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What We Teach About Race and Gender: Representation in Images and Text of Children’s Books
The Quarterly Journal of Economics ( IF 13.7 ) Pub Date : 2023-08-31 , DOI: 10.1093/qje/qjad028
Anjali Adukia 1 , Alex Eble 2 , Emileigh Harrison 3 , Hakizumwami Birali Runesha 3 , Teodora Szasz 3
Affiliation  

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 past 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 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 nondominant social identities and fewer copies of these books in libraries that serve predominantly White communities.

中文翻译:

我们教授的关于种族和性别的内容:儿童读物的图像和文本中的表现

书籍塑造了孩子们了解社会和规范的方式,部分是通过描绘不同的人物来塑造的。我们使用计算工具来描述过去一个世纪在家庭、教室和图书馆广泛阅读的儿童书籍中的代表性,并描述可能促成这些模式的经济力量。我们引入新的人工智能方法来系统地将图像转换为数据。我们应用这些工具以及文本分析方法来测量这些书籍内容中的肤色、种族、性别和年龄,记录随着时间​​的推移发生的变化和持续的内容。我们发现,尽管黑人和拉丁裔的代表性随着时间的推移而增加,但相对于其人口比例而言,在最具影响力的书籍中,黑人和拉丁裔的代表性不足。女性也越来越多地出现,但在文本中出现的频率低于在图像中出现的频率,这表明图片中的象征性包容性多于故事中的实质性包容性。这些有影响力的书中的人物平均肤色比其他书中更浅,即使在种族条件下也是如此,而且儿童的平均肤色比成人浅。我们对相关经济行为进行实证分析,以更好地理解我们在这些书中发现的表述。在需求方面,我们表明人们消费以自己身份为中心的书籍,并且购买的儿童书籍类型与当地的政治信仰相关。在供应方面,我们记录了以非主导社会身份为中心的书籍价格较高,而主要为白人社区服务的图书馆中这些书籍的数量较少。
更新日期:2023-08-31
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