When Common Identities Decrease Trust
An Experimental Study of Partisan Women
Bibliographic Data
| ID | 6231664 |
|---|---|
| Authors | Samara Klar (0000-0003-4863-9949, University of Arizona, corresponding author) |
| Year | 2018 |
| Volume | 62 |
| Issue | 3 |
| Pages | 610-622 |
| Publication date | 2018-07-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | American Journal of Political Science (JOURNAL) |
| Journal identifiers | ISSN: 0092-5853 • E-ISSN: 1540-5907 |
| Publisher | Wiley (PUBLISHER • GB) |
| DOI | 10.1111/ajps.12366 |
| OpenAlex | W2807298963 |
| Language | EN |
| Citations received | 52 |
| References cited | 45 |
How does sharing a common gender identity affect the relationship between Democratic and Republican women? Social psychological work suggests that common ingroup identities unite competing factions. After closely examining the conditions upon which the common ingroup identity model depends, I argue that opposing partisans who share the superordinate identity of being a woman will not reduce their intergroup biases. Instead, I predict that raising the salience of their gender will increase cross‐party biases. I support my hypotheses with a nationally representative survey of 3,000 adult women and two survey experiments, each with over 1,000 adult women. These findings have direct implications for how women evaluate one another in contentious political settings and, more broadly, for our understanding of when we can and cannot rely upon common identities to bridge the partisan divide
Affect (linguistics · Collective identity · Identity (music · Ingroups and outgroups · Norm (philosophy · Political science · Politics · Salience (neuroscience · Social group · Social identity theory · Superordinate goals · Survey data collection · Electoral Systems and Political Participation · Gender Politics and Representation · Psychology · Social and Intergroup Psychology · Social Psychology
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| Unique citing works | 52 |
|---|---|
| Citations per year | 7,43 |
| Citation span | 2019 - 2026 (8) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 51 |