Using Environmental Features to Maximize Prediction of Regional Intergroup Bias
Using Environmental Features to Maximize Prediction of Regional Intergroup Bias
复制标题
利用环境特征最大限度地预测区域群间偏差
DOI:
10.1177/1948550620909775
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发表时间:
2020
影响因子:
5.7
通讯作者:
Jimmy Calanchini
中科院分区:
文献类型:
--
作者:
Eric Hehman;Eugene K. Ofosu;Jimmy Calanchini
The present research adopts a data-driven approach to identify how characteristics of the environment are related to different types of regional in-group biases. After consolidating a large data set of environmental attributes (N = 813), we used modern model selection techniques (i.e., elastic net regularization) to develop parsimonious models for regional implicit and explicit measures of race-, religious-, sexuality-, age-, and health-based in-group biases. Developed models generally predicted large amounts of variance in regional biases, up to 62%, and predicted significantly and substantially more variance in regional biases than basic regional demographics. Human features of the environment and events in the environment strongly and consistently predicted biases, but nonhuman features of the environment and population characteristics inconsistently predicted biases. Results implicate shared psychological causes of different regional intergroup biases, reveal distinctions between biases, and contribute to developing theoretical models of regional bias.
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影响因子:
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作者:
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通讯作者:
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影响因子:
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作者:
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通讯作者:
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DOI:
10.1073/pnas.1818816116
发表时间:
2019-06-11
影响因子:
11.1
作者:
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通讯作者:
Brown-Iannuzzi, Jazmin L.