Investigating stereotype structure with empirical network models
Investigating stereotype structure with empirical network models
复制标题
用经验网络模型研究刻板印象结构
DOI：
10.1002/ejsp.2505
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发表时间：
2018
影响因子：
3.9
通讯作者：
A. R. Rojas Tejada
中科院分区：
文献类型：
--
作者：
P. Sayans;F. Harreveld;Jonas Dalege;A. R. Rojas Tejada
在这项工作中，我们提出经验网络模型作为研究刻板印象结构的新方法。我们认为，经验网络模型可以提供对刻板印象结构的更多洞察，因为它们不受因子分析和多维尺度的固有限制（例如，仅根据共享方差对组特征进行同质解释、不可能充分表示认知模式、难以基于可能重叠的维度进行推理）。在本研究中，我们展示了经验网络模型如何将刻板印象表示为聚集在不同子结构中的动态认知结构。这些结构将基于刻板印象内容和每个群体目标中特征的共现。此外，这项研究还表明，使用经验网络如何有助于扩大对偏见或群体间态度框架中代表的刻板印象的解释。
In this work we present empirical network models as a new approach in the investigation of stereotype structure. We will argue that empirical network models can provide more insight into stereotype structure because they do not suffer from the inherent constraints of factor analysis and multidimensional scaling (e.g., group features interpreted homogeneously only on the basis of their shared variance, impossibility to adequately represent cognitive schemas, difficulties to make inferences on the basis of dimensions potentially overlapping). In the present research we show how empirical network models can represent stereotypes as dynamic cognitive structures clustered in different substructures. These structures will be based on both the stereotype content and the co‐occurrence of features in each group target. Additionally, this research shows how using empirical networks can contribute to broadening the interpretation of stereotypes representing them in the framework of prejudice or intergroup attitudes.
影响因子：
2.1
作者：
Friedman, Jerome;Hastie, Trevor;Tibshirani, Robert
通讯作者：
Tibshirani, Robert