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CLIFFORD, SCOTT (2) answer(s).
 
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ID:   171346


How empathic concern Fuels Political Polarization / Simas, Elizabeth N; Clifford, Scott; Kirkland, Justin H   Journal Article
Simas, Elizabeth N Journal Article
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Summary/Abstract Over the past two decades, there has been a marked increase in partisan social polarization, leaving scholars in search of solutions to partisan conflict. The psychology of intergroup relations identifies empathy as one of the key mechanisms that reduces intergroup conflict, and some have suggested that a lack of empathy has contributed to partisan polarization. Yet, empathy may not always live up to this promise. We argue that, in practice, the experience of empathy is biased toward one’s ingroup and can actually exacerbate political polarization. First, using a large, national sample, we demonstrate that higher levels of dispositional empathic concern are associated with higher levels of affective polarization. Second, using an experimental design, we show that individuals high in empathic concern show greater partisan bias in evaluating contentious political events. Taken together, our results suggest that, contrary to popular views, higher levels of dispositional empathy actually facilitate partisan polarization.
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2
ID:   180823


Increasing Precision without Altering Treatment Effects: Repeated Measures Designs in Survey Experiments / Clifford, Scott   Journal Article
Clifford, Scott Journal Article
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Summary/Abstract The use of survey experiments has surged in political science. The most common design is the between-subjects design in which the outcome is only measured posttreatment. This design relies heavily on recruiting a large number of subjects to precisely estimate treatment effects. Alternative designs that involve repeated measurements of the dependent variable promise greater precision, but they are rarely used out of fears that these designs will yield different results than a standard design (e.g., due to consistency pressures). Across six studies, we assess this conventional wisdom by testing experimental designs against each other. Contrary to common fears, repeated measures designs tend to yield the same results as more common designs while substantially increasing precision. These designs also offer new insights into treatment effect size and heterogeneity. We conclude by encouraging researchers to adopt repeated measures designs and providing guidelines for when and how to use them.
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