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Note: This Manuscript Is a Pre-Print Version of a Manuscript Accepted for Publication in the Journal of Personality and Social Psychology PARTISAN-MOTIVATED SAMPLING Note: This manuscript is a pre-print version of a manuscript accepted for publication in the Journal of Personality and Social Psychology. This paper is not the copy of record and may not exactly replicate the final, authoritative version of the article. Please do not copy or cite without authors' permission. The final article will be available, upon publication, via its DOI: 10.1037/pspi0000375. Data and Materials for this manuscript are available at: https://osf.io/9627e/? view_only=4f5c8a589e014c92a1fca171bb0e4369. Please email [email protected] if you have questions. 2 Partisan-Motivated Sampling Partisan-Motivated Sampling: Re-Examining Politically Motivated Reasoning Across the Information Processing Stream Yrian Derreumaux1, Robin Bergh2, Brent L. Hughes1 1University of California, Riverside, 2Uppsala University Correspondence should be addressed to: Brent Hughes Department of Psychology University of California, Riverside 900 University Ave, Riverside CA, USA Email: [email protected] 3 Partisan-Motivated Sampling Abstract The U.S. is increasingly politically polarized, fueling intergroup conflict and intensifying partisan biases in cognition and behavior. To date, research on intergroup bias has separately examined biases in how people search for information and how they interpret information. Here, we integrate these two perspectives to elucidate how partisan biases manifest across the information processing stream, beginning with (1) a biased selection of information, leading to (2) skewed samples of information that interact with (3) motivated interpretations to produce evaluative biases. Across 3 experiments and 4 internal meta-analyses, participants (N = 2,431) freely sampled information about ingroup and outgroup members or ingroup and outgroup political candidates until they felt confident to evaluate them. Across experiments, we reliably find that most participants begin sampling information from the ingroup, which was associated with individual differences in group-based motives, and that participants sampled overall more information from the ingroup. This sampling behavior, in turn, generates more variability in ingroup (relative to outgroup) experiences. We find that more variability in ingroup experiences predicted when participants decided to stop sampling, and was associated with more biased evaluations. We further demonstrate that participants employ different sampling strategies over time when 4 Partisan-Motivated Sampling the ingroup is de facto worse–obfuscating real group differences–and that participants selectively integrate their experiences into evaluations based on congeniality. The proposed framework extends classic findings in psychology by demonstrating how biases in sampling behavior interact with motivated interpretations to produce downstream evaluative biases and has implications for intergroup bias interventions. Keywords: intergroup bias, political partisanship, experience sampling, motivated reasoning The U.S. is more polarized now than during civil rights movement (Abramowitz & Saunders, 2008; Levendusky, 2010; Pew Research Center, 2017). Elevated polarization increases partisan biases in information processing (Druckman et al., 2013). Consider the electorate’s experience of President Donald Trump’s impeachment hearings: People were exposed to different amounts of pro- vs-anti impeachment arguments, based largely on what news sources they consumed (e.g., Fox News vs. CNN). Moreover, even when people had access to the same information (e.g., that Trump asked Ukrainian President Zelensky to investigate the Bidens), conclusions tended to diverge along party lines (i.e. 91% 5 Partisan-Motivated Sampling Democrats thought Trump had acted illegally vs. 32% of Republicans; Pew Research Center, 2020). These examples highlight two important aspects of information processing that can generate biased evaluations and beliefs. First, people tend to reach conclusions that re-affirm their pre-existing partisan beliefs, even when exposed to the same data (an interpretive bias). This phenomenon fits into a long tradition of research on motivated reasoning, which describes how pre-existing beliefs (e.g., that the ingroup is better) bias the interpretation of information to form conclusions that are most desired rather than those that are most accurate (Greenberg & Pyszczynski, 1985; Kunda, 1987; Wyer & Frey, 1983; Kunda, 1990). Second, although Republicans and Democrats had access to diverse and comprehensive information, they gathered only a subset of such information, which likewise led to congenial conclusions (a sampling bias). Such sampling biases stem from people accessing only a subset of information that is non-representative and skewed relative to all available information (e.g., Fiedler, 2000; Lindskog, Winman, & Juslin, 2013). To date, research has typically examined sampling and interpretive biases separately (e.g., Denrell, 2005; Gampa et al., 2019), rather than jointly modeling these influences on evaluations of groups (or other judgments and decisions). 6 Partisan-Motivated Sampling Here, we argue that group-based bias is driven in part by a motivation preceding those ubiquitous in studies of motivated reasoning: a wish to gather information first and most frequently from one’s own groups. This, in turn, leads to non-representative samples that, when unaccounted for, interact with partisan- based interpretive motives to bolster biased evaluations favoring the ingroup. In other words, we examine connections between three sources of evaluative bias across the information-processing stream: (1) a biased selection of information, which leads to (2) skewed samples of information, which interacts with (3) motivated interpretations to produce evaluative biases. Together, we provide a comprehensive framework for understanding the emergence of partisan biases across information processing by integrating sampling and evaluative sources of bias. We review the literature on each source of bias, stepping backwards through the causal chain to capture the evolution of the literature (interpretive biases have the longest history; e.g., Hastorf & Cantril, 1954), before outlining the framework for the current experiments. Partisan Evaluative Biases Social identities provide people with an important source of value and status, which in turn increases their tendency to engage in motivated reasoning when exposed to identity-relevant information (e.g., Kahan, 2013; Kahan et al., 2011, 7 Partisan-Motivated Sampling 2013). Political identity in particular has become one of the strongest social identity attachments in the U.S., along with race, ethnicity, and religion (Iyengar et al., 2019; Iyengar & Krupenkin, 2018; Mason, 2018). As such, a wealth of research has examined interpretive biases that arise in politically motivated reasoning (Cohen, 2003; for meta-analysis see: Ditto et al., 2019; for a review of methods see: Kahan, 2016; Tappin et al., 2020). In a typical study within this tradition, participants are asked to evaluate information that is matched as closely as possible on all dimensions, except for whether the information (or the source of the information) favors one’s political identity or not. A consistent finding is that congenial information (i.e. information that favors pre-existing beliefs) or information from congenial sources (e.g., coming from an ingroup source) is interpreted more favorably and perceived as more valid than uncongenial information (Flynn et al., 2017; Gampa et al., 2019; Hughes et al., 2017; Lord et al., 1979; Tappin et al., 2017). For example, Democrats and Republicans evaluate identical information more favorably when it is supported by members of their own party (i.e. “party over policy”; Cohen, 2003). A growing body of research suggests that people not only favor congenial information, but are also motivated skeptics of uncongenial information (disconfirmation bias; Ditto et al., 1998; Ditto & Lopez, 1992; Kraft et al., 2015; 8 Partisan-Motivated Sampling Taber et al., 2009; Taber & Lodge, 2012). From this perspective, people adopt differential judgement criteria when evaluating uncongenial relative to congenial information, holding arguments they dislike to higher standards that require more and stronger evidence. Taken together, this research explains how politically motivated reasoning, which affects both Democrats and Republicans (Ditto et al., 2019; cf. Baron & Jost, 2019), can generate discrepancies in peoples’ evaluations of the same (i.e. matched) information based on group membership. Importantly, the majority of these frameworks focus on the interpretation phase of information processing, where the congeniality of the information, most often qualitative in nature (e.g., a title of an article that is pro/anti-gun rights) or the partisan source of the information (e.g., coming from a conservative or liberal source) are explicitly labeled. However, they do not consider the sampling phase of information processing, wherein people gather and explore information that precedes interpretation. In addition, it is often difficult to establish causal links between partisan-motivations and other motivations and explanations, due in part to the qualitative nature of the information used in studies of politically motivated reasoning (see e.g., Tappin et al., 2020). Moreover, in the real world, people often have to make inferences about underlying distributions from “noisy” data that require prolonged search to arrive at an accurate judgement.
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