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Journal articles on the topic 'Educational inequality'

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Published: 4 June 2021
Last updated: 22 June 2024

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1

Hughey, Matthew W. "Educational Inequality." Humanity & Society 39, no. 4 (September 6, 2015): 476–78. http://dx.doi.org/10.1177/0160597615604924.

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2

Azuma, Yoshiaki, and Herschel I. Grossman. "Educational Inequality." Labour 17, no. 3 (September 2003): 317–35. http://dx.doi.org/10.1111/1467-9914.00242.

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3

Mason, Mark. "Educational inequality and educational quality." International Journal of Educational Development 34 (January 2014): 1–2. http://dx.doi.org/10.1016/j.ijedudev.2013.11.002.

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4

McGrath, Simon. "Addressing educational inequality." International Journal of Educational Development 30, no. 2 (March 2010): 119–20. http://dx.doi.org/10.1016/j.ijedudev.2009.11.002.

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5

Lu, Siyuan. "Correlation between Educational Inequality and Income Inequality." BCP Education & Psychology 7 (November 7, 2022): 400–403. http://dx.doi.org/10.54691/bcpep.v7i.2694.

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The study of the relationship between education and income inequality is not a new topic, and scholars have been concerned with this issue for a long time. For the sake of social equity and poverty alleviation, governments should strengthen education for the poor. In recent years, with new advances in theories of economic growth and economic development and the emergence of new data, academic interest in the issue of income distribution has begun to grow again, focusing mainly on the determinants and dynamics of income distribution. Among them, the relationship between education and income inequality, which is an important form of human capital accumulation, has naturally become a hot issue in economics. This paper summarizes and reviews the recent studies on the relationship between education and income inequality from both theoretical and empirical perspectives.
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Schlicht-Schmälzle, Raphaela, and Kathrin Ackermann. "Logics of Educational Stratification: A Cross-National Map of Educational Inequality." ISRN Education 2012 (March 26, 2012): 1–11. http://dx.doi.org/10.5402/2012/109647.

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Equality of education is often seen as the fundament of the overall equality of opportunity in modern societies. However, no reliable and comprehensive cross-national comparison of educational inequality hitherto exists. The aim of the present paper is to provide a cross-national comparative outline of diverse dimensions of educational inequality in the OECD world. We estimate the effects of three highly influential aspects of socioeconomic background on educational achievement in each OECD country in order to create a ranking of educational inequality in 30 capitalist countries. The central finding is that we indeed cannot identify a single cross-national ranking but three dimensions of education inequality: educational inequality based on economic, educational, and migration background at home. Capitalist economies thus do not only differ with regard to the degree of inequality but, first and foremost concerning the predominant patterns of inequality and the main distributive keys.
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7

Moore, Spencer, Mark Daniel, and Yan Kestens. "IS EDUCATIONAL INEQUALITY PROTECTIVE?" American Journal of Public Health 97, no. 1 (January 2007): 8–9. http://dx.doi.org/10.2105/ajph.2006.101618.

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8

BLANDEN, JO, and LINDSEY MACMILLAN. "Educational Inequality, Educational Expansion and Intergenerational Mobility." Journal of Social Policy 45, no. 4 (May 4, 2016): 589–614. http://dx.doi.org/10.1017/s004727941600026x.

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AbstractThe distribution of education by social background and the mobility prospects of society are intimately connected. To begin to predict future trends in mobility in the UK we bring together evidence on educational inequality by family background for cohorts from 1958 to 2000 for a range of educational outcomes. There is evidence that educational inequalities have narrowed among recent cohorts as the overall level of educational achievement has increased. This could be promising for mobility provided the labour market returns to these qualifications are maintained. However, stubborn inequalities by background at higher attainment levels imply that narrowing inequalities and expanding equality of opportunity throughout the educational distribution is a difficult task.
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9

Simangunsong, Humala, Baldry Pitre Stewart, and Debortoli Debortoli. "The Impact of Economic Inequality on Social Disparities: A Quantitative Analysis." Jurnal Sosial, Sains, Terapan dan Riset (Sosateris) 11, no. 2 (June 30, 2023): 122–30. http://dx.doi.org/10.35335/mdjzzw52.

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This quantitative study examines the complex relationship between economic inequality and social inequities, focusing on educational attainment. The study examines how Gini coefficient-measured economic disparity affects educational attainment in hypothetical countries. This study uses a linear regression model to examine how economic inequality affects social outcomes. A statistically substantial positive correlation exists between the Gini coefficient and educational attainment discrepancy. Educational attainment disparity increases by 2.5 years per unit rise in the Gini coefficient, according to the calculated coefficient. This supports the idea that economic inequality increases education gaps, prolonging cycles of disadvantage for vulnerable populations. The study underlines the intricacy of these processes by conceding that regression analysis cannot prove causation. Economic inequality affects educational attainment disparity through policy frameworks, institutional structures, and cultural norms. This highlights the necessity for extensive policy responses to address these issues. The policy ramifications of this study are significant. The findings emphasize the need for fair access to quality education, especially for disadvantaged communities. Targeted actions are needed to reduce economic inequality's impact on education and promote inclusivity. This study examined educational attainment, but its approach and findings are important. The association between economic inequality and social differences is multifaceted, begging for further study. This study adds to the debate between economic inequality and social inequality. This study emphasizes the need for educated and context-sensitive strategies to reduce gaps, enhance social mobility, and create more equitable society as societies face inequality.
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Dey, Anindita. "Gender Inequality in Educational Expenditure in India." International Journal of Science and Research (IJSR) 13, no. 5 (May 5, 2024): 1381–83. http://dx.doi.org/10.21275/sr24522210929.

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11

BLANDEN, JO, and LINDSEY MACMILLAN. "Educational Inequality, Educational Expansion and Intergenerational Mobility – CORRIGENDUM." Journal of Social Policy 45, no. 4 (May 25, 2016): 615. http://dx.doi.org/10.1017/s0047279416000350.

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12

Park, Kang H. "Educational expansion and educational inequality on income distribution." Economics of Education Review 15, no. 1 (February 1996): 51–58. http://dx.doi.org/10.1016/0272-7757(95)00000-3.

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13

Billon, Margarita, Jorge Crespo, and Fernando Lera-López. "Educational inequalities." Information Development 34, no. 5 (August 17, 2017): 447–59. http://dx.doi.org/10.1177/0266666917720968.

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This paper examines the impact of Internet use on economic growth and the extent to which educational inequality modulates this impact for a panel data set of 94 countries between 1995 and 2010. We obtain a positive and significant impact of Internet use on economic growth and a negative influence of educational inequality on the Internet’s impact on growth. When we disaggregate by income levels, the results indicate that Internet use is positively associated with economic growth for middle- and high-income countries. Educational inequality influences the impact of Internet use on economic growth only for middle- and low-income countries, although with the opposite sign. For middle-income countries, the impact is negative, while the impact is positive for low-income economies. The research provides evidence for the first time about how inequalities in education may limit the positive economic outcomes and benefits derived from the use of information and communication technologies.
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14

Tang, Rongsheng, and Gaowang Wang. "Educational mismatch and income inequality." Economic Modelling 100 (July 2021): 105525. http://dx.doi.org/10.1016/j.econmod.2021.105525.

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15

Eremin, S. V. "EDUCATIONAL INEQUALITY IN RURAL AREAS." Russian Peasant Studies 6, no. 3 (2021): 124–34. http://dx.doi.org/10.22394/2500-1809-2021-6-3-124-134.

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16

Below, Susanne von, Justin J. W. Powell, and Lance W. Roberts. "Educational Systems and Rising Inequality." Sociology of Education 86, no. 4 (September 10, 2013): 362–75. http://dx.doi.org/10.1177/0038040713496585.

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17

Quarles, Christopher L., Ceren Budak, and Paul Resnick. "The shape of educational inequality." Science Advances 6, no. 29 (July 2020): eaaz5954. http://dx.doi.org/10.1126/sciadv.aaz5954.

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Hundreds of thousands of students drop out of school each year in the United States, despite billions of dollars of funding and myriad educational reforms. Existing research tends to look at the effect of easily measurable student characteristics. However, a vast number of harder-to-measure student traits, skills, and resources affect educational success. We present a conceptual framework for the cumulative effect of all factors, which we call student capital. We develop a method for estimating student capital in groups of students and find that student capital is distributed exponentially in each of 140 cohorts of community college students. Students’ ability to be successful does not behave like standard tests of intelligence. Instead, it acts like a limited resource, distributed unequally. The results suggest that rather than removing barriers related to easily measured characteristics, interventions should be focused on building up the skills and resources needed to be successful in school.
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18

Howie, Maureen. "Educational inequality: closing the gap." Educational Research and Evaluation 25, no. 5-6 (August 18, 2019): 325–28. http://dx.doi.org/10.1080/13803611.2020.1730085.

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19

Schlicht, Raphaela, Isabelle Stadelmann-Steffen, and Markus Freitag. "Educational Inequality in the EU." European Union Politics 11, no. 1 (February 24, 2010): 29–59. http://dx.doi.org/10.1177/1465116509346387.

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20

Hendel, Igal, Joel Shapiro, and Paul Willen. "Educational opportunity and income inequality." Journal of Public Economics 89, no. 5-6 (June 2005): 841–70. http://dx.doi.org/10.1016/j.jpubeco.2004.11.004.

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21

Riedel, Cornelia, and Hartmut Ditton. "Educational Inequality During Primary School." Procedia - Social and Behavioral Sciences 106 (December 2013): 964–69. http://dx.doi.org/10.1016/j.sbspro.2013.12.109.

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22

Graetz, Brian. "Cohort changes in educational inequality." Social Science Research 16, no. 4 (December 1987): 329–44. http://dx.doi.org/10.1016/0049-089x(87)90007-x.

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23

Pappu, Rekha, and D. Vasanta. "Educational Quality and Social Inequality." Contemporary Education Dialogue 7, no. 1 (January 2010): 94–117. http://dx.doi.org/10.1177/0973184913411201.

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24

Cullen, Kairen. "Educational Inequality: Closing the gap." DECP Debate 1, no. 177 (March 2021): 33.1–33. http://dx.doi.org/10.53841/bpsdeb.2021.1.177.33.

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25

Wei, Yehua Dennis, Weiye Xiao, Christopher A. Simon, Baodong Liu, and Yongmei Ni. "Neighborhood, race and educational inequality." Cities 73 (March 2018): 1–13. http://dx.doi.org/10.1016/j.cities.2017.09.013.

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26

Wardhana, Adhitya, Bayu Kharisma, and Nurul S. J. "KETIMPANGAN PENDIDIKAN DAN PENDAPATAN DI INDONESIA." Bina Ekonomi 23, no. 1 (April 29, 2020): 29–38. http://dx.doi.org/10.26593/be.v23i1.3886.29-38.

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AbstractThis study aims to determine the factors of educational and income inequality decreased in Indonesia. Several factors affect education inequality and income inequality such as government spending in education and urbanization. The data used are secondary data in the form of panels for the period 2010 to 2017 as many as 33 provinces in Indonesia. The research method used is 2SLS (two stage least squares) with fixed effects selected as the best parameter estimation method. The results of this study explain income inequality is influenced by education inequality variables and income inequality lag, which is significantly positive while per capita economic growth and urbanization variables do not have a significant effect on income inequality that occurs in Indonesia. While educational inequality is influenced by government spending in education and urbanization with a significant negative effect and lag of educational inequality has a significant positive effect on educational inequality. The income inequality has an insignificant effect on educational inequality.Keywords: income inequality; educational inequality; 2SLS
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27

Mayer, Susan E. "The relationship between income inequality and inequality in schooling." Theory and Research in Education 8, no. 1 (March 2010): 5–20. http://dx.doi.org/10.1177/1477878509356346.

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Children of affluent parents get more schooling than children of poor parents, which seems to imply that reducing income inequality would reduce inequality in schooling. Similarly, one of the best predictors of an individual’s income is his educational attainment, which seems to imply that reducing inequality in schooling will reduce income inequality. Economic theory predicts that all else being equal an increase in income inequality will lead to an increase in inequality of educational attainment. Empirical estimates suggest that when income inequality increased in the United States so did inequality in educational attainment. But changes in government education policies reduced the impact of the increase in income inequality on inequality in schooling. Economic theory also predicts that all else being equal an increase in inequality of educational attainment will result in greater inequality of earnings. But unequal schooling does not account for much of the variance in income, so equalizing schooling will do little to reduce the overall variation in economic success among adults.
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28

Checchi, Daniele, and Herman G. van de Werfhorst. "Policies, skills and earnings: how educational inequality affects earnings inequality." Socio-Economic Review 16, no. 1 (February 20, 2017): 137–60. http://dx.doi.org/10.1093/ser/mwx008.

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29

Yang, Jun, Xiao Huang, and Xiaoyu Li. "Educational inequality and income inequality: An empirical study on China." Frontiers of Education in China 4, no. 3 (August 5, 2009): 413–34. http://dx.doi.org/10.1007/s11516-009-0022-1.

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30

Cheema, Ahmed Raza, Shanza Ghaffar, Jabbar Ul-Haq, and Qazi Muhammad Adnan Hye. "Does educational inequality lead to income inequality? Evidence from Pakistan." Edelweiss Applied Science and Technology 7, no. 2 (December 14, 2023): 154–63. http://dx.doi.org/10.55214/25768484.v7i2.404.

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One of the main issues that developing nations like Pakistan are dealing with is income inequality. Education, inter Alia, plays a key role in reducing income inequality. Theoretically, in developing countries, it is anticipated that there exist two groups: the bourgeoisie (have) and the proletariat (have not), as suggested by Karl Marx, and there is an educational difference between these two groups, and Pakistan is no exception. This study aims to investigate the impact of educational inequality on income inequality at the provincial level of Pakistan with a rural-urban break up for the period from 1998-99 to 2018-19 (pooled data). Keeping in view the nature of the data, panel data techniques are applied. Appropriate tests (i.e., the F-test and the Hausman Specification test) suggest that Fixed Effect Model is the preferred model. The results show that there is a statistically significant positive link between educational inequality and income inequality. The results are robust to various proxies of educational inequality and income inequality (i.e., Gini coefficient, Generalized Entropy, and Atkinson Index) as well as to control variables (i.e., income and poverty). Further, the study found the negative relation between income and income inequality to be statistically significant, indicating that an increase in income leads to a decrease in income inequality. Moreover, the impact of poverty on income inequality is positive and statistically significant. The policy insinuation is that the government should focus on reducing educational inequality to reduce income inequality in Pakistan.
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31

Liu, Yipeng. "Educational Inequality in the Context of China's Educational Expansion." Lecture Notes in Education Psychology and Public Media 52, no. 1 (May 13, 2024): 46–53. http://dx.doi.org/10.54254/2753-7048/52/20241515.

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Since the conclusion of World War II, the topic of educational growth has garnered global interest, including in China. While the education expansion program has given several benefits and advantages to China, there are still many faults in the strategy. This paper examines the issue of educational inequality within the framework of educational growth in China. The paper examines educational inequity in China within the framework of educational growth, focusing on four key areas: educational inequity stemming from socio-economic factors, urban-rural disparities, insufficient secondary education, and gender disparities. After examining the aforementioned factors, this study asserts that the issue of educational inequality persists and proves to be particularly challenging to eradicate in certain areas, such as socio-economic disparity. Based on this, this paper puts forward the following suggestions. First, the government needs to increase spending on education. Second, attention should be paid to improving the balance of educational distribution. Finally, there is a need to close the gender gap in higher education. These guidelines are the best alternative to achieving equality in education.
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32

Zhou, Peng, Fengwen Chen, Wei Wang, Peixin Song, and Chenliang Zhu. "Does the Development of Information and Communication Technology and Transportation Infrastructure Affect China’s Educational Inequality?" Sustainability 11, no. 9 (May 1, 2019): 2535. http://dx.doi.org/10.3390/su11092535.

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Educational inequality is an important factor in the development of human capital, and limits the output of regional economic activities. The unequal distribution of educational resources has become a hot topic noticed by the public, and has restricted sustainable economic growth. This paper provides a better understanding of educational inequality, and explores the impacts of information and communication technology (ICT) and transportation infrastructure on the distribution of educational resources. The panel data models are constructed to discuss the relationship among ICT, transportation infrastructure, and educational inequality, using the data of 31 provinces in China from 2006 to 2016. The empirical results show that there is a positive relationship between ICT and educational inequality, while transportation infrastructure can restrain the unequal distribution of educational resources. Moreover, there is a significant inverted U-shaped relationship between transportation infrastructure and educational inequality. Since China’s education reform in 2010, the relationship among ICT, transportation infrastructure, and educational inequality has been significantly changed, as well as the influence mechanism of ICT. In addition, transportation infrastructure in China western regions can effectively alleviate the problem of educational inequality, and its impact will increase with the growth of transportation investments. It is necessary to consider the rational allocation of educational resources, and this is essential to relieve the problem of educational inequality. Therefore, our results demonstrate the key roles of information technology and transportation network in the field of education, and provide some new ideas for the solution of educational inequality.
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33

Kim, jiyoun, and Soon-Yong Pak. "A Study on the Changes in Educational Inequalities amidst the Expansion of Higher Education Opportunities: A Systematic Review of Korean Literature." Institute for Educational Research 35, no. 4 (December 31, 2022): 79–108. http://dx.doi.org/10.35283/erft.2022.35.4.79.

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The purpose of this study is to comprehensively review the patterns and mechanisms of educational inequalities that have changed in the context of expanding and diversifying accessibility to higher education since the 1990s. Undergoing systematic literature review, the researchers selected 38 documents that dealt with the theme on educational inequality, and then proceeded to analyze and integrate the findings. First, educational inequality was found to coexist in two types: vertical inequality and horizontal inequality. The impact of parents' socioeconomic status on children's academic achievement increased, as the educational gap between socioeconomic classes widened. Second, as a factor of deepening educational inequality, the lower the parents' socioeconomic status, the less investment were made in private education, and the formation of social and cultural capital that promotes academic achievement was also low. This study expanded the understanding of educational inequalities in Korea by systematically integrating research on educational inequality, and based on the findings, suggested measures to alleviate educational inequality.
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34

Munir, Kashif, and Ayesha Kanwal. "Impact of educational and gender inequality on income and income inequality in South Asian countries." International Journal of Social Economics 47, no. 8 (July 29, 2020): 1043–62. http://dx.doi.org/10.1108/ijse-04-2020-0226.

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PurposeThe objectives of this study are threefold: firstly, to measure the impact of educational inequality on income inequality, and per capita income; secondly, to measure the impact of gender inequality in education on income inequality, per capita income and educational inequality; and lastly, to test the Kuznets inverted U-shape hypothesis between inequality in education and average year of schooling.Design/methodology/approachThe study has adopted the Marin and Psacharopoulos (1976) model of human capital in which income earned by an individual can be estimated as a function of number of year spent in schooling or education. Gini coefficient is used as a measure of income inequality, while inequality in education is measured by Gini index of educational inequality. Gender inequality in education is measured by the difference between male and female enrolment ratios as a proportion of male enrolment. The study utilizes the data of six South Asian countries, i.e. Bangladesh, India, Maldives, Nepal, Pakistan and Sri Lanka from 1980 to 2010 at five-year average and employs fixed effect model (FEM) and random effect model (REM) for estimation.FindingsResult suggests that educational inequality and average year of schooling have positive and significant impact on income inequality. Primary (basic) education and tertiary (higher) education reduce income inequality, while secondary education widens income inequality. Negative relationship exists between educational inequality and per capita income. Unequal distribution of education among boys and girls at primary level increases income inequality, while reduces income inequality at tertiary level. Gender inequality in secondary and tertiary level of education reduces per capita income, while unequal distribution of education among boys and girls further increases the educational inequality. Kuznets inverted U-shape hypothesis does not hold between education expansion and educational inequality, while weak U-shape relationship exists in South Asian countries.Practical implicationsGovernment has to provide free education in poor regions and makes employment programs to reduce the income and educational inequality respectively, while to remove gender inequality in education it is necessary to build more schools especially for girls. Government has to launch different online education programs for expansion in education at all levels.Originality/valueThis study adds to the literature by analyzing whether the inequality in income increases (decreases) due to increase (decrease) in educational and gender inequality in South Asian countries. This study contributes in the existing literature by developing a measure of educational and gender inequality in education in South Asian countries.Peer review The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-04-2020-0226.
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35

Xiong, Yixuan. "Analysis of Educational Inequality in China." Lecture Notes in Education Psychology and Public Media 18, no. 1 (October 26, 2023): 139–46. http://dx.doi.org/10.54254/2753-7048/18/20231306.

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Economic development should be based on talents. Education is the foundation of a countrys centennial plan. The quality of education development is related to the destiny of a countrys development. At present, the problem of educational inequality in China is obvious, and the talents cultivated under the educational management system can no longer meet the needs of Chinas social development. In order to promote the balanced development of education from the perspectives of the government, families, individuals, and schools, the paper proposes appropriate solutions and analyses the current situation of educational inequality in China and the factors that cause it from various angles. The paper also takes educational inequality in China as its research theme. The conclusions of this study have reference value for solving educational inequality, providing reference for government decision-making, further promoting the improvement of Chinas education system and promoting education equality in urban and rural areas, regions and gender.
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36

Gross, Stefan. "Inequality and Emancipation : An Educational Approach." Journal of Education and Research 2 (February 12, 2013): 9–16. http://dx.doi.org/10.3126/jer.v2i0.7617.

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Emancipation has lost its charisma. In the 1960s, the term had been one of the saviour-concepts in the educational debate on social inequality and the political function of pedagogy in Western countries. Nowadays, as the discussion is still ongoing, the word is rarely in use. Overloaded with political enmeshments and a plurality of meanings, emancipation seems to be nothing more than a nearly forgotten relict of an ancient time. How could this rise and fall happen? The present essay is tracing the colourful history of emancipation in various contexts, recapitulating its pedagogical importance in the 1960s and discovering how the pillars have kept their primary function, although the word is not in use any longer. DOI: http://dx.doi.org/10.3126/jer.v2i0.7617 Journal of Education and Research Vol. 2, 2010 p.9-16
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37

Merle, Pierre. "Democratization or Increase in Educational Inequality?" Population (english edition) 57, no. 4 (2002): 631. http://dx.doi.org/10.3917/pope.204.0631.

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38

Zinchenko, Daria, and Anna Lukiyanova. "Educational Assortative Mating and Income Inequality." Higher School of Economics Economic Journal 22, no. 2 (2018): 169–96. http://dx.doi.org/10.17323/1813-8691-2018-22-2-169-196.

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39

Fiel, Jeremy E. "The Transmission of Multigenerational Educational Inequality." Social Forces 97, no. 4 (August 23, 2018): 1455–86. http://dx.doi.org/10.1093/sf/soy090.

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40

Richards, Colin. "Educational inequality in English primary education." Education 3-13 36, no. 4 (November 2008): 365–70. http://dx.doi.org/10.1080/03004270801959239.

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41

McKeever, Matthew. "Educational Inequality in Apartheid South Africa." American Behavioral Scientist 61, no. 1 (January 2017): 114–31. http://dx.doi.org/10.1177/0002764216682988.

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In this article, I explore the utility of effectively maintained inequality theory in examining educational inequality in South Africa at the end of the apartheid era. As an obviously unequal country, South Africa provides an excellent opportunity to test the claim that even with large quantitative differences in achievement, qualitative differences will matter. Using data from the early 1990s, I find that there were extensive quantitative differences in secondary school transitions across respondents in different racial categories. The minority White population was consistently able to achieve both more and better education. At the same time, though, qualitative distinctions mattered. For the majority of the population, particularly Africans, the quality of education attained varied across parental background. These outcomes are important not only for examining the veracity of effectively maintained inequality, both in terms of racial and class differences but also because they illustrate how educational differences have served to perpetuate inequality over time in a society that no longer allows for the explicit denial of opportunity by race.
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42

Holm, Anders, Anders Hjorth-Trolle, and Mads Meier Jæger. "Signals, Educational Decision-Making, and Inequality." European Sociological Review 35, no. 4 (March 14, 2019): 447–60. http://dx.doi.org/10.1093/esr/jcz010.

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Abstract We propose a model of educational decision-making based on rational choice theory in which students use signals about academic ability to make inference about the costs and benefits of different educational options. Our model is simple, extends ideas from previous models, and has testable implications. We test our model using data on Danish monozygotic twins and find that (i) students who receive a positive signal about their academic ability have a higher likelihood of enrolling in and completing a college-bound track compared with those who do not; (ii) the effect of the signal is stronger for students from low socio-economic status (SES) backgrounds than for those from high-SES ones; and (iii) for low-SES students the effect is stronger on enrolment than on completion. Our results suggest that signals about academic ability affect educational decisions in general; they are more important for students who do not have a family ‘push’ to avoid downward social mobility; and they affect educational inequality by making low-SES students too optimistic about their likelihood of completing the college-bound track.
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43

Groß, Martin. "Educational systems and perceived social inequality." European Societies 5, no. 2 (January 2003): 193–225. http://dx.doi.org/10.1080/1461669032000076892.

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44

Herd, Pamela, Jeremy Freese, Kamil Sicinski, Benjamin W. Domingue, Kathleen Mullan Harris, Caiping Wei, and Robert M. Hauser. "Genes, Gender Inequality, and Educational Attainment." American Sociological Review 84, no. 6 (November 22, 2019): 1069–98. http://dx.doi.org/10.1177/0003122419886550.

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Women’s opportunities have been profoundly altered over the past century by reductions in the social and structural constraints that limit women’s educational attainment. Do social constraints manifest as a suppressing influence on genetic indicators of potential, and if so, did equalizing opportunity mean equalizing the role of genetics? We address this with three cohort studies: the Wisconsin Longitudinal Study (WLS; birth years 1939 to 1940), the Health and Retirement Study, and the National Longitudinal Study of Adolescent Health (Add Health; birth years 1975 to 1982). These studies include a “polygenic score” for educational attainment, providing a novel opportunity to explore this question. We find that within the WLS cohort, the relationship between genetics and educational outcomes is weaker for women than for men. However, as opportunities changed in the 1970s and 1980s, and many middle-aged women went back to school, the relationship between genetic factors and education strengthened for women as they aged. Furthermore, utilizing the HRS and Add Health, we find that as constraints limiting women’s educational attainment declined, gender differences in the relationship between genetics and educational outcomes weakened. We demonstrate that genetic influence must be understood through the lens of historical change, the life course, and social structures like gender.
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45

Meschi, Elena, and Francesco Scervini. "A new dataset on educational inequality." Empirical Economics 47, no. 2 (November 20, 2013): 695–716. http://dx.doi.org/10.1007/s00181-013-0758-6.

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46

Maksvytienė, Inga, and Sandra Polgrimaitė. "Evaluation of Educational Inequality in Lithuania." Applied Economics: Systematic Research 9, no. 1 (2015): 143–56. http://dx.doi.org/10.7220/aesr.2335.8742.2015.9.1.9.

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47

Papay, John P., Richard J. Murnane, and John B. Willett. "Income-Based Inequality in Educational Outcomes." Educational Evaluation and Policy Analysis 37, no. 1_suppl (May 2015): 29S—52S. http://dx.doi.org/10.3102/0162373715576364.

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Ivaniushina, Valeria, and Elena Williams. "Tracking, School Mobility, and Educational Inequality." Voprosy obrazovaniya / Educational Studies Moscow, no. 4 (December 2019): 47–70. http://dx.doi.org/10.17323/1814-9545-2019-4-47-70.

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Perry, Laura B. "Using PISA to examine educational inequality." ORBIS SCHOLAE 2, no. 2 (February 23, 2018): 77–86. http://dx.doi.org/10.14712/23363177.2018.235.

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50

Aronowitz, Stanley. "A Different Perspective on Educational Inequality." Review of Education, Pedagogy, and Cultural Studies 16, no. 2 (January 1994): 135–51. http://dx.doi.org/10.1080/1071441940160203.

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