Literature DB >> 25331879

Motive attribution asymmetry for love vs. hate drives intractable conflict.

Adam Waytz1, Liane L Young2, Jeremy Ginges3.   

Abstract

Five studies across cultures involving 661 American Democrats and Republicans, 995 Israelis, and 1,266 Palestinians provide previously unidentified evidence of a fundamental bias, what we term the "motive attribution asymmetry," driving seemingly intractable human conflict. These studies show that in political and ethnoreligious intergroup conflict, adversaries tend to attribute their own group's aggression to ingroup love more than outgroup hate and to attribute their outgroup's aggression to outgroup hate more than ingroup love. Study 1 demonstrates that American Democrats and Republicans attribute their own party's involvement in conflict to ingroup love more than outgroup hate but attribute the opposing party's involvement to outgroup hate more than ingroup love. Studies 2 and 3 demonstrate this biased attributional pattern for Israelis and Palestinians evaluating their own group and the opposing group's involvement in the current regional conflict. Study 4 demonstrates in an Israeli population that this bias increases beliefs and intentions associated with conflict intractability toward Palestinians. Finally, study 5 demonstrates, in the context of American political conflict, that offering Democrats and Republicans financial incentives for accuracy in evaluating the opposing party can mitigate this bias and its consequences. Although people find it difficult to explain their adversaries' actions in terms of love and affiliation, we suggest that recognizing this attributional bias and how to reduce it can contribute to reducing human conflict on a global scale.

Entities:  

Keywords:  attribution; cognitive bias; ingroup love; intergroup conflict; outgroup hate

Mesh:

Year:  2014        PMID: 25331879      PMCID: PMC4226129          DOI: 10.1073/pnas.1414146111

Source DB:  PubMed          Journal:  Proc Natl Acad Sci U S A        ISSN: 0027-8424            Impact factor:   11.205


  17 in total

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  8 in total

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