Abstract
In this research, we quantify an inflow of women into science in the past three decades. Structured Big Data allow us to estimate the contribution of women scientists to the growth of science by disciplines (N = 14 STEMM disciplines) and over time (1990–2023). A monolithic segment of STEMM science emerges from this research as divided between the disciplines in which women’s share rose most rapidly–and the disciplines in which the role of women was marginal. There are four disciplines in which 50% of currently publishing scientists are women; and five disciplines in which more than 50% of currently young scientists are women. But there is also a cluster of four highly mathematized disciplines (MATH, COMP, PHYS, and ENG) in which the growth of science is only marginally driven by women. Digital traces left by scientists in their publications indexed in global datasets open two new dimensions in large-scale academic profession studies: time and gender. The growth of science in Europe was accompanied by growth in the number of women scientists, but with powerful cross-disciplinary and cross-generational differentiations. We examined the share of women scientists coming from ten different age cohorts for 32 European and four comparator countries (the USA, Canada, Australia, and Japan). Our study sample was N = 1,740,985 scientists (including 39.40% women scientists). Three critical methodological challenges of using structured Big Data of the bibliometric type were discussed: gender determination, academic age determination, and discipline determination.
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We used data from Scopus, a proprietary scientometric database. For legal reasons, data from Scopus received through collaboration with the ICSR Lab owned by Elsevier cannot be made openly available.
References
Abramo G, D’Angelo CA, Murgia G (2016) The combined effect of age and seniority on research performance of full professors. Sci Public Policy 43(3):301–319
Aksnes DW, Rorstad K, Piro F, Sivertsen G (2011) Are female researchers less cited? A large-scale study of Norwegian scientists. J Am Soc Inf Sci 62:628–636. https://doi.org/10.1002/asi.21486
Alexopoulos M, Lyons K, Mahetaji K, Barnes, ME, Gutwillinger R (2023) Gender inference: can ChatGPT outperform common commercial tools? In Proceedings of the ACM Conference, pp. 161–166
Alperin JP, Portenoy J, Demes K, Larivière V, Haustein S (2024) An analysis of the suitability of OpenAlex for bibliometric analyses. Preprint at. https://arxiv.org/abs/2404.17663
Baker DP, Powell JJW (2024) Global mega-science: Universities, research collaborations, and knowledge production. Palo Alto: Stanford University Press
Baker M (2012) Academic careers and the gender gap. Vancouver: UBC Press
Bell A (2020) Age period cohort analysis: a review of what we should and shouldn’t do. Ann Hum Biol 47(2):208–217
Ben-David J (1968) The universities and the growth of science in Germany and the United States. Minerva 7:1–35
Van den Besselaar P, Sandström U (2016) Gender differences in research performance and its impact on careers: a longitudinal case study. Scientometrics 106(1):143–162
Bornmann L, Mutz R (2015) Growth rates of modern science: A bibliometric analysis based on the number of publications and cited references. J Assn Inf Sci Tec 66:2215–2222. https://doi.org/10.1002/asi.23329
Bornmann L, Haunschild R, Mutz R (2021) Growth rates of modern science: a latent piecewise growth curve approach to model publication numbers from established and new literature databases. Human Soc Sci Commun 8:224. https://doi.org/10.1057/s41599-021-00903-w
Branch EH, Alegria S (2016) Gendered Responses to Failure in Undergraduate Computing. Evidence, Contradictions, and New Directions. In: EH Branch (ed.), Pathways, Potholes, and the Persistence of Women in Science. Reconsidering the Pipeline. Lexington Books, pp. 17–31
Cañibano C, Woolley R, Iversen EJ et al. (2019) A conceptual framework for studying science research careers. J Technol Transf 44:1964–1992. https://doi.org/10.1007/s10961-018-9659-3
Cech EA, Waidzunas TJ(2021) Systemic inequalities for LGBTQ professionals in STEM Sci Adv 7:eabe0933. https://doi.org/10.1126/sciadv.abe0933
Cole S (1979) Age and scientific performance. Am J Sociol 84(4):958–977
Cole JR (1979) Women in the scientific community. New York: Columbia University Press
Cornelius R, Constantinople A, Gray J(1988) The Chilly Climate: Fact Or Artifact? J High Educ 59(5):527–555
Elsevier (2018) Gender in the global research landscape. Elsevier
Elsevier (2020) The researcher journey through a gender lens. Elsevier
Fosse E, Winship C (2019) Analyzing age-period-cohort data: a review and critique. Annu Rev Sociol 45:467–492. https://doi.org/10.1146/annurev-soc-073018-022616
Fowler JH, Aksnes DW (2007) Does self-citation pay?. Scientometrics 72(3):427–437
Fox MF (2010) Women and men faculty in academic science and engineering: Social-organizational indicators and implications. Am Behav Sci 53:997–1012
Fox MF, Mohapatra S (2007) Social-organizational characteristics of work and publication productivity among academic scientists in doctoral-granting departments. J High Educ 78(5):542–571
Fox MF, Kline K (2016) Women faculty in computing. A keycase of women in science. In: EH Branch (ed.), Pathways, potholes, and the persistence of women in science: Reconsidering the pipeline. Lexington Books, pp. 54–69
Gilbert GN (1978) Measuring the growth of science. Scientometrics 1:9–34. https://doi.org/10.1007/BF02016837
Glenn ND (2005) Cohort analysis. Thousand Oaks, CA: Sage
Goulden M, Mason MA, Frasch K (2011) Keeping women in the science pipeline. Ann Am Acad Political Soc Sci 638:141–162
Gui Q, Liu C, Du D (2019) Globalization of science and international scientific collaboration: a network perspective. Geoforum 105:1–12. https://doi.org/10.1016/j.geoforum.2019.06.017
Holmes DE (2017) Big data: A very short introduction. Oxford: Oxford University Press
Hu Y, Hu C, Tran T, Kasturi T, Joseph E, Gillingham M (2021) What’s in a name? Gender classification of names with character-based machine learning models. Data Min Knowl Discov 35(4):1537–1563
Huang J, Gates AJ, Sinatra R, Barabási A-L (2020) Historical comparison of gender inequality in scientific careers across countries and disciplines. Proc Natl Acad Sci USA 117(9):4609–4616
Ioannidis JPA, Boyack KW, Klavans R (2014) Estimates of the continuously publishing core in the scientific workforce. PLOS One 9(7):e101698
Ioannidis JPA, Boyack KW, Collins TA, Baas J (2023) Gender imbalances among top-cited scientists across scientific disciplines over time through the analysis of nearly 5.8 million authors. PLOS Biol 21(11):e3002385. https://doi.org/10.1371/journal.pbio.3002385
Karimi F, Wagner C, Lemmerich F, Jadidi M, Strohmaier M (2016) Inferring gender from names on the web: A comparative evaluation of gender detection methods. In Proceedings of the 25th International Conference Companion on World Wide Web, pp. 53–54
King MM, Bergstrom CT, Correll SJ, Jacquet J, West JD (2017) Men set their own cites high: gender and self-citation across fields and over time. Socius 3:1–15
Kwiek M, Roszka W (2021a) Gender disparities in international research collaboration: A large-scale bibliometric study of 25,000 university professors. J Econ Surv 35(5):1344–1388. https://doi.org/10.1111/joes.12395
Kwiek M, Roszka W (2021b) Gender-based homophily in research: a large-scale study of man-woman collaboration. J Informetr 15(3):1–38. https://doi.org/10.1016/j.joi.2021.101171
Kwiek M, Roszka W (2022a) Are female scientists less inclined to publish alone? The gender solo research gap. Scientometrics 127:1697–1735. https://doi.org/10.1007/s11192-022-04308-7
Kwiek M, Roszka W (2022b) Academic vs. biological age in research on academic careers: a large-scale study with implications for scientifically developing systems. Scientometrics 127:3543–3575. https://doi.org/10.1007/s11192-022-04363-0
Kwiek M, Roszka W (2024a) Once highly productive, forever highly productive? Full professors’ research productivity from a longitudinal perspective. High Educ 87:519–549. https://doi.org/10.1007/s10734-023-01022-y
Kwiek M, Roszka W (2024b) Are scientists changing their research productivity classes when they move up the academic ladder?. Innovative High Educ 50:329–367. https://doi.org/10.1007/s10755-024-09735-3
Kwiek M, Roszka W (2024c) Top research performance in Poland over three decades: a multidimensional micro-data approach. J Informetr 18(4):101595. https://doi.org/10.1016/j.joi.2024.101595
Kwiek M, Szymula L (2023) Young male and female scientists: a quantitative exploratory study of the changing demographics of the global scientific workforce. Quant Sci Stud 4(4):902–937. https://doi.org/10.1162/qss_a_00276
Kwiek M, Szymula L (2024) Quantifying attrition in science: a cohort-based, longitudinal study of scientists in 38 OECD countries. High Educ 89:1465–1493. https://doi.org/10.1007/s10734-024-01284-0
Kwiek M, Szymula L (2025) Quantifying lifetime productivity changes: a longitudinal study of 320,000 late-career scientists. Quant Sci Stud 6:1002–1038. https://doi.org/10.1162/QSS.a.16
Kyvik S (1990) Age and scientific productivity: differences between fields of learning. High Educ 19:37–55
Larivière V, Archambault E, Gingras Y (2008) Long-term variation in the aging of scientific literature: from exponential growth to steady-state science (1900–2004). J Am Soc Inf Sci Technol 59(2):288–292
Larivière V, Ni C, Gingras Y, Cronin B, Sugimoto CR (2013) Bibliometrics: global gender disparities in science. Nature 504(7479):211–213
Lehman HC (1953) Age and achievement. Princeton: Princeton University Press
Liu L, Jones BF, Uzzi B, Ma Y, Izar AU, Wang D (2023) Data, measurement and empirical methods in the science of science. Nat Hum Behav 7:1046–1058
Long JS, Allison PD, McGinnis R (1993) Rank advancement in academic careers: Sex differences and the effects of productivity. Am Sociological Rev 58(5):703–722
Marginson S (2020) The world research system: Expansion, diversification, network and hierarchy. In: William Locke CC, Marginson S (ed) Changing higher education for a changing world, London: Bloomsbury. pp. 35–51
Menard S (2002) Longitudinal Research. Thousand Oaks, CA: Sage
Michels C, Schmoch U (2012) The growth of science and database coverage. Scientometrics 93:831–846. https://doi.org/10.1007/s11192-012-0732-7
Milojević S, Radicchi F, Walsh JP (2018) Changing demographics of scientific careers: the rise of the temporary workforce. Proc Natl Acad Sci USA 115(50):12616–12623. https://doi.org/10.1073/pnas.1800478115
Morgan AC, Way SF, Hoefer MJD, Larremore DB, Galesic M, Clauset A (2021) The unequal impact of parenthood in academia. Sci Adv 7(9):eabd1996
NamSor (2024) NamSor API documentation. https://namsor.app/api-documentation/
Nane GF, Larivière V, Costas R (2017) Predicting the age of researchers using bibliometric data. J Informetr 11(3):713–729
Ni C, Eileen Smith, Yuan H, Larivière V, Sugimoto CR (2021) The gendered nature of authorship. Sci Adv 7(36):eabe4639. https://doi.org/10.1126/sciadv.abe4639
O’Brien RM (2015) Age–period–cohort models: Approaches and analyses with aggregate data. Boca Raton: CRC Press
Pelz DC, Andrews FW (1976) Scientists in organizations. New York: Wiley
Peters SAE, Norton R (2018) Sex and gender reporting in global health: New editorial policies. BMJ Glob Health 3(4):e001038. https://doi.org/10.1136/bmjgh-2018-001038
Ployhart RE, Vandenberg RJ (2010) Longitudinal research: The theory, design, and analysis of change. J Manag 36(1):94–120
Powell JJW (2018) Higher education and the exponential rise of science: competition and collaboration. In: Scott RA, Buchmann M, Kosslyn S (eds.) Emerging Trends in the Social and Behavioral Sciences, Stanford: CASBS
Price D (1963) Little science, big science. New York: Columbia University Press
Priem J, Piwowar H, Orr R (2022) OpenAlex: a fully-open index of scholarly works, authors, venues, institutions, and concepts. Preprint at. https://arxiv.org/abs/2205.01833
Radicchi F, Castellano C (2013) Analysis of bibliometric indicators for individual scholars in a large data set. Scientometrics 97:627–637
Riesman D (1969) Universities and the growth of science in Germany and the United States. Minerva 7:751–755. https://doi.org/10.1007/BF01099545
Robinson-García N, Costas R, Sugimoto CR, Larivière V, Nane GF (2020) Task specialization across research careers. eLife 9: e60586. https://doi.org/10.7554/eLife.60586
Rørstad K, Aksnes DW, Piro FN (2021) Generational differences in international research collaboration: A bibliometric study of Norwegian university staff. PLOS ONE 16(11):e0260239. https://doi.org/10.1371/journal.pone.0260239
Ross MB, Glennon BM, Murciano-Goroff R, Berkouwer HR, Williams HL, Thompson NC (2022) Women are credited less in science than men. Nature 608:135–145. https://doi.org/10.1038/s41586-022-04966-w
Rosser SV (2004) The science glass ceiling: Academic women scientists and the struggle to succeed. New York: Routledge
Salganik MJ (2018) Bit by bit: Social research in the digital age. Princeton: Princeton University Press
Sanliturk E, Zagheni E, Dańko MJ, Theile T, Akbaritabar M (2023) Global patterns of migration of scholars with economic development. Proc Natl Acad Sci USA 120(4):e2217937120. https://doi.org/10.1073/pnas.2217937120
Santamaría L, Mihaljević H (2018) Comparison and benchmark of name-to-gender inference services. PeerJ Comput Sci 4:e156. https://doi.org/10.7717/peerj-cs.156
Savage WE, Olejniczak AJ (2021) Do senior faculty members produce fewer research publications than their younger colleagues? Evidence from Ph.D. granting institutions in the United States. Scientometrics 126:4659–4686. https://doi.org/10.1007/s11192-021-03957-4
Science-Metrix (2018) Analytical support for bibliometrics indicators. Development of bibliometric indicators to measure women’s contribution to scientific publications. Final report. Science-Metrix
Sebo P (2021) Performance of gender detection tools: A comparative study of name-to-gender inference services. J Med Libr Assoc 109(3):414–421
Selwyn N (2019) What is digital sociology? Cambridge: Polity Press
Shaw AK, Stanton DE (2012) Leaks in the pipeline: separating demographic inertia from ongoing gender differences in academia. Proc R Soc B: Biol Sci 279(1743):3736–3741
Singer JD, Willett JB (2003) Applied longitudinal data analysis: Modeling change and event occurrence. Oxford: Oxford University Press
Sonnert G (1995) Who succeeds in science? The gender dimension. New Brunswick, NJ: Rutgers University Press
Spoon K, LaBerge N, Wapman KH, Zhang S, Morgan AC, Galesic M, Fosdick BK, Larremore DB, Clauset A (2023) Gender and retention patterns among U.S. faculty. Sci Adv 9: eadi2205. https://doi.org/10.1126/sciadv.adi2205
Stephan P (2012) How economics shapes science. Cambridge, MA: Harvard University Press
Stephan PE, Levin SG (1992) Striking the mother lode in science: The importance of age, place, and time. New York: Oxford University Press
Sugimoto CR, Sugimoto TJ, Tsou A, Milojević S, Larivière V (2016) Age stratification and cohort effects in scholarly communication: a study of social sciences. Scientometrics 109(2):997–1016
Sugimoto C, Larivière V (2023) Equity for women in science: Dismantling systemic barriers to advancement. Cambridge, MA: Harvard University Press
Sugimoto CR, Larivière V (2018) Measuring research: What everyone needs to know. Oxford: Oxford University Press
Wagner CS, Joong Kim D (2014) The price of big science: saturation or abundance in scientific publication?. Policy Complex Syst 1(1):108–127
Wagner CS (2008) The new invisible college: Science for development. Washington, DC: Brookings Institution Press
Wais K (2016) Gender prediction methods based on first names with genderizeR. R J 8(1):17–37
Wang D, Barabási AL (2021) The science of science. Cambridge: Cambridge University Press
Weingart P (2004) Impact of bibliometrics upon the science system: inadvertent consequences? In: Moed HF, Glänzel W, Schmoch U (eds), Handbook on quantitative science and technology research, p 117-131 Kluwer Academic Publishers
West JD, Jacquet J, King MM, Correll SJ, Bergstrom CT (2013) The role of gender in scholarly authorship. PLOS ONE 8(7):e66212. https://doi.org/10.1371/journal.pone.0066212
Xie Y, Shauman KA (2003) Women in science: Career processes and outcomes. Harvard University Press
Xu YJ (2008) Gender disparity in STEM disciplines: a study of faculty attrition and turnover intentions. Res High Educ 49:607–624
Zhang L, Powell JJW, Baker DP (2015) Exponential Growth and the Shifting Global Center of Gravity of Science Production, 1900–2011. Change: The Magazine of Higher Learning 47(4):46–49. https://doi.org/10.1080/00091383.2015.1053777
Zippel K (2017) Women in global science. Stanford: Stanford University Press
Zuckerman H, Cole JR, Bruer JT (eds) (1991) The outer circle: women in the scientific community. New York: W.W. Norton & Company
Acknowledgements
M.K. gratefully acknowledges the support provided by the grant from MNISW (NDS grant no. NdS-II/SP/0010/2023/01). L.S. is grateful for the support of his doctoral studies provided by the NCN grant 2019/35/0/HS6/02591. We gratefully acknowledge the assistance of the International Center for the Studies of Research (ICSR) Lab with Kristy James and Alick Bird. We also want to thank Dr. Wojciech Roszka from the CPPS Poznan Team for many fruitful discussions.
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Marek Kwiek: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Resources, Software, Validation, Writing—original draft, Writing—review & editing. Lukasz Szymula: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Software, Validation, Visualization, Writing—original draft, Writing—review & editing.
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Kwiek, M., Szymula, L. Women in science: measuring participation in Europe across disciplines, generations and over time. Humanit Soc Sci Commun (2026). https://doi.org/10.1057/s41599-026-06912-x
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DOI: https://doi.org/10.1057/s41599-026-06912-x


