Perceived distributions of the characteristics of in-group and out-group members: empirical evidence and a computer simulation.
Perceived distributions of the characteristics of in-group and out-group members: empirical evidence and a computer simulation.
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DOI：
10.1037/0022-3514.57.2.165
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发表时间：
1989-08
影响因子：
7.6
通讯作者：
Patricia W. Linville;G. W. Fischer;P. Salovey
中科院分区：
文献类型：
--
作者：
Patricia W. Linville;G. W. Fischer;P. Salovey
本研究探讨了社会类别成员特征的知觉分布的两个性质：类别成员之间的区分（区分）概率和类别成员的知觉变异（方差）。4个实验的结果支持了这一假设，即更熟悉的社会群体导致更大的感知分化和变异有关的组。组内成员形成更分化和可变的分布，由年龄定义的组和更分化的分布，由国籍定义的组。对于性别（学生对两种性别的人大致同样熟悉），没有发生组内-组外差异。此外，学生们在一个学期的课程中感受到了同学之间更大的差异和变化。为了解释这些结果，我们开发了PDIST，一个多样本模型，假设人们通过激活一组类别样本，然后根据这些特征值的相对激活强度来判断不同特征值的相对似然性，从而形成感知分布。计算机模拟实验的结果表明，PDIST是足以解释我们的4个实验的结果。根据PDIST形成的感知分布，增加熟悉度导致更大的分化和变异性，有一个凹的影响，并有更大的影响分化比变异性。
This research studied 2 properties of perceived distributions of the characteristics of social category members: the probability of differentiating (making distinctions) among category members and the perceived variability (variance) of category members. The results of 4 experiments supported the hypothesis that greater familiarity with a social group leads to greater perceived differentiation and variability regarding that group. In-group members formed more differentiated and variable distributions for groups defined by age and more differentiated distributions for groups defined by nationality. For gender (where students were roughly equally familiar with people of both genders), no in-group--out-group differences occurred. Also, students perceived greater differentiation and variability among classmates over the course of a semester. To explain these results, we developed PDIST, a multiple exemplar model that assumes that people form perceived distributions by activating a set of category exemplars and then judging the relative likelihoods of different feature values on the basis of the relative activation strengths of these feature values. The results of a computer simulation experiment indicated that PDIST is sufficient to explain the results of our 4 experiments. According to the perceived distributions formed by PDIST, increasing familiarity leads to greater differentiation and variability, has a concave impact, and has greater impact on differentiation than on variability.