- Alex Eble
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Books shape how children learn about society and norms, in part through representation of different characters. We introduce new artificial intelligence methods for systematically converting images into data and apply them, along with text analysis methods, to measure the representation of race, gender, and age in award-winning children’s books from the past century. We find that more characters with darker skin color appear over time, but the most influential books persistently depict a greater proportion of light-skinned characters than other books, even after conditioning on race; we also find that children are depicted with lighter skin than adults. Relative to their growing share of the U.S. population, Black and Latinx people are underrepresented in these same books, while White males are overrepresented. Over time, females are increasingly present but appear less often in text than in images, suggesting greater symbolic inclusion in pictures than substantive inclusion in stories. We then report empirical evidence for predictions about the supply of and demand for representation that would generate these patterns. On the demand side, we show that people consume books that center their own identities. On the supply side, we document higher prices for books that center non-dominant social identities and fewer copies of these books in libraries that serve predominantly White communities. Lastly, we show that the types of children’s books purchased in a neighborhood are related to local political beliefs.
How much does family demand matter for child learning in settings of extreme poverty? In rural Gambia, families with high aspirations for their children’s future education and career, measured before children start school, go on to invest substantially more than other families in the early years of their children’s education. Despite this, essentially no children are literate or numerate three years later. When villages receive a highly-impactful, teacher-focused supply-side intervention, however, children of these families are 25 percent more likely to achieve literacy and numeracy than other children in the same village. Furthermore, improved supply enables these children to acquire other higher-level skills necessary for later learning and child development. We also document patterns of substitutability and complementarity between demand and supply in generating learning at varying levels of skill difficulty. Our analysis shows that greater demand can map onto developmentally meaningful learning differences in such settings, but only with adequate complementary inputs on the supply side.
Colleges can send signals about their quality by adopting new, more alluring names. We study how this affects college choice and labor market performance of college graduates. Administrative data show name-changing colleges enroll higher-aptitude students, with larger effects for alluring-but-misleading name changes and among students with less information. A large resume audit study suggests a small premium for new college names in most jobs, and a significant penalty in lower-status jobs. We characterize student and employer beliefs using web-scraped text, surveys, and other data. Our study shows signals designed to change beliefs can have real, lasting impacts on market outcomes.
Aspirations shape important future-oriented behaviors, including educational investment. Higher family aspirations for children predict better educational outcomes in multiple developing countries. Unfortunately, aspirations sometimes outstrip people's ability to pursue them. We study the relationship between family aspirations for children and later child educational outcomes in an extremely poor context. We observe caregivers' educational and career aspirations for thousands of rural Gambian children about to begin schooling. While higher aspirations predict subsequent educational investment and, three years later, better child performance on reading/math tests, these gains are small in terms of skills learned, and high-aspirations children remain far from achieving literacy/numeracy. In contrast, a bundled supply-side intervention generated large literacy/numeracy gains in these areas. Since unobserved correlates of aspirations and educational outcomes likely bias our estimates upwards, the true aspirations-learning relationship may be even smaller. We conclude higher aspirations alone are insufficient to achieve literacy/numeracy in this, and perhaps similar contexts.
We study the transmission of beliefs about gender differences in math ability from adults to children and how this affects girls’ academic performance relative to boys. We exploit randomly assigned variation in the proportion of a child’s middle school classmates whose parents believe boys are innately better than girls at learning math. An increase in exposure to peers whose parents report this belief increases a child’s likelihood of believing it, with similar effects for boys and girls and greater effects from peers of the same gender. This exposure also affects children’s perceived difficulty of math, aspirations, and math performance, generating gains for boys and losses for girls.
Despite large schooling and learning gains in many developing countries, children in highly deprived areas are often unlikely to achieve even basic literacy and numeracy. We study how much of this problem can be resolved using a multi-pronged intervention combining several distinct interventions known to be effective in isolation. We conducted a cluster-randomized trial in The Gambia evaluating a literacy and numeracy intervention designed for primary-aged children in remote parts of poor countries. The intervention combines para teachers delivering after-school supplementary classes, scripted lesson plans, and frequent monitoring focusing on improving teacher practice (coaching). A similar intervention previously demonstrated large learning gains in a cluster-randomized trial in rural India. After three academic years, Gambian children receiving the intervention scored 46 percentage points (3.2 SD) better on a combined literacy and numeracy test than control children. This intervention holds great promise to address low learning levels in other poor, remote settings.
Children routinely benefit from being assigned a teacher who shares an identity with them, such as gender or ethnicity. We study how student beliefs impact teacher-student gender match effects, and how this varies across subjects with different societal beliefs about differential ability by gender. A simple model of belief formation predicts that match effects will be larger for students who believe they are of low ability, and be greater in subjects with more salient societal beliefs. We test these using data from Chinese middle schools, exploiting random assignment of students to teachers. In China, many people believe boys are innately better than girls at math. We find that being assigned a female math teacher helps low-perceived-ability girls and slightly harms low-perceived-ability boys, with no effects for other children. In English and Chinese – subjects with less salient societal beliefs – these patterns persist but diminish. This yields policy implications for the assignment of teachers to students.