Studies of gender disparities in STEM (science, technology, engineering, and mathematics) performance have generally focused on average differences. However, the extremes could also be important because disparities at the top may shape stratification in access to STEM careers, while disparities at the bottom can shape stratification in dropout. This article investigates determinants of gender disparities in math across the performance distribution in Latin American countries, where there is a persistent boys’ advantage in STEM performance. Findings reveal disparate national patterns in gender gaps across the performance distribution. Furthermore, while certain national characteristics are linked to gender gaps at the low- and middle-ranges of the performance distribution, female representation in education is the only characteristic associated with a reduced gender gap at the top level.
AbadíaL. K. (2017). Gender score gaps of Colombian students in the PISA test. Vniversitas Economica, 17(8), 1–24.
2.
AbadíaL. K.BernalG. (2017). A widening gap? A gender-based analysis of performance on the Colombian high school exit examination. Revista de Economia Del Rosario, 20(1), 5–31. doi:10.12804/revistas.urosario.edu.co/economia/a.6144
ArcidiaconoM.CrucesG.GaspariniL.JaumeD.SerioM.VazquezE. (2014). La segregacion escolar publico-privada en America LATINA [Public-private school segregation in Latin America] (No. 195). Santiago, Chile: Publicación de las Naciones Unidas.
5.
AyalonH.LivnehI. (2013). Educational standardization and gender differences in mathematics achievement: A comparative study. Social Science Research, 42, 432–445. doi:10.1016/j.ssresearch.2012.10.001
6.
BakerD. P.LeTendreG. K. (2005). National differences, global similarities: World culture and the future of schooling. Palo Alto, CA: Stanford University Press.
7.
BakerD. P.JonesD. P. (1993). Creating gender equality: Cross-national gender stratification and mathematical performance. Sociology of Education, 66, 91–103. doi:10.2307/2112795
8.
BayeA.MonseurC. (2016). Gender differences in variability and extreme scores in an international context. Large-Scale Assessments in Education, 4(1). doi:10.1186/s40536-015-0015-x
9.
BolT.Van de WerfhorstH. G. (2013). The measurement of tracking, vocational orientation, and standardization of educational systems: A comparative approach (GINI Discussion Paper No. 81, p. 63). Retrieved from http://archive.uva-aias.net/uploaded_files/publications/81-3-3-1.pdf
10.
CeronF. I. (2016). Beyond school effects: The impact of privatization and standardization of school systems on achievement inequality in Latin America. SSRN Electronic Journal. doi: 10.2139/ssrn.2885223
11.
CharlesM.HarrB.CechE.HendleyA. (2014). Who likes math where? Gender differences in eighth-graders’ attitudes around the world. International Studies in Sociology of Education, 24, 85–112. doi:10.1080/09620214.2014.895140
12.
DuncanO. D.DuncanB. (1955). A methodological analysis of segregation indexes. American Sociological Review, 20, 210–217. doi:10.2307/2088328
13.
Else-QuestN. M.HamiltonV. (2018). Measurement and analysis of nation-level gender equity in the psychology of women. In TravisC. BWhiteJ. W.RutherfordA.WilliamsW. S.CookS. L.WycheK. F. (Eds.), APA handbooks in psychology series. APA handbook of the psychology of women: Perspectives on women’s private and public lives (pp. 545–563). Washington, DC: American Psychological Association. doi: 10.1037/0000060-029
14.
Else-QuestN. M.HydeJ. S.LinnM. C. (2010). Cross-national patterns of gender differences in mathematics: A meta-analysis. Psychological Bulletin, 136, 103–127. doi:10.1037/a0018053
15.
FahleE. M.ReardonS. F. (2018). Education. In Stanford Center on Poverty and Inequality (Series Ed.), State of the Union: The poverty and inequality report (pp. 9–12). Palo Alto, CA: Stanford Center on Poverty and Inequality. Retrieved from https://inequality.stanford.edu/sites/default/files/Pathways_SOTU_2018.pdf
16.
FanX.ChenM.MatsumotoA. R.FanX. (1997). Gender differences in mathematics achievement: Findings from the “National Education Longitudinal Study of 1988.”Journal of Experimental Education, 65, 229–242.
17.
FeingoldA. (1992). Sex differences in variability in intellectual abilities: A new look at an old controversy. Review of Educational Research, 62, 61–84. doi:10.2307/1170716
18.
FryerR. G.LevittS. D. (2010). An empirical analysis of the gender gap in Mathematics. American Economic Journal: Applied Economics, 2, 210–240.
GuisoL.MonteF.SapienzaP.ZingalesL. (2008). Culture, gender, and math. Science, 320, 1164–1165.
21.
HanS. W. (2016). National education systems and gender gaps in STEM occupational expectations. International Journal of Educational Development, 49, 175–187. doi:10.1016/j.ijedudev.2016.03.004
22.
HedgesL. V.FriedmanL. (1993). Gender differences in variability in intellectual abilities: A reanalysis of Feingold’s results. Review of Educational Research, 63, 94–105. doi:10.2307/1170561
23.
HedgesL. V.NowellA. (1995). Sex differences in mental test scores, variability, and numbers of high-scoring individuals. Science, 269, 41–45.
24.
HydeJ. S.LindbergS. M.LinnM. C.EllisA. B.WilliamsC. C. (2008). Gender similarities characterize math performance. Science, 321, 494–495. doi:10.1126/science.1160364
25.
HydeJ. S.MertzJ. E. (2009). Gender, culture, and mathematics performance. Proceedings of the National Academy of Sciences of the U S A, 106, 8801–8807. doi:10.1073/pnas.0901265106
26.
InglehartR.NorrisP. (2003). Rising tide: Gender equality and cultural change around the world. Cambridge, England: Cambridge University Press.
27.
JanoszM.LeBlancM.BoulericeB.TremblayR. E. (1997). Disentangling the weight of school dropout predictors: A test on two longitudinal samples. Journal of Youth and Adolescence, 26, 733–762. doi:10.1023/A:1022300826371
28.
JimersonS.EgelandB.SroufeL. A.CarlsonB. (2000). A prospective longitudinal study of high school dropouts examining multiple predictors across development. Journal of School Psychology, 38, 525–549. doi:10.1016/S0022-4405(00)00051-0
29.
LindbergS. M.HydeJ. S.PetersenJ. L.LinnM. C. (2010). New trends in gender and mathematics performance: A meta-analysis. Psychological Bulletin, 136, 1123–1135. doi:10.1037/a0021276
30.
MarteletoL.GelberD.HubertC.SalinasV. (2012). Educational inequalities among Latin American adolescents: Continuities and changes over the 1980s, 1990s and 2000s. Research in Social Stratification and Mobility, 30, 352–375.
31.
MizalaA.TorcheF. (2012). Bringing the schools back in: the stratification of educational achievement in the Chilean voucher system. International Journal of Educational Development, 32, 132–144.
ParkH. (2008). The varied educational effects of parent-child communication: A comparative study of fourteen countries. Comparative Education Review, 52, 219–243. doi:10.1086/528763
34.
PekkarinenT. (2008). Gender differences in educational attainment: Evidence on the role of tracking from a Finnish quasi-experiment. Scandinavian Journal of Economics, 110, 807–825. doi:10.1111/j.1467-9442.2008.00562.x
35.
PennerA. M. (2008). Gender differences in extreme mathematical achievement: An international perspective on biological and social factors. American Journal of Sociology, 114(Suppl.), S138–S170.
36.
ReardonS. F.FahleE. M.KalogridesD.PodolskyA.ZárateR. C. (2019). Gender achievement gaps in U.S. school districts. American Educational Research Journal, forthcoming. Advance online publication. doi:10.3102/0002831219843824
37.
Riegle-CrumbC. (2005). The cross-national context of the gender gap in math and science. In HedgesL. V.SchneiderB. (Eds.), The social organization of schooling (pp. 227–243). New York, NY: Russell Sage Foundation.
38.
SikoraJ.PokropekA. (2012). Gender segregation of adolescent science career plans in 50 countries. Science Education, 96, 234–264. doi:10.1002/sce.20479
39.
TorcheF. (2005). Privatization reform and inequality of educational opportunity: The case of Chile. Sociology of Education, 78, 316–343. doi:10.1177/0038040705 07800403
40.
TorcheF. (2010). Economic crisis and inequality of educational opportunity in Latin America. Sociology of Education, 83, 85–110.
41.
TsuiM. (2007). Gender and mathematics achievement in China and the United States. Gender Issues, 24(3), 1–11. doi:10.1007/s12147-007-9044-2
ValverdeG.Näslund-HadleyE. (2011). La condición de la educación en matemáticas y ciencias naturales en América Latina y el Caribe [The condition of education in mathematics and natural sciences in Latin America and the Caribbean]. Retrieved from https://publications.iadb.org/handle/11319/2757
47.
Van de WerfhorstH. G.MijsJ. J. B. (2010). Achievement inequality and the institutional structure of educational systems: A comparative perspective. Annual Review of Sociology, 36, 407–428. doi:10.1146/annurev.soc.012809.102538
48.
WilliamsR. (2005). GOLOGIT2: Stata module to estimate generalized logistic regression models for ordinal dependent variables (Statistical Software Components S453401). Chestnut, MA: Boston College, Department of Economics.
