Involvement of women in the scientific outputs of the National Institute for Space Research (INPE)
DOI:
https://doi.org/10.47989/ir30357581Keywords:
scientific production, social network analysis, gender differenceAbstract
Introduction. In research centres, the evaluation of scientific production is of great importance, since various aspects of this production can be analysed, such as co-authorship networks, participation in research projects and in academic juries, to name a few. The aim of this study is to analyse the participation of women researchers in the scientific output of a Brazilian research institution, the National Institute for Space Research (INPE).
Method. A quantitative analysis, complemented by the social network analysis approach, was applied from the perspective of network centrality.
Analysis. The study found that, although the number of women researchers is lower than that of men researchers, they individually have an annual publication rate very close to that of men researchers, as well as participation in numerous research projects and academic juries, contrary to initial expectations and the evidence presented in the theoretical study.
Conclusion. It is hoped that the results of this study will add to the existing knowledge on the contribution of women in the field of space, as well as allowing reflection on the issue of women's participation in science, and encourage actions and policies to stimulate the training of women researchers.
References
Abramo, G., & D’Angelo, C. A. (2023). How reliable are unsupervised author disambiguation algorithms in the assessment of research organization performance? Quantitative Science Studies, 4(1), 144-166. https://doi.org/10.1162/qss_a_00236
Adams, J., Gurney, K., Hook, D., & Leydesdorff, L. (2014). International collaboration cluster in Africa. Scientometrics, 98(1), 547-556. https://doi.org/10.1007/s11192-013-1060-2
Alcaide, G., Calatayud, V., Valderrama-Zurian, J. C., & Aleixandre-Benavent, R. (2009). Participation of women in Spanish sociology journals. Revista Española de Investigaciones Sociologicas, 126, 153-166. https://doi.org/10.5477/cis/reis.126.153.
Anderson, J., & Evered, D. C. (1986). Why do research on research? Lancet, 328(8510), 799-802. https://doi.org/10.1016/s0140-6736(86)90312-0
Aria, M., & Cuccurullo, C. (2017). Bibliometrix: An R-tool for comprehensive science mapping analysis. Journal of Informetrics, 11(4), 959-975. https://doi.org/10.1016/j.joi.2017.08.007
Arroyo Moliner, L., Gallardo-Gallardo, E., & Gallo de Puelles, P. (2017). Understanding scientific communities: A social network approach to collaborations in talent management research. Scientometrics, 113(3), 1439-1462. https://doi.org/10.1007/s11192-017-2537-1
Azimi, M. H., & Mohammadi, Z. (2024). Analysis of the scientific cooperation network of ontology researchers using social network indicators and examining the degree of correlation between centrality indicators and researchers' productivity and efficiency. Scientometrics Research Journal, 9(2), 471-496. https://doi.org/10.22070/rsci.2022.15249.1532
Bakshi-Hamm, P., & Hamm, A. (2023). Knowledge production: Analysing gender– and country– dependent factors in research topics through term communities. MDPI Publications, 10(45), 1-37. https://doi.org/10.3390/publications10040045
Bergsma, S., Mandryk, R. L., & McCalla, G. (2014). Learning to measure influence in a scientific social network. In M. Sokolova, & P. van Beek (Eds.), Advances in Artificial Intelligence: Proceedings of the 27th Canadian Conference on Artificial Intelligence, Montreal, QC, May 6-9, 2014 (pp. 35-46). Springer. https://link.springer.com/chapter/10.1007/978-3-319-06483-3_4
Bouabid, H., & Achachi, H. (2022). Size of science team at university and internal co-publications: Science policy implications. Scientometrics, 127(12), 6993-7013. https://doi.org/10.1007/s11192-022-04285-x
Braun, T. (1999). Bibliometric indicators for the evaluation of universities: Intelligence from the quantitation of the scientific literature. Scientometrics, 45(3), 425-432. https://doi.org/10.1007/bf02457602
Cândido, M. R., Campos, L., & Feres, J. (2021). The gendered division of labor in Brazilian political science journals. Brazilian Political Science Review, 15(3), 1-33. https://doi.org/10.1590/1981-3821202100030008
Chen, K., Zhang, Y., & Fu, X. (2019). International research collaboration: an emerging domain of innovation studies? Research Policy, 48(1), 149-168. https://doi.org/10.1016/j.respol.2018.08.005
Chinchilla-Rodríguez, Z., Miao, L., Murray, D., Robinson-Garcia, N., Costas, R., & Sugimoto, C. R. (2018). A global comparison of scientific mobility and collaboration according to national scientific capacities. Frontiers in Research Metrics and Analytics, 3, article 17. https://doi.org/10.3389/frma.2018.00017
Dabas, B., & Kumar, S. (2018). Research output of Indian women scientists in the field of physics and astronomy: A scientometrics study. Library Philosophy and Practice, article 1903. http://digitalcommons.unl.edu/libphilprac/1903
Damar, M., Ozdagoglu, G., & Saso, L. (2022). Designing a business intelligence-based monitoring platform for evaluating research collaborations within university networks: The case of UNICA, the Network of Universities from the Capitals of Europe. Information Research, 27(4), paper945. https://doi.org/10.47989/irpaper945
Danesh, F., Karan, S. K., Banihashemi, L., & GhaviDel, S. (2023). Social Network Analysis of Editorial Board Interlocking phenomena from the perspective of astronomy and astrophysics journals. International Journal of Information Science and Management, 21(1), 127-148. https://doi.org/10.22034/ijism.2022.1977746.0
Demirkan, I., & Demirkan, S. (2012). Network characteristics and patenting in biotechnology, 1990-2006. Journal of Management, 38(6), 1892-1927. https://doi.org/10.1177/0149206311408319
Di Bella, E. Gandullia, L., & Preti, S. (2021). Analysis of scientific collaboration network of Italian Institute of Technology. Scientometrics, 126(10), 8517-8539. https://doi.org/10.1007/s11192-021-04120-9
Felizardo, K. et al. (2021). Global and Latin American female participation in evidence-based software engineering: A systematic mapping study. Journal of the Brazilian Computer Society, 27(6), article 6/2021. https://doi.org/10.1186/s13173-021-00109-7
Galbiati, L. A., & Campos, J. (2021). Relatório Equidade de gênero nos espaços de governança climática. http://urlib.net/ibi/8JMKD2USNRW34T/4DMANA8
Hajibabaei, A., Schiffauerova, A., & Ebadi, A. (2023). Women and key positions in scientific collaboration networks: Analysing central scientists’ profiles in the artificial intelligence ecosystem through a gender lens. Scientometrics, 128(2), 1219-1240. https://doi.org/10.1007/s11192-022-04601-5
Hansen, D. L., Shneiderman, B., & Smith, M. A. (2011). Analysing social media networks with NodeXL: Insights from a connected world. Graduate Journal of Social Science, 8(3), 177-181. https://doi.org/10.1016/C2009-0-64028-9
Holman, L., Stuart-Fox, D., & Hauser, C. E. (2018). The gender gap in science: How long until women are equally represented? PLOS Biology, 16(4), e2004956. https://doi.org/10.1371/journal.pbio.2004956
Huang, J. Gates, A., Sinatra, R., & Barabasi, A. (2020). Historical comparison of gender inequality in scientific careers across countries and disciplines. PNAS, 117(9), 4609-4616. http://doi.org/10.1073/pnas.1914221117
Instituto Nacional de Pesquisas Espaciais. (2022). Plano Diretor do INPE 2022-2026. http://urlib.net/ibi/8JMKD3MGPW34P/48U8JBB
Jadidi, M., Karimi, F., Lietz, H., & Wagner, C. (2023). Gender disparities in science? Dropout, productivity, collaborations and success of male and female computer scientists. Advances in Complex Systems, 21(3-4), 1750011. https://doi.org/10.1142/S0219525917500114
Johannesen, E., Ojwala, R. A., Rodriguez, M. C., Neat, F., Kitada, M., Buckingham, S., Schofield, C., Long, R., Jarnsäter, J., & Sun, Z. (2022 May/June). The sea change needed for gender equality in ocean-going research. Marine Technology Society Journal, 3, 18-24. https://doi.org/10.4031/MTSJ.56.3.6
Joyce, K. E., Nakalembe, C. L., Gómez, C., Suresh, G., Fickas, K., Halabisky, M., Kalamandeen, M., & Crowley, M. A. (2022). Discovering inclusivity in remote sensing: Leaving no one behind. Frontiers in Remote Sensing, 3, article 869291 . https://doi.org/10.3389/frsen.2022.869291
Kemechian, T., Sigahi, T., Martins, V., Rampasso, I., Moraes, G. H., Serafim, M. P., Leal Filho, W., & Anholon, R. (2023). Towards the SDGs for gender equality and decent work: Investigating major challenges faced by Brazilian women in STEM careers with international experience. Discover Sustainability, 4, article 11. https://doi.org/10.1007/s43621-023-00125-x
Kumar, S. (2015). Co-authorship networks: A review of literature. Aslib Journal of Information Management, 67(1), 55-73. https://doi.org/10.1108/AJIM-09-2014-0116
Larivière, V., Ni, C., Gingras, Y., Cronin, B., & Sugimoto, C. R. (2013). Bibliometrics: Global gender disparities in science. Nature, 504, 211-213. https://doi.org/10.1038/504211a
Legg, S., Wang, C., Kappel, E., & Thompson, L. (2023). Gender equity in oceanography. Annual Review of Marine Science, 15, 15-39. https://doi.org/10.1146/annurev-marine-032322-100357
Martins, D. L. (2014). Análise dinâmica de redes sociais de coparticipação em bancas de defesa de teses e dissertações: um estudo de caso a partir de múltiplos indicadores na área de Ciências da Comunicação. Encontros Bibli: revista eletrônica de biblioteconomia e ciência da informação, 19(40), 99-116. https://doi.org/10.5007/1518-2924.2014v19n40p99
Moschkovich, M., & Almeida, A. M. (2015). Desigualdades de gênero na carreira acadêmica no Brasil. Dados, 58(3), 749-789. https://doi.org/10.1590/00115258201558
Newman, M. E. J. (2012). Communities, modules and large-scale structure in networks. Nature Physics, 8(1), 25-31. https://doi.org/10.1038/nphys2162
Ozel, B. (2012a). Collaboration structure and knowledge diffusion in Turkish management academia. Scientometrics, 93(1), 183-206. https://doi.org/10.1007/s11192-012-0641-9
Ozel, B. (2012b). Individual cognitive structures and collaboration patterns in academia. Scientometrics, 91(2), 539-555. https://doi.org/10.1007/s11192-012-0624-x
Pico, T., Bierman, P., Doyle, K., & Richardson, S. (2020). First authorship gender gap in the geosciences. Earth Space Science, 7(8), e2020EA001203. https://doi.org/10.1029/2020EA001203
Recuero, R. (2017). Introdução à análise de redes sociais online. Edfba. https://repositorio.ufba.br/bitstream/ri/24759/4/AnaliseDeRedesPDF.pdf
Robredo, J., & Cunha, M. B. da (1998). Aplicação de técnicas infométricas para identificar a abrangência do léxico básico que caracteriza os processos de indexação e recuperação da informação. Ciência da Informação, 27(1), 11-27. https://www.scielo.br/j/ci/a/6mYwyL3tkQxzHDh7HQ8LWnM/?format=pdf&lang=pt
Rotolo, D., Rafols, I., Hopkins, M. M., & Leydesdorff, L. (2017). Strategic intelligence on emerging technologies: Scientometric overlay mapping. Journal of the Association for Information Science and Technology, 68(1), 214-233. https://doi.org/10.1002/asi.23631
Sadatmoosavi, A., Nooshinfard, F., Hariri, N., & Esmaeil, S. M. (2018). Does the superior position of countries in co-authorship networks lead to their high citation performance in the field of nuclear science and technology? Malaysian Journal of Library & Information Science, 23(1), 51-65. https://doi.org/10.22452/mjlis.vol23no1.4
Saunders, M., Thornhill, A., & Lewis, P. (2016). Research methods for business students (7th ed.). Pearson Education.
Serrat, O. (2017). Social network analysis. In Knowledge solutions: Tools, methods, and approaches to drive organizational performance (pp. 39-43). Springer. http://link.springer.com/book/10.1007/978-981-10-0983-9
Shin, H., Kim, K., & Kogler, D. F. (2022) Scientific collaboration, research funding, and novelty in scientific knowledge. PLoS ONE 17(7), e0271678. https://doi.org/10.1371/journal.pone.0271678
Sonnenwald, D. (2007). Scientific collaboration. Annual Review of Information Science and Technology, 41(1), 643-681. https://asistdl.onlinelibrary.wiley.com/doi/10.1002/aris.2007.1440410121
Supplee, L., Boaz, A., & Metz, A. (2023). Learning across contexts: Bringing together research on research use and implementation science. William T. Grant Foundation. https://eric.ed.gov/?id=ED628120
Thomas, D. A., Nedeva, M., Tirado, M. M., & Jacob, M. (2020). Changing research on research evaluation: a critical literature review to revisit the agenda. Research Evaluation, 29(3), 275–288. https://doi.org/10.1093/reseval/rvaa008.
Velez-Estevez, A., Garcia-Sanchez, P., Moral-Munhoz, J. A., & Cobo, M. J. (2022). Why do papers from international collaborations get more citations? A bibliometric analysis of library and information science papers. Scientometrics, 127(12), 7517-7555. https://doi.org/10.1007/s11192-022-04486-4
Wagner, C., & Leydesdorff, L. (2005). Network structure, self-organization, and the growth of international collaboration in science. Research Policy 34(10), 1608–1618. https://doi.org/10.1016/j.respol.2005.08.002
Wasserman, S., & Faust, K. (1994). Social network analysis: Methods and applications. Cambridge University Press.
Yuan, S., Shao, Z., Wei, X., Tang, J., Hall, W., Wang, Y., Wang, Y., & Wang, Y. (2020). Science behind AI: The evolution of trend, mobility, and collaboration. Scientometrics, 124(2), 993-1013. https://doi.org/10.1007/s11192-020-03423-7
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