Construing stigmatized identities: A golden section study
Objectives. In order to examine whether persons belonging to stigmatized groups are evaluated more negatively than others, this study employed the golden section hypothesis, which predicts that people organize their evaluations in a ratio of roughly 62% positive to 38% negative. Method. Surveys were...
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Veröffentlicht in: | Psychology and psychotherapy 2008-09, Vol.81 (3), p.285-296 |
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Zusammenfassung: | Objectives. In order to examine whether persons belonging to stigmatized groups are evaluated more negatively than others, this study employed the golden section hypothesis, which predicts that people organize their evaluations in a ratio of roughly 62% positive to 38% negative.
Method. Surveys were administered to 154 participants, with 143 surveys analysed. Participants rated nine different identities (business person, politician, lawyer, police officer, college professor, criminal, mental patient, homeless person, and self) along 12 different bipolar dimensions (generous–stingy, pleasant–unpleasant, true–false, fair–unfair, active–passive, energetic–lethargic, sharp–dull, excitable–calm, strong–weak, bold–timid, hard–soft, and rugged–delicate). These dimensions had well‐established positive and negative poles.
Results. Non‐stigmatized identities were evaluated slightly more positively than the golden section hypothesis predicts, while stigmatized identities were rated in a ‘reverse’ golden section pattern. A criminal identity was rated more negatively than the golden section hypothesis predicts and the self more positively. Follow‐up analyses suggested that the percentages of positive adjectives assigned to the self and non‐stigmatized others were consistent with a model that expands upon the golden section hypothesis.
Conclusion. Stigmatized identities are rated using a reverse golden section ratio. This has implications for understanding how people construe stigmatized people. While the golden section hypothesis did not hold for non‐stigmatized identities, this may be because the data are better explained by a more refined model that is slightly different from the golden section. |
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ISSN: | 1476-0835 2044-8341 |
DOI: | 10.1348/147608308X292361 |