方法对比

	Support for Political Violence Measure	Affective Polarization Measurement
领域	政治心理学	政治心理学
方法族	Latent structure	Process / pipeline
起源年份	2022	2012
提出者	Nathan Kalmoe & Lilliana Mason	Shanto Iyengar, Gaurav Sood & Yphtach Lelkes
类型	Attitude scale for endorsement of partisan violence	Composite survey index
开创性文献	Kalmoe, N. P., & Mason, L. (2022). Radical American Partisanship: Mapping Violent Hostility, Its Causes, and the Consequences for Democracy. University of Chicago Press. ISBN: 9780226820286	Iyengar, S., Sood, G., & Lelkes, Y. (2012). Affect, not ideology: A social identity perspective on polarization. Public Opinion Quarterly, 76(3), 405-431.
别名	Lethal Partisanship Scale, Support for Partisan Violence Battery, Kalmoe-Mason Political Violence Items, Radical Partisanship Measure	Affective Polarization Index, Partisan Affect Gap, Thermometer Difference Measure
相关	3	4
摘要	This measure assesses citizens' willingness to endorse violence against political opponents, a key indicator of democratic fragility. Nathan Kalmoe and Lilliana Mason's research, synthesized in Radical American Partisanship (2022), maps a continuum of violent partisan hostility from wishing harm on the other side to endorsing lethal attacks, using representative surveys and embedded behavioral experiments. Because such attitudes are rare and the items are extreme, the measure has prompted vigorous methodological debate, exemplified by Westwood and colleagues' demonstration that inattentive responding and item design can substantially inflate apparent support, making bias correction central to credible estimates.	Affective polarization measurement quantifies the gap between how positively people feel toward their own political party (the in-party) and how negatively they feel toward the opposing party (the out-party). Iyengar, Sood and Lelkes (2012) showed that this affective divide has grown sharply even where issue positions have not, reframing polarization as a social-identity phenomenon of partisan like and dislike rather than ideological distance.