7), pages 1-6, July.
    12. Waltman, Ludo, 2012. "An empirical analysis of the use of alphabetical authorship in scientific publishing," Journal of Informetrics, Elsevier, vol. 6(4), pages 700-711.
    13. Abramo, Giovanni & D’Angelo, Ciriaco Andrea & Murgia, Gianluca, 2013. "Gender differences in research collaboration," Journal of Informetrics, Elsevier, vol. 7(4), pages 811-822.
    14. Allison L. Hopkins & James W. Jawitz & Christopher McCarty & Alex Goldman & Nandita B. Basu, 2013. "Disparities in publication patterns by gender, race and ethnicity based on a survey of a random sample of authors," Scientometrics, Springer;Akadémiai Kiadó, vol. 96(2), pages 515-534, August.
    15. José María Cavero & Belén Vela & Paloma Cáceres & Carlos Cuesta & Almudena Sierra-Alonso, 2015. "The evolution of female authorship in computing research," Scientometrics, Springer;Akadémiai Kiadó, vol. 103(1), pages 85-100, April.
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    5. Dongqing Lyu & Kaile Gong & Xuanmin Ruan & Ying Cheng & Jiang Li, 2021. "Does research collaboration influence the “disruption” of articles? Evidence from neurosciences," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(1), pages 287-303, January.

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