Brechas de género en la ciencia: revisión sistemática de las principales explicaciones y agenda de investigación

Resumen

A pesar de las mejoras en la incorporación de mujeres en la educación terciaria y la ciencia, aún persisten brechas de género en el ingreso y avance en áreas científico- tecnológicas a nivel mundial. Entender cuáles son los factores que determinan estas brechas es clave para la plena incorporación de las mujeres en las sociedades del conocimiento en términos de equidad. La presente investigación buscó explorar y sistematizar las explicaciones dadas a este fenómeno por parte de la literatura internacional en las últimas cuatro décadas. Los objetivos fueron: (1) Analizar la evolución de las principales agendas de investigación y categorizar estas en grupos (o clúster) de explicaciones, y (2) discutir los desafíos que las agendas de investigación presentan para dar cuenta del fenómeno de forma multicausal. Los datos se obtuvieron mediante una búsqueda en Web of Science (WoS) y fueron sometidos a una revisión sistemática utilizando técnicas bibliométricas y cualitativas. El análisis revela un crecimiento importante de la investigación en esta área dentro de las ciencias sociales que se agrupa en cinco grandes tipos de explicación: (1) desempeño de estudiantes en áreas STEM, (2) influencia de estereotipos y modelos de género, (3) conformación de intereses y experiencias educativas y de aprendizaje, (4) expectativas y elección educativo-ocupacional, y (5) desigual avance y desempeño en las carreras científicas. La evolución muestra que las explicaciones sobre el desempeño y la elección individual han perdido peso en el presente, dando lugar a explicaciones sobre la influencia de los estereotipos y modelos de género dentro de los sistemas educativos y ámbitos de socialización. Este estudio contribuye así a una mayor y más ordenada comprensión sobre los factores causales que han determinado las brechas de género en la ciencia al tiempo que identifica algunos vacíos en las agendas de investigación.
  • Referencias
  • Cómo citar
  • Del mismo autor
  • Métricas
Archer, L., DeWitt, J., Osborne, J., Dillon, J., Willis, B., & Wong, B. (2010). “Doing” science versus “being” a scientist: Examining 10/11-year-old schoolchildren's constructions of science through the lens of identity. Science Education, 94(4), 617-639. https://doi.org/10.1002/sce.20399
Bendels, M. H. K., Müller, R., Brueggmann, D., & Groneberg, D. A. (2018). Gender disparities in high-quality research revealed by Nature Index journals. PLoS ONE, 13(1), e0189136. https://doi.org/10.1371/journal.pone.0189136
Benería, L. (1979). Reproduction, production, and the sexual division of labor. Cambridge Journal of Economics, 3(3), 203–225.
Bennett, J., Lubben, F., & Hogarth, S. (2007). Bringing science to life: A synthesis of the research evidence on the effects of context-based and STS approaches to science teaching. Science Education, 91(3), 347–370. https://doi.org/10.1002/sce.20186
Bian, L., Leslie, S.-J., & Cimpian, A. (2017). Gender stereotypes about intellectual ability emerge early and influence children’s interests. Science, 355(6323), 389–391. https://doi.org/10.1126/science.aah6524
Blondel, V. D., Guillaume, J.-L., Lambiotte, R., & Lefebvre, E. (2008). Fast unfolding of communities in large networks. Journal of Statistical Mechanics: Theory and Experiment, 2008(10), P10008. https://doi.org/10.1088/1742-5468/2008/10/P10008
Bøe, M. V., Henriksen, E. K., Lyons, T., & Schreiner, C. (2011). Participation in science and technology: young people’s achievement?related choices in late?modern societies. Studies in Science Education, 47(1), 37-72. https://doi.org/10.1080/03057267.2011.549621
Caprile, M. (Ed). (2012). Meta-analysis of gender and science research: Synthesis report. (EUROPEAN COMMISSION). Publications Office.
Carli, L. L., Alawa, L., Lee, Y., Zhao, B., & Kim, E. (2016). Stereotypes About Gender and Science: Women ? Scientists. Psychology of Women Quarterly, 40(2), 244-260. https://doi.org/10.1177/0361684315622645
Carter, N. M., Gartner, W. B., Shaver, K. G., & Gatewood, E. J. (2003). The career reasons of nascent entrepreneurs. Journal of Business Venturing, 18(1), 13–39. https://doi.org/10.1016/S0883-9026(02)00078-2
Ceci, S. J., Ginther, D. K., Kahn, S., & Williams, W. M. (2014). Women in Academic Science: A Changing Landscape. Psychological Science in the Public Interest, 15(3), 75-141. https://doi.org/10.1177/1529100614541236
Ceci, S. J., & Williams, W. M. (2011). Understanding current causes of women’s underrepresentation in science. Proceedings of the National Academy of Sciences, 108(8), 3157–3162. https://doi.org/10.1073/pnas.1014871108
Charles, M., & Bradley, K. (2002). Equal but Separate? A Cross-National Study of Sex Segregation in Higher Education. American Sociological Review, 67(4), 573–599. https://doi.org/10.2307/3088946
Cheryan, S., & Plaut, V. C. (2010). Explaining Underrepresentation: A Theory of Precluded Interest. Sex Roles, 63(7–8), 475–488. https://doi.org/10.1007/s11199-010-9835-x
Cheryan, S., Plaut, V. C., Davies, P. G., & Steele, C. M. (2009). Ambient belonging: How stereotypical cues impact gender participation in computer science. Journal of Personality and Social Psychology, 97(6), 1045–1060. https://doi.org/10.1037/a0016239
Cheryan, S., Siy, J. O., Vichayapai, M., Drury, B. J., & Kim, S. (2011). Do Female and Male Role Models Who Embody STEM Stereotypes Hinder Women’s Anticipated Success in STEM? Social Psychological and Personality Science, 2(6), 656–664. https://doi.org/10.1177/1948550611405218
Cheryan, S., Ziegler, S. A., Montoya, A. K., & Jiang, L. (2017). Why are some STEM fields more gender balanced than others? Psychological Bulletin, 143(1), 1–35. https://doi.org/10.1037/bul0000052
Cliff, J. E. (1998). Does one size fit all? Exploring the relationship between attitudes towards growth, gender, and business size. Journal of Business Venturing, 13(6), 523–542. https://doi.org/10.1016/S0883-9026(97)00071-2
Coffin, R. J., & MacIntyre, P. D. (1999). Motivational influences on computer-related affective states. Computers in Human Behavior, 15(5), 549–569. https://doi.org/10.1016/S0747-5632(99)00036-9
Cole, E. R. (2009). Intersectionality and research in psychology. American Psychologist, 64(3), 170–180. https://doi.org/10.1037/a0014564
Cole, J., & Zuckerman, H. (1984). The Productivity Puzzle: Persistence and Change in Patterns of Publication of Men and Women Scientists. In M. W. Steinkamp & M. L. Maehr (Eds.), Advances in Motivation and Achievement (Vol. 2, pp. 217–256). JAI Press.
Correll, S. J. (2001). Gender and the Career Choice Process: The Role of Biased Self?Assessments. American Journal of Sociology, 106(6), 1691–1730. https://doi.org/10.1086/321299
Cross, S. E. (2001). Training the Scientists and Engineers of Tomorrow: A Person-Situation Approach1. Journal of Applied Social Psychology, 31(2), 296–323. https://doi.org/10.1111/j.1559-1816.2001.tb00198.x
Cvencek, D., Kapur, M., & Meltzoff, A. N. (2015). Math achievement, stereotypes, and math self-concepts among elementary-school students in Singapore. Learning and Instruction, 39, 1–10. https://doi.org/10.1016/j.learninstruc.2015.04.002
Dasgupta, N., & Asgari, S. (2004). Seeing is believing: Exposure to counterstereotypic women leaders and its effect on the malleability of automatic gender stereotyping. Journal of Experimental Social Psychology, 40(5), 642–658. https://doi.org/10.1016/j.jesp.2004.02.003
Diekman, A. B., Weisgram, E. S., & Belanger, A. L. (2015). New Routes to Recruiting and Retaining Women in STEM: Policy Implications of a Communal Goal Congruity Perspective. Social Issues and Policy Review, 9(1), 52–88. https://doi.org/10.1111/sipr.12010
DiPrete, T. A., & Eirich, G. M. (2006). Cumulative Advantage as a Mechanism for Inequality: A Review of Theoretical and Empirical Developments. Annual Review of Sociology, 32(1), 271–297. https://doi.org/10.1146/annurev.soc.32.061604.123127
Durndell, A., & Haag, Z. (2002). Computer self-efficacy, computer anxiety, attitudes towards the Internet and reported experience with the Internet, by gender, in an East European sample. Computers in Human Behavior, 18(5), 521–535. https://doi.org/10.1016/S0747-5632(02)00006-7
Eagly, A. H., & Wood, W. (2013). The Nature–Nurture Debates: 25 Years of Challenges in Understanding the Psychology of Gender. Perspectives on Psychological Science, 8(3), 340–357. https://doi.org/10.1177/1745691613484767
Eagly, A. H, & Carli, L. L. (2007). Through the Labyrinth: The Truth about how Women Become Leaders. Harvard Business Press.
Eccles, J. S. (1994). Understanding Women’s Educational and Occupational Choices. Psychology of Women Quarterly, 18(4), 585–609. https://doi.org/10.1111/j.1471-6402.1994.tb01049.x
Elder, G. H. (1998). The Life Course as Developmental Theory. Child Development, 69(1), 1–12. https://doi.org/10.2307/1132065
Else-Quest, N. M., Hyde, J. S., & Linn, M. C. (2010). Cross-national patterns of gender differences in mathematics: A meta-analysis. Psychological Bulletin, 136(1), 103–127. https://doi.org/10.1037/a0018053
Else-Quest, N. M., Mineo, C. C., & Higgins, A. (2013). Math and Science Attitudes and Achievement at the Intersection of Gender and Ethnicity. Psychology of Women Quarterly, 37(3), 293-309. https://doi.org/10.1177/0361684313480694
European Commission. (2019). She Figures 2018. https://ec.europa.eu/info/publications/she-figures-2018_en
Feng, J., Spence, I., & Pratt, J. (2007). Playing an action video game reduces gender differences in spatial cognition. Psychological Science, 18(10), 850–855. https://doi.org/10.1111/j.1467-9280.2007.01990.x
Fouad, N. A., Hackett, G., Smith, P. L., Kantamneni, N., Fitzpatrick, M., Haag, S., & Spencer, D. (2010). Barriers and Supports for Continuing in Mathematics and Science: Gender and Educational Level Differences. Journal of Vocational Behavior, 77(3), 361-373. https://doi.org/10.1016/j.jvb.2010.06.004
Fox, M. F. (2005). Gender, Family Characteristics, and Publication Productivity among Scientists. Social Studies of Science, 35(1), 131–150. https://doi.org/10.1177/0306312705046630
Fox, M. F., Fonseca, C., & Bao, J. (2011). Work and family conflict in academic science: Patterns and predictors among women and men in research universities: Social Studies of Science, 41(5), 715-735. https://doi.org/10.1177/0306312711417730
Goldin, C. (2014). A Grand Gender Convergence: Its Last Chapter. American Economic Review, 104, 1091–1119. https://doi.org/10.127/aer.104.4.1091
Harackiewicz, J. M., Canning, E. A., Tibbetts, Y., Priniski, S. J., & Hyde, J. S. (2016). Closing achievement gaps with a utility-value intervention: Disentangling race and social class. Journal of Personality and Social Psychology, 111(5), 745–765. https://doi.org/10.1037/pspp0000075
Howe, C., & Abedin, M. (2013). Classroom dialogue: A systematic review across four decades of research. Cambridge Journal of Education, 43(3), 325–356. https://doi.org/10.1080/0305764X.2013.786024
Hyde, J. S., Bigler, R. S., Joel, D., Tate, C. C., & van Anders, S. M. (2019). The future of sex and gender in psychology: Five challenges to the gender binary. American Psychologist, 74(2), 171–193. https://doi.org/10.1037/amp0000307
Hyde, J. S., Fennema, E., & Lamon, S. J. (1990). Gender differences in mathematics performance: A meta-analysis. Psychological Bulletin, 107(2), 139–155. https://doi.org/10.1037/0033-2909.107.2.139
Hyde, J. S., & Linn, M. C. (1988). Gender differences in verbal ability: A meta-analysis. Psychological Bulletin, 104(1), 53–69. https://doi.org/10.1037/0033-2909.104.1.53
Hyde, J. S., & Mertz, J. E. (2009). Gender, culture, and mathematics performance. Proceedings of the National Academy of Sciences, 106(22), 8801–8807. https://doi.org/10.1073/pnas.0901265106
Jones, M. G., Howe, A., & Rua, M. J. (2000). Gender differences in students’ experiences, interests, and attitudes toward science and scientists. Science Education, 84(2), 180–192. https://doi.org/10.1002/(SICI)1098-237X(200003)84:2<180::AID-SCE3>3.0.CO;2-X
Kahle, J. B., Parker, L. H., Rennie, L. J., & Riley, D. (1993). Gender Differences in Science Education: Building a Model. Educational Psychologist, 28(4), 379-404. https://doi.org/10.1207/s15326985ep2804_6
Keller, E. F. (1995). Reflections on Gender and Science. Yale University Press.
Kessler, M. M. (1963). Bibliographic coupling between scientific papers. American Documentation, 14(1), 10–25. https://doi.org/10.1002/asi.5090140103
Krapp, A., & Prenzel, M. (2011). Research on Interest in Science: Theories, Methods and Findings. International Journal of Science Education, 33(01), 27–50. https://doi.org/10.1080/09500693.2010.518645
Krueger, N. F., Reilly, M. D., & Carsrud, A. L. (2000). Competing models of entrepreneurial intentions. Journal of Business Venturing, 15(5), 411–432. https://doi.org/10.1016/S0883-9026(98)00033-0
Kyvik, S, & Teigen, M. (1996). Child Care, Research Collaboration, and Gender Differences in Scientific Productivity. Science, Technology, & Human Values, 21(1), 54–71. https://doi.org/10.1177/016224399602100103
Lee, B., & Bozeman, B. (2005). The Impact of Research Collaboration on Scientific Productivity. Social Studies of Science, 35, 673–702. https://doi.org/10.1177/0306312705052359
Lent, R. W., Sheu, H.-B., Miller, M. J., Cusick, M. E., Penn, L. T., & Truong, N. N. (2018). Predictors of science, technology, engineering, and mathematics choice options: A meta-analytic path analysis of the social–cognitive choice model by gender and race/ethnicity. Journal of Counseling Psychology, 65(1), 17–35. https://doi.org/10.1037/cou0000243
Lincoln, A. E., Pincus, S., Koster, J. B., & Leboy, P. S. (2012). The Matilda Effect in science: Awards and prizes in the US, 1990s and 2000s. Social Studies of Science, 42(2), 307-320. https://doi.org/10.1177/0306312711435830
Long, J. S. (1992). Measures of sex differences in Scientific Productivity. Social Forces, 71, 159-178. https://doi.org/10.2307/2579971
López-Bassols, V., Grazzi, M., Guillard, C., & Salazar, M. (2018). Las brechas de género en ciencia, tecnología e innovación en América Latina y el Caribe: Resultados de una recolección piloto y propuesta metodológica para la medición. Banco Interamericano de Desarrollo. https://doi.org/10.18235/0001082
Ma, Y. (2011). Gender Differences in the Paths Leading to a STEM Baccalaureate. Social Science Quarterly, 92(5), 1169–1190. https://doi.org/10.1111/j.1540-6237.2011.00813.x
Maltese, A. V., & Tai, R. H. (2010). Eyeballs in the Fridge: Sources of early interest in science. International Journal of Science Education, 32(5), 669–685. https://doi.org/10.1080/09500690902792385
Mason, M. A., & Goulden, M. (2004). Marriage and Baby Blues: Redefining Gender Equity in the Academy. The Annals of the American Academy of Political and Social Science, 596(1), 86–103. https://doi.org/10.1177/0002716204268744
Merton, R. K. (1977). La sociología de la ciencia: Investigaciones teóricas y empíricas. Alianza Editorial, S. A.
Miller, D. I., Nolla, K. M., Eagly, A. H., & Uttal, D. H. (2018). The Development of Children’s Gender-Science Stereotypes: A Meta-analysis of 5 Decades of U.S. Draw-A-Scientist Studies. Child Development, 89(6), 1943–1955. https://doi.org/10.1111/cdev.13039
Mongeon, P., & Paul-Hus, A. (2016). The journal coverage of Web of Science and Scopus: A comparative analysis. Scientometrics, 106(1), 213–228. https://doi.org/10.1007/s11192-015-1765-5
Morgan, S. L., Gelbgiser, D., & Weeden, K. A. (2013). Feeding the pipeline: Gender, occupational plans, and college major selection. Social Science Research, 42(4), 989–1005. https://doi.org/10.1016/j.ssresearch.2013.03.008
Morrison, E., Rudd, E., & Nerad, M. (2011). Onto, Up, Off the Academic Faculty Ladder: The Gendered Effects of Family on Career Transitions for a Cohort of Social Science Ph.D.s. The Review of Higher Education, 34(4), 525–553. https://doi.org/10.1353/rhe.2011.0017
Moss-Racusin, C. A., Dovidio, J. F., Brescoll, V. L., Graham, M. J., & Handelsman, J. (2012). Science faculty’s subtle gender biases favor male students. Proceedings of the National Academy of Sciences of the United States of America, 109(41), 16474–16479. https://doi.org/10.1073/pnas.1211286109
Nittrouer, C. L., Hebl, M. R., Ashburn-Nardo, L., Trump-Steele, R. C. E., Lane, D. M., & Valian, V. (2018). Gender disparities in colloquium speakers at top universities. Proceedings of the National Academy of Sciences, 115(1), 104–108. https://doi.org/10.1073/pnas.1708414115
Nosek, B. A., Smyth, F. L., Sriram, N., Lindner, N. M., Devos, T., Ayala, A., Bar-Anan, Y., Bergh, R., Cai, H., Gonsalkorale, K., Kesebir, S., Maliszewski, N., Neto, F., Olli, E., Park, J., Schnabel, K., Shiomura, K., Tulbure, B. T., Wiers, R. W., Somogyi, M., Akrami, N., Ekehammar, B., Vianello, M., Banaji, M. R., & Greenwald, A. G. (2009). National differences in gender–science stereotypes predict national sex differences in science and math achievement. Proceedings of the National Academy of Sciences, 106(26), 10593-10597. https://doi.org/10.1073/pnas.0809921106
Petersen, J., & Hyde, J. S. (2014). Gender-Related Academic and Occupational Interests and Goals. In L. S. Liben & R. S. Bigler (Eds.), The Role of Gender in Educational Contexts and Outcomes (Vol. 47, pp. 43-76). Academic Press. https://doi.org/10.1016/bs.acdb.2014.04.004
Reilly, D. (2012). Gender, Culture, and Sex-Typed Cognitive Abilities. PLoS ONE, 7(7), e39904. https://doi.org/10.1371/journal.pone.0039904
Reilly, D., Neumann, D.L., & Andrews, G. (2015). Sex differences in mathematics and science achievement: A meta-analysis of National Assessment of Educational Progress assessments. Journal of Educational Psychology, 107(3), 645–662. https://doi.org/10.1037/edu0000012
Riegle-Crumb, C., Farkas, G., & Muller, C. (2006). The Role of Gender and Friendship in Advanced Course Taking. Sociology of Education, 79(3), 206–228. https://doi.org/10.1177/003804070607900302
Riegle-Crumb, C., King, B., Grodsky, E., & Muller, C. (2012). The More Things Change, the More They Stay the Same? Prior Achievement Fails to Explain Gender Inequality in Entry into STEM College Majors Over Time. American Educational Research Journal, 49(6), 1048-1073. https://doi.org/10.3102/0002831211435229
Rossi, A. S. (1965). Women in Science: Why So Few? Science, 148(3674), 1196–1202. https://doi.org/10.1126/science.148.3674.1196
Rossiter, M. W. (1993). The Matthew Matilda Effect in Science. Social Studies of Science, 23(2), 325–341. https://doi.org/10.1177/030631293023002004
Sadler, P. M., Sonnert, G., Hazari, Z., & Tai, R. (2012). Stability and volatility of STEM career interest in high school: A gender study. Science Education, 96(3), 411-427. https://doi.org/10.1002/sce.21007
Sax, L. J., Kanny, M. A., Riggers-Piehl, T. A., Whang, H., & Paulson, L. N. (2015). “But I’m Not Good at Math”: The Changing Salience of Mathematical Self-Concept in Shaping Women’s and Men’s STEM Aspirations. Research in Higher Education, 56(8), 813-842. https://doi.org/10.1007/s11162-015-9375-x
Schmader, T. (2002). Gender Identification Moderates Stereotype Threat Effects on Women’s Math Performance. Journal of Experimental Social Psychology, 38(2), 194–201. https://doi.org/10.1006/jesp.2001.1500
Shauman, K. A., & Xie, Y. (1996). Geographic Mobility of Scientists: Sex Differences and Family Constraints. Demography, 33(4), 455–468. https://doi.org/10.2307/2061780
Shields, S. A. (2008). Gender: An Intersectionality Perspective. Sex Roles, 59(5), 301-311. https://doi.org/10.1007/s11199-008-9501-8
Sikora, J., & Pokropek, A. (2012). Gender segregation of adolescent science career plans in 50 countries. Science Education, 96(2), 234–264. https://doi.org/10.1002/sce.20479
Steele, C. M. (1997). A threat in the air. How stereotypes shape intellectual identity and performance. The American Psychologist, 52(6), 613–629. https://doi.org/10.1037//0003-066x.52.6.613
Stern, P. C., Kalof, L., Dietz, T., & Guagnano, G. A. (1995). Values, Beliefs, and Proenvironmental Action: Attitude Formation Toward Emergent Attitude Objects1. Journal of Applied Social Psychology, 25(18), 1611-1636. https://doi.org/10.1111/j.1559-1816.1995.tb02636.x
Stout, J. G., Dasgupta, N., Hunsinger, M., & McManus, M. A. (2011). STEMing the tide: Using ingroup experts to inoculate women’s self-concept in science, technology, engineering, and mathematics (STEM). Journal of Personality and Social Psychology, 100(2), 255–270. https://doi.org/10.1037/a0021385
Tenenbaum, H. R., & Leaper, C. (2003). Parent-child conversations about science: The socialization of gender inequities? Developmental Psychology, 39(1), 34–47. https://doi.org/10.1037//0012-1649.39.1.34
UNESCO. (2011). Global education digest 2010. Comparing Education Statistics Across the World. http://www.uis.unesco.org/
UNESCO. (2017). Cracking the code: Girls’ and women’s education in science, technology, engineering and mathematics (STEM). https://unesdoc.unesco.org/ark:/48223/pf0000253479
UNESCO. (2018). Women in Science (Fact Sheet No. 51 June 2018 FS/2018/SCI/51).
Uttal, D. H., Meadow, N. G., Tipton, E., Hand, L. L., Alden, A. R., Warren, C., & Newcombe, N. S. (2013). The malleability of spatial skills: A meta-analysis of training studies. Psychological Bulletin, 139(2), 352–402. https://doi.org/10.1037/a0028446
Valian, V. (1999). Why So Slow? MIT Press.
Vincent?Ruz, P., & Schunn, C. D. (2017). The increasingly important role of science competency beliefs for science learning in girls. Journal of Research in Science Teaching, 54(6), 790–822. https://doi.org/10.1002/tea.21387
Voyer, D., Voyer, S., & Bryden, M. P. (1995). Magnitude of sex differences in spatial abilities: A meta-analysis and consideration of critical variables. Psychological Bulletin, 117(2), 250–270. https://doi.org/10.1037/0033-2909.117.2.250
Voyer, D., & Voyer, S. D. (2014). Gender differences in scholastic achievement: A meta-analysis. Psychological Bulletin, 140(4), 1174–1204. https://doi.org/10.1037/a0036620
Waltman, L., van Eck, N. J., & Noyons, E. C. M. (2010). A unified approach to mapping and clustering of bibliometric networks. Journal of Informetrics, 4(4), 629–635. https://doi.org/10.1016/j.joi.2010.07.002
Weinberg, B. H. (1974). Bibliographic coupling: A review. Information Storage and Retrieval, 10(5), 189–196. https://doi.org/10.1016/0020-0271(74)90058-8
Weinburgh, M. (1995). Gender differences in student attitudes toward science: A meta-analysis of the literature from 1970 to 1991. Journal of Research in Science Teaching, 32(4), 387–398. https://doi.org/10.1002/tea.3660320407
West, J. D., Jacquet, J., King, M. M., Correll, S. J., & Bergstrom, C. T. (2013). The Role of Gender in Scholarly Authorship. PLoS ONE, 8(7), e66212. https://doi.org/10.1371/journal.pone.0066212
Wolfinger, N. H., Mason, M. A., & Goulden, M. (2009). Stay in the Game: Gender, Family Formation and Alternative Trajectories in the Academic Life Course. Social Forces, 87(3), 1591–1621. https://doi.org/10.1353/sof.0.0182
Wright, A. B., & Holttum, S. (2012). Gender identity, research self-efficacy and research intention in trainee clinical psychologists in the UK. Clinical Psychology & Psychotherapy, 19(1), 46–56. https://doi.org/10.1002/cpp.732
Zuckerman, H., & Cole, J. (1975). Women in American Science. Minerva, 13(1), 82–102. https://doi.org/10.1007/BF01096243
Tomassini, C. (2021). Brechas de género en la ciencia: revisión sistemática de las principales explicaciones y agenda de investigación. Education in the Knowledge Society (EKS), 22. https://doi.org/10.14201/eks.25437

Descargas

Los datos de descargas todavía no están disponibles.
+