Representing human difference: Testing how beliefs about social categories form in development

项目摘要 这个项目将使用实验研究和实验研究来考察儿童对社会类别的信念是如何发展的 基于模型的分析。在发展过程中，孩子们学会将人视为不同类别的成员：老师， 女性、共和党人、穆斯林、新英格兰人和白人只是几个例子。儿童也会形成信仰 关于为什么这些类别的成员是这样的：例如，孩子们可能会相信男孩和 女孩玩不同的玩具，因为她们生来就是这样的(我们称之为自然决定力)或孩子 可能会认为，男孩和女孩主要是被灌输了这些偏好(我们称之为社会建构)。这个 这个项目的目的是了解是什么导致儿童推断自然决定或社会结构。 为了促进对这些信念如何发展的理解，我们需要回答三个问题：(1)什么是 儿童对社会范畴的最初印象？2)儿童如何解读成年人对社会的看法 类别？(3)孩子们如何在成人演讲中修改他们的初始印象？要回答这些问题 问题，我们有三个目标：目标1将测试由外部线索标记的新的社会类别(例如，服装 和配饰)或内在暗示(例如，肤色和脸型)。我们将测量儿童的基线信念 关于这两个线索所标记的类别。然后我们需要知道孩子们根据成年人的什么推断 说到社会类别。目标2将探索泛型语言，这是一种进行泛化的语言 关于类别成员：例如，“男孩喜欢蓝色。”我们会根据成年人是否使用通用语言而有所不同 生物属性(“他们对乳糖不耐受”)、文化属性(“他们相信太阳是他们的上帝”)，或者 两者兼而有之。最后，我们需要知道孩子们是如何改变他们的信仰来回应成人的言论的。 目标3将使用基于模型的分析来定量描述儿童如何更新他们的基线信念 分类使用他们对来自语言的证据的解释。拟议中的研究试图调和 儿童经常推断自然决断力的证据和儿童灵活考虑多个 关于发育过程中社会类别的假说。具体地说，该项目追求的帐户 儿童的概率世界知识导致他们更多地推断自然决定而不是社交决定 结构，即使负责其推论的潜在认知过程是正式的 不偏不倚。独立于这一特定的描述，一个关于儿童对社会的信念的计算模型 范畴的发展将极大地推动理论的发展。它还将有助于旨在减少有害物质的干预措施 儿童可以形成关于社会类别的信念。为此，我们设计的实验将产生 开发和比较计算模型所需的数据。使用在线实验室联系家庭 将最大限度地推广这一项目的研究结果。通过将这些数据 在开放科学框架上公开访问，其他研究人员可以使用这些数据进行基于模型的分析 这将最大限度地发挥拟议实验的影响。

Project Summary This project will examine how children’s beliefs about social categories develop using experimental studies and model-based analysis. During development, children learn to think of people as members of categories: Teacher, woman, Republican, Muslim, New Englander, and White are but a few examples. Children also form beliefs about why members of these categories are the way they are: For example, children might believe boys and girls play with different toys because they were born that way (what we call natural determination) or children might believe that boys and girls were mostly taught those preferences (what we call social construction). The purpose of this project is to understand what leads children to infer natural determination or social construction. To advance understanding of how these beliefs develop, we need to answer three questions: (1) What are children’s initial impressions of social categories? 2) How do children interpret what adults say about social categories? (3) How do children revise their initial impressions in the presence of adult speech? To answer these questions, we have three aims: Aim 1 will test novel social categories marked by extrinsic cues (e.g., clothing and accessories) or intrinsic cues (e.g., skin color and face shape). We will measure children’s baseline beliefs about categories marked by these two cues. We then need to know what children infer based on what adults say about social categories. Aim 2 will explore generic language, which is language that makes generalizations about category members: e.g., “boys like blue.” We will vary whether adults use generic language about biological properties (“they are lactose intolerant”), cultural properties (“they believe the sun is their god”), or some combination of both. Finally, we need to know how children revise their beliefs in response to adult speech. Aim 3 will use model-based analysis to quantitatively describe how children update their baseline beliefs about categories using their interpretation of evidence from language. The proposed research seeks to reconcile evidence that children often infer natural determination and evidence that children flexibly consider multiple hypothesis about social categories during development. Specifically, the project pursues an account in which children’s probabilistic world knowledge leads them to infer natural determination more often than social construction even though the underlying cognitive processes responsible for their inferences are formally unbiased. Independent of this specific account, a computational model of how children’s beliefs about social categories develop would substantially advance theory. It would also aid interventions aimed at reducing harmful beliefs children can develop about social categories. To this end, we designed experiments that will generate the data necessary to develop and compare computational models. The use of the online lab to reach families from across the United States will maximize the generalizability of this project’s findings. By making this data publicly accessible on Open Science Framework, other researchers can use the data for model-based analysis too, which will maximize the impact of the proposed experiments.