Research

Published and Working Papers

“What We Teach About Race and Gender: Representation in Images and Text of Children’s Books” (with A. Eble, E. Harrison, H.B. Runesha, T. Szasz) (November 2023, The Quarterly Journal of Economics)

Books shape how children learn about society and norms, in part through representation of different characters. We use computational tools to characterize representation in children’s books widely read in homes, classrooms, and libraries over the last century, and describe economic forces that may contribute to these patterns. We introduce new artificial intelligence methods for systematically converting images into data. We apply these tools, alongside text analysis methods, to measure skin color, race, gender, and age in the content of these books, documenting what has changed and what has endured over time. We find underrepresentation of Black and Latinx people in the most influential books, relative to their population shares, though representation of Black individuals increases over time. Females are also increasingly present but appear less often in text than in images, suggesting greater symbolic inclusion in pictures than substantive inclusion in stories. Characters in these influential books have lighter average skin color than in other books, even after conditioning on race, and children are depicted with lighter skin color than adults on average. We then present empirical analysis of related economic behavior to better understand the representation we find in these books. On the demand side, we show that people consume books that center their own identities, and that the types of children’s books purchased correlate with local political beliefs. 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.  [Replication Files]         [Slides]         [Twitter Thread]         [Research Brief]         [AI Research Brief (SSN)]         [Video]         [Poster]         [Interactive Figures]         [Google Case Study]        [Brookings Chalkboard]         [IZA Article]       [Press: Time Magazine, School Library Journal, Wall Street Journal, Code Together, Inequalitalks, FutureEd, The 74, Columbia Daily Tribune, ParentData, New York Times, The Economist, Scientific American]         [Recognition: Named one of the ten most significant education studies of 2021 by George Lucas Foundation’s Edutopia, Received the 2021 Early Career Award from the Education Policy Collaborative, Received the first place poster prize at APPAM 2021, Received the 2021 Google Customer Award for Education and the 2021 Google Customer Award for Diversity, Equity & Inclusion, Received the 2023 MindBytes Data Visualization Award, Featured on Best of #econtwitter]

“From Retributive to Restorative: An Alternative Approach to Justice” (with B. Feigenberg, F. Momeni) (September 2023, Revision Invited at American Economic Review)

School districts historically approached conflict-resolution from a zero-sum perspective: suspend students seen as disruptive and potentially harm them, or avoid suspensions and harm their classmates. Restorative practices (RP) — focused on reparation and shared ownership of disciplinary justice — are designed to avoid this trade-off by addressing undesirable behavior without imparting harm. This study examines Chicago Public Schools’ adoption of RP. We identify decreased suspensions, improved school climate, and find no evidence of increased classroom disruption. We estimate a 19% decrease in arrests, including for violent offenses, with reduced arrests outside of school, providing evidence that RP substantively changed behavior.  [Project Webpage]  [Research Brief]   [Short Video]   [Video]   [Slides]  [Press: Washington Post, Education Week, Chalkbeat, WGN TV, WGN (article), WBEZ, WBEZ Reset, Politico Playbook, The Pie podcast, BET, Outside the Loop Radio, Block Club Chicago, Chicago Sun Times (1), Chicago Sun Times (2), WTTW, Restorative Works! Podcast, Hechinger Report, USA Today]

“Residential Segregation and Unequal Access to Local Public Services in India: Evidence from 1.5m Neighborhoods” (with S. Asher ⓡ K. JhaP. NovosadB. Tan) (December 2023, Revision Invited at American Economic Review)

Rapid urbanization in lower-income countries has the potential to cause substantial improvements in well-being, but the residential segregation of marginalized groups could reinforce inequality and limit access to new opportunities. We study residential segregation, access to public services, and economic outcomes across 1.5 million urban and rural neighborhoods for two of India’s marginalized communities: Scheduled Castes (SCs) and Muslims. Levels of urban segregation in India are comparable to Black/White segregation in the United States. Within cities, public facilities and public infrastructure are systematically allocated away from neighborhoods where many Muslims and Schedules Castes live. Nearly all of the regressive allocation is across neighborhoods within cities—at the most informal and least studied form of government. These inequalities are also not visible in the more aggregated data typically used to study unequal service allocation. Children and young adults growing up in marginalized group neighborhoods have less schooling, even after controlling for parent education and household consumption. Unequal access to public services in India’s highly segregated neighborhoods may be a significant contributor to disadvantages faced by marginalized groups.   [Summary]         [Fact Sheet]         [Twitter Summary]        [Press: The Wire, The Indian Express, The Print, GK Today, Counterview, Hindustan Times, Article14]

“Reparative Ripple Effects? Exploring the Impacts of Sibling Exposure to School-Based Restorative Justice” (with B. Feigenberg, F. Momeni) (forthcoming, American Economic Association Papers and Proceedings)

“Tales and Tropes: Gender Roles from Word Embeddings in a Century of Children’s Books” (with P. Chiril, C. Christ, A. DasA. Eble, E. Harrison, H.B. Runesha) (October 2022, Proceedings of the 28th International Conference on Computational Linguistics (COLING))

The manner in which gender is portrayed in materials used to teach children conveys messages about people’s roles in society. In this paper, we measure the gendered depiction of central domains of social life in 100 years of highly influential children’s books. We make two main contributions: (1) we find that the portrayal of gender in these books reproduces traditional gender norms in society, and (2) we publish StoryWords 1.0, the first word embeddings trained on such a large body of children’s literature. We find that, relative to males, females are more likely to be represented in relation to their appearance than in relation to their competence; second, they are more likely to be represented in relation to their role in the family than their role in business. Finally, we find that non-binary or gender-fluid individuals are rarely mentioned. Our analysis advances understanding of the different messages contained in content commonly used to teach children, with immediate applications for practice, policy, and research. [Video]   [Poster]   [Slides]

“Economic and Social Development along the Urban-Rural Continuum: New Opportunities to Inform Policy”
(with A. Cattaneo, D. Brown, L. Christiaensen, D.K. Evans, A. Haakenstad, T. McMenomy, M. Partridge, S. Vaz, D. Weiss) (September 2022, World Development)

The economic and social development of nations relies on their population having physical access to services and employment opportunities. For the vast majority of the 3.4 billion people living in rural locations, this largely depends on their access to urban centers of different sizes. Similarly, urban centers depend on their rural hinterlands. Building on the literature on functional areas/territories and the rural-urban continuum as well as insights from central place theory, this review paper advances the notion of catchment areas differentiated along an urban-to-rural continuum to capture these urban-rural interconnections. It further shows how a new, publicly available data set operationalizing this concept can shed new light on policy making across a series of development fields, including institutions and governance, urbanization and food systems, welfare and poverty, and access to health and education services. Together the insights support a more geographically nuanced perspective on development. [Blog Post with D.K. Evans: Most Out-of-School Children are in Rural Areas. Education Systems Must Serve Them Better.]

“Portrayals of Race and Gender: Sentiment in 100 Years of Children’s Literature” (with C. Christ, A. Das, A. Raj) (June 2022, Proceedings of the ACM SIGCAS/SIGCHI Conference on Computing and Sustainable Societies (ACM COMPASS ’22))

The way that people of different identities are portrayed in children’s books can send subconscious messages about how positively or negatively children should think about people with those identities. These messages can then shape the next generation’s perceptions and attitudes about people, which can have important implications for belief formation and resource allocation. In this paper, we make two contributions: (1) we examine the depiction of race and gender in award-winning children’s books from the last century, and (2) we examine how consumption of these books relates to local beliefs. First, we analyze the sentiment associated with the famous individuals mentioned in these books. While the sentiment surrounding women is positive overall, on average, we see that Black women are more often portrayed with negative sentiment in Mainstream books, while White women are more often portrayed with positive sentiment. Because children’s books in the US depict more White women overall, this disguises the more negative intersectional portrayals of Black women. Books that center underrepresented identities are more likely to portray all characters with more positive sentiment. A century ago, women were much less positively spoken about than men, but the average sentiment of females and males has converged over time. The difference in sentiment connected with Black people and White people has also decreased over time, but there still remains a substantial gap. Second, we then analyze the relationship between book purchases and local beliefs to understand the potential messages being transmitted to children in different parts of society. We see that more purchases of books with positive sentiment towards Black characters are associated with a larger proportion of individuals who believe that White people in the U.S. have certain advantages because of the color of their skin and who are angry that racism exists. Understanding the messages that may be implicitly — or explicitly — sent to children through highly influential books can lend insight into the factors that may shape children’s beliefs and attitudes.   [Video]

“Measuring Representation of Race, Gender, and Age in Children’s Books: Face Detection and Feature Classification in Illustrated Images” (with T. Szasz, E. Harrison, P-J. Liu, P-C. Lin, H.B. Runesha) (January 2022, Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV))

Images in children’s books convey messages about society and the roles that people play in it. Understanding these messages requires systematic measurement of who is represented. Computer vision face detection tools can provide such measurements; however, state-of-the-art face detection models were trained with photographs, and 80\% of images in children’s books are illustrated; thus existing methods both misclassify and miss classifying many faces. In this paper, we introduce a new approach to analyze images using AI tools, resulting in data that can assess representation of race, gender, and age in both illustrations and photographs in children’s books. We make four primary contributions to the fields of deep learning and social sciences: (1) We curate an original face detection data set (IllusFace 1.0) by manually labeling 5,403 illustrated faces with bounding boxes. (2) We train two AutoML-based face detection models for illustrations: (i) using IllusFace 1.0 (FDAI); (ii) using iCartoon, a publicly available data set (FDAI_iC), each optimized for illustrated images, detecting 2.5 times more faces in our testing data than the established face detector using Google Vision (FDGV). (3) We curate a data set of the race, gender, and age of 980 faces manually labeled by three different raters (CBFeatures 1.0). (4) We train an AutoML feature classification model (FCA) using CBFeatures 1.0. We compare FCA with the performance of another AutoML model that we trained on UTKFace, a public data set (FCA_UTK) and of an established model using FairFace (FCF). Finally, we examine distributions of character identities over the last century across the models. We find that FCA is 34% more accurate than FCF in its race predictions. These contributions provide tools to educators, caregivers, and curriculum developers to assess the representation contained in children’s content.    [Poster]    [Video]

“Spillover Impacts on Education from Employment Guarantees” (January 2022, Education Finance and Policy)

Programs that guarantee some basic level of low-skill employment are a popular anti-poverty strategy in developing countries, with India’s employment-guarantee program (MGNREGA) annually employing adults in 23% of Indian households.  An important concern is these employment programs may discourage children’s education and, thus, more-sustained long-run income growth.  Using large-scale administrative data and household survey data, I estimate precise spillover impacts on education that reject substantive declines in children’s education from the rollout of MGNREGA.  These negative spillovers are inexpensive to counteract, and small compared to immediate effects of MGNREGA on rural employment and poverty alleviation.  [Takeaway (one-pager)]

“Religion and Sanitation Practices”
(with M. Alsan, K. Babiarz, J. Goldhaber-Fiebert, and L. Prince)  (May 2021, World Bank Economic Review)

In India, infant mortality among Hindus is higher than among Muslims, and religious differences in sanitation practices have been cited as a contributing factor. To explore whether religion itself is associated with differences in sanitation practices, this study compares sanitation practices of Hindus and Muslims living in the same locations using three nationally representative data sets from India. Across all three data sets, the unconditional religion-specific gap in latrine ownership and latrine use declines by approximately two-thirds when conditioning on location characteristics or including location fixed effects. Further, the estimates do not show evidence of religion-specific differences in other sanitation practices, such as handwashing or observed fecal material near homes. Household sanitation practices vary substantially across areas of India, but religion itself has less direct influence when considering differences between Hindus and Muslims within the same location.

“Educational Investment Responses to Economic Opportunity: Evidence from Indian Road Construction”
(with S. Asher and P. Novosad) (January 2020, American Economic Journal: Applied Economics)

The rural poor in developing countries, once economically isolated, are increasingly being connected to outside markets. Whether these new connections crowd out or encourage educational investment is a central question. We examine the impacts on educational choices of 115,000 new roads built under India’s flagship road construction program. We find that children stay in school longer and perform better on standardized exams. Treatment heterogeneity supports the predictions of a standard human capital investment model: enrollment increases are largest where nearby labor markets offer the highest returns to education and lowest where they imply high opportunity costs of schooling.   [Slides]

“Sanitation and Education” (April 2017, American Economic Journal: Applied Economics)

I explore whether the absence of school-sanitation infrastructure impedes educational attainment, particularly among pubescent-age girls, using a national Indian school latrine-construction initiative and administrative school-level data. School-latrine construction substantially increases enrollment of pubescent-age girls, though predominately when providing sex-specific latrines. Privacy and safety appear to matter sufficiently for pubescent-age girls that only sex-specific latrines reduce gender disparities. Any latrine substantially benefits younger girls and boys, who may be particularly vulnerable to sickness from uncontained waste. Academic test scores did not increase following latrine construction, however. Estimated increases in enrollment are similar across the substantial variation in Indian district characteristics.   [Slides]

 

Other Writings: Policy Briefs, Op-Eds, Blog Posts

Road connectivity and rural economic development: Evidence from India’s rural roads programme (with S. Asher and Paul Novosad), VoxDev, July 2022.

India’s National Education Policy: A need to look beyond the classroom to improve resultsVoxDev, November 2019.

How sanitation facilities in schools can improve educational outcomes, Ideas for India, August 2018.

Promoting Education through School SanitationWorld Bank Development Impact, March 2014.

“The Impact of the Financial Crisis on Tertiary Education World Wide” (with B. Long) World Bank, September 2009.

“The Broadmoor Project New Orleans Community Engagement Initiative: Progress Report” (with D. Ahlers, M. Blakley, L. Cole, M. El Dahshan, A. Hodari, H. Ko, J. Maeso, A. Noble, D. Radcliffe, M. Richards, C. Valentine, A. Van, D. Walsh, A. Watson, A. Woods, C. Wood, J. Wright, K. Yang). Harvard Kennedy School – Broadmoor Initiative, March 2007.

 

 

HOME                               RESEARCH                                CV                               CONTACT                               LAND ACKNOWLEDGEMENT