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      Countries with Higher Levels of Gender Equality Show Larger National Sex Differences in Mathematics Anxiety and Relatively Lower Parental Mathematics Valuation for Girls

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          Abstract

          Despite international advancements in gender equality across a variety of societal domains, the underrepresentation of girls and women in Science, Technology, Engineering, and Mathematics (STEM) related fields persists. In this study, we explored the possibility that the sex difference in mathematics anxiety contributes to this disparity. More specifically, we tested a number of predictions from the prominent gender stratification model, which is the leading psychological theory of cross-national patterns of sex differences in mathematics anxiety and performance. To this end, we analyzed data from 761,655 15-year old students across 68 nations who participated in the Programme for International Student Assessment (PISA). Most importantly and contra predictions, we showed that economically developed and more gender equal countries have a lower overall level of mathematics anxiety, and yet a larger national sex difference in mathematics anxiety relative to less developed countries. Further, although relatively more mothers work in STEM fields in more developed countries, these parents valued, on average, mathematical competence more in their sons than their daughters. The proportion of mothers working in STEM was unrelated to sex differences in mathematics anxiety or performance. We propose that the gender stratification model fails to account for these national patterns and that an alternative model is needed. In the discussion, we suggest how an interaction between socio-cultural values and sex-specific psychological traits can better explain these patterns. We also discuss implications for policies aiming to increase girls’ STEM participation.

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          Most cited references 60

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          The gender similarities hypothesis.

           Janet Hyde (2005)
          The differences model, which argues that males and females are vastly different psychologically, dominates the popular media. Here, the author advances a very different view, the gender similarities hypothesis, which holds that males and females are similar on most, but not all, psychological variables. Results from a review of 46 meta-analyses support the gender similarities hypothesis. Gender differences can vary substantially in magnitude at different ages and depend on the context in which measurement occurs. Overinflated claims of gender differences carry substantial costs in areas such as the workplace and relationships. Copyright (c) 2005 APA, all rights reserved.
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            The Nature, Effects, and Relief of Mathematics Anxiety

             Ray Hembree (1990)
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              Cross-national patterns of gender differences in mathematics: a meta-analysis.

              A gender gap in mathematics achievement persists in some nations but not in others. In light of the underrepresentation of women in careers in science, technology, mathematics, and engineering, increasing research attention is being devoted to understanding gender differences in mathematics achievement, attitudes, and affect. The gender stratification hypothesis maintains that such gender differences are closely related to cultural variations in opportunity structures for girls and women. We meta-analyzed 2 major international data sets, the 2003 Trends in International Mathematics and Science Study and the Programme for International Student Assessment, representing 493,495 students 14-16 years of age, to estimate the magnitude of gender differences in mathematics achievement, attitudes, and affect across 69 nations throughout the world. Consistent with the gender similarities hypothesis, all of the mean effect sizes in mathematics achievement were very small (d < 0.15); however, national effect sizes showed considerable variability (ds = -0.42 to 0.40). Despite gender similarities in achievement, boys reported more positive math attitudes and affect (ds = 0.10 to 0.33); national effect sizes ranged from d = -0.61 to 0.89. In contrast to those of previous tests of the gender stratification hypothesis, our results point to specific domains of gender equity responsible for gender gaps in math. Gender equity in school enrollment, women's share of research jobs, and women's parliamentary representation were the most powerful predictors of cross-national variability in gender gaps in math. Results are situated within the context of existing research demonstrating apparently paradoxical effects of societal gender equity and highlight the significance of increasing girls' and women's agency cross-nationally.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                2016
                21 April 2016
                : 11
                : 4
                Affiliations
                [1 ]School of Education, University of Glasgow, Glasgow, Scotland, United Kingdom
                [2 ]School of Education, University of California Irvine, Irvine, CA, United States of America
                [3 ]Department of Psychological Sciences, University of Missouri, Columbia, MO, United States of America
                Goethe-Universitat Frankfurt am Main, GERMANY
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Analyzed the data: GS DB. Wrote the paper: GS DB AM DG.

                Article
                PONE-D-15-40441
                10.1371/journal.pone.0153857
                4839696
                27100631
                9238cd93-2153-41dd-a8e5-f90debc4d81b
                © 2016 Stoet et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                Page count
                Figures: 3, Tables: 4, Pages: 24
                Product
                Funding
                Funded by: funder-id http://dx.doi.org/10.13039/501100000853, University Of Glasgow;
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/501100000853, University Of Glasgow;
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/501100000853, University Of Glasgow;
                Award Recipient :
                The University of Glasgow supported Gijsbert Stoet, Drew H. Bailey, and David C. Geary with an “International Partnership Development Funding (IPDF).” The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Social Sciences
                Sociology
                Education
                Schools
                Biology and Life Sciences
                Psychology
                Emotions
                Anxiety
                Social Sciences
                Psychology
                Emotions
                Anxiety
                People and Places
                Population Groupings
                Age Groups
                Children
                People and Places
                Population Groupings
                Families
                Children
                People and Places
                Population Groupings
                Families
                Mothers
                Social Sciences
                Economics
                Labor Economics
                Employment
                Careers
                Research and Analysis Methods
                Mathematical and Statistical Techniques
                Mathematical Models
                Social Sciences
                Economics
                Labor Economics
                Employment
                Jobs
                People and Places
                Population Groupings
                Professions
                Custom metadata
                All PISA data are available via https://www.oecd.org/pisa/pisaproducts/. This website has also links to the manuals for statistical data analysis.

                Uncategorized

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