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      Single-Target Implicit Association Tests (ST-IAT) Predict Voting Behavior of Decided and Undecided Voters in Swiss Referendums

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          Abstract

          Undecided voters represent a major challenge to political pollsters. Recently, political psychologists have proposed the use of implicit association tests (IAT) to measure implicit attitudes toward political parties and candidates and predict voting behavior of undecided voters. A number of studies have shown that both implicit and explicit (i.e., self-reported) attitudes contribute to the prediction of voting behavior. More importantly, recent research suggests that implicit attitudes may be more useful for predicting the vote of undecided voters in the case of specific political issues rather than elections. Due to its direct-democratic political system, Switzerland represents an ideal place to investigate the predictive validity of IATs in the context of political votes. In this article, I present evidence from three studies in which both explicit and implicit measures were used ahead of the vote on four different referendums. Explicit measures predicted voting better than implicit attitudes for decided voters while implicit and explicit attitudes were equally good predictors among undecided voters. In addition, implicit attitudes predicted voting behavior descriptively, but not significantly better for undecided voters while, also from a descriptive point of view, explicit attitudes predicted voting better for decided respondents. In sum, results suggest that, as argued in previous research, the predictive value of implicit attitudes may be higher in the context of issue-related votes but still not as high as initially hoped-for.

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          Most cited references13

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          Measuring individual differences in implicit cognition: the implicit association test.

          An implicit association test (IAT) measures differential association of 2 target concepts with an attribute. The 2 concepts appear in a 2-choice task (2-choice task (e.g., flower vs. insect names), and the attribute in a 2nd task (e.g., pleasant vs. unpleasant words for an evaluation attribute). When instructions oblige highly associated categories (e.g., flower + pleasant) to share a response key, performance is faster than when less associated categories (e.g., insect & pleasant) share a key. This performance difference implicitly measures differential association of the 2 concepts with the attribute. In 3 experiments, the IAT was sensitive to (a) near-universal evaluative differences (e.g., flower vs. insect), (b) expected individual differences in evaluative associations (Japanese + pleasant vs. Korean + pleasant for Japanese vs. Korean subjects), and (c) consciously disavowed evaluative differences (Black + pleasant vs. White + pleasant for self-described unprejudiced White subjects).
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            Understanding and using the implicit association test: I. An improved scoring algorithm.

            In reporting Implicit Association Test (IAT) results, researchers have most often used scoring conventions described in the first publication of the IAT (A.G. Greenwald, D.E. McGhee, & J.L.K. Schwartz, 1998). Demonstration IATs available on the Internet have produced large data sets that were used in the current article to evaluate alternative scoring procedures. Candidate new algorithms were examined in terms of their (a) correlations with parallel self-report measures, (b) resistance to an artifact associated with speed of responding, (c) internal consistency, (d) sensitivity to known influences on IAT measures, and (e) resistance to known procedural influences. The best-performing measure incorporates data from the IAT's practice trials, uses a metric that is calibrated by each respondent's latency variability, and includes a latency penalty for errors. This new algorithm strongly outperforms the earlier (conventional) procedure.
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              The single category implicit association test as a measure of implicit social cognition.

              The Single Category Implicit Association Test (SC-IAT) is a modification of the Implicit Association Test that measures the strength of evaluative associations with a single attitude object. Across 3 different attitude domains--soda brand preferences, self-esteem, and racial attitudes--the authors found evidence that the SC-IAT is internally consistent and makes unique contributions in the ability to understand implicit social cognition. In a 4th study, the authors investigated the susceptibility of the SC-IAT to faking or self-presentational concerns. Once participants with high error rates were removed, no significant self-presentation effect was observed. These results provide initial evidence for the reliability and validity of the SC-IAT as an individual difference measure of implicit social cognition. Copyright 2006 APA, all rights reserved.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                2016
                12 October 2016
                : 11
                : 10
                : e0163872
                Affiliations
                [001]Department of Political Science, University of Zurich, Zurich, Switzerland
                Universitat de Valencia, SPAIN
                Author notes

                Competing Interests: The author has declared that no competing interests exist.

                • Conceptualization: LR.

                • Data curation: LR.

                • Formal analysis: LR.

                • Funding acquisition: LR.

                • Investigation: LR.

                • Methodology: LR.

                • Project administration: LR.

                • Resources: LR.

                • Software: LR.

                • Supervision: LR.

                • Validation: LR.

                • Visualization: LR.

                • Writing – original draft: LR.

                • Writing – review & editing: LR.

                Article
                PONE-D-15-53292
                10.1371/journal.pone.0163872
                5061388
                27732617
                8022670c-725d-4638-919d-cf7d7eb38b02
                © 2016 Livio Raccuia

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 17 December 2015
                : 15 September 2016
                Page count
                Figures: 0, Tables: 8, Pages: 19
                Funding
                The author received no specific funding for this work.
                Categories
                Research Article
                Social Sciences
                Economics
                Labor Economics
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                Social Sciences
                Political Science
                Elections
                Biology and Life Sciences
                Neuroscience
                Cognitive Science
                Cognition
                Decision Making
                Medicine and Health Sciences
                Public and Occupational Health
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                Health Economics
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                Health Care
                Health Economics
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                Behavior
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                Europe
                Switzerland
                Custom metadata
                All data are available here: http://doi.org/10.3886/E100174V1.

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