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251.
252.
John Dixon Guy Elcheroth Philippa Kerr John Drury Mai Al Bzour Emina Subašić 《European Review of Social Psychology》2020,31(1):40-75
ABSTRACTThe social psychology of intergroup relations has emerged largely from studies of how one group of people (e.g., whites) think and feel about another (e.g., blacks). By reducing the social world to binary categories, this approach has provided an effective and efficient methodological framework. However, it has also obscured important features of social relations in historically divided societies. This paper highlights the importance of investigating intergroup relationships involving more than two groups and of exploring not only their psychological but also their political significance. Exemplifying this argument, we discuss the conditions under which members of disadvantaged groups either dissolve into internecine competition or unite to challenge the status quo, highlighting the role of complex forms of social comparison, identification, contact, and third-party support for collective action. Binary conceptualizations of intergroup relations, we conclude, are the product of specific sociohistorical practices rather than a natural starting point for psychological research. 相似文献
253.
Scott B. Morris Michael Bass Elizabeth Howard Richard E. Neapolitan 《International Journal of Testing》2020,20(2):146-168
The standard error (SE) stopping rule, which terminates a computer adaptive test (CAT) when the SE is less than a threshold, is effective when there are informative questions for all trait levels. However, in domains such as patient-reported outcomes, the items in a bank might all target one end of the trait continuum (e.g., negative symptoms), and the bank may lack depth for many individuals. In such cases, the predicted standard error reduction (PSER) stopping rule will stop the CAT even if the SE threshold has not been reached and can avoid administering excessive questions that provide little additional information. By tuning the parameters of the PSER algorithm, a practitioner can specify a desired tradeoff between accuracy and efficiency. Using simulated data for the Patient-Reported Outcomes Measurement Information System Anxiety and Physical Function banks, we demonstrate that these parameters can substantially impact CAT performance. When the parameters were optimally tuned, the PSER stopping rule was found to outperform the SE stopping rule overall, particularly for individuals not targeted by the bank, and presented roughly the same number of items across the trait continuum. Therefore, the PSER stopping rule provides an effective method for balancing the precision and efficiency of a CAT. 相似文献