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Cited by 545

The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.

It Could Be Worse: Selective Evaluation as a Response to Victimization

Taylor, Shelley E., Wood, Joanne V., Lichtman, Rosemary R.·1983·Journal of Social Issues

Abstract

A theory of victims' responses to their victimization, termed Selective Evaluation, is proposed. It is maintained that the perception that one is a victim and the belief that others perceive one as a victim are aversive. Victims react to this aversive state by selectively evaluating themselves and their situation in ways that are self‐enhancing. Five mechanisms of selective evaluation that minimize victimization are proposed and discussed: making social comparisons with less fortunate others (i.e., downward comparison); selectively focusing on attributes that make one appear advantaged; creating hypothetical, worse worlds; construing benefit from the victimizing event; and manufacturing normative standards of adjustment that make one's own adjustment appear exceptional. The theory is integrated with the existing literature on victimization, and possible functions of selective evaluation are discussed.

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Crossref · 10.1111/j.1540-4560.1983.tb00139.x

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Metadata

Authors
Taylor, S. E., Wood, J. V., & Lichtman, R. R.
Venue
Journal of Social Issues
Publisher
Wiley
Published
1983-07
Volume
39
Issue
2
Pages
19-40
ISSN
  • 0022-4537 (ISSN-L)
  • 1540-4560
OpenAlex
W2011796313
Cited by
545
References
5
FWCI
36.67
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: It Could Be Worse: Selective Evaluation as a Response to Victimization. https://app.cochat.ai/papers/10.1111/j.1540-4560.1983.tb00139.x
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Taylor, S. E., Wood, J. V., & Lichtman, R. R. (1983). It Could Be Worse: Selective Evaluation as a Response to Victimization. Journal of Social Issues. https://doi.org/10.1111/j.1540-4560.1983.tb00139.x

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.