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A Meta-Analysis on the Correlation Between the Implicit Association Test and Explicit Self-Report Measures

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TLDR
The results suggest that implicit and explicit measures are generally related but that higher order inferences and lack of conceptual correspondence can reduce the influence of automatic associations on explicit self-reports.
Abstract
Theoretically, low correlations between implicit and explicit measures can be due to (a) motivational biases in explicit self reports, (b) lack of introspective access to implicitly assessed representations, (c) factors influencing the retrieval of information from memory, (d) method-related characteristics of the two measures, or (e) complete independence of the underlying constructs. The present study addressed these questions from a meta-analytic perspective, investigating the correlation between the Implicit Association Test (IAT) and explicit self-report measures. Based on a sample of 126 studies, the mean effect size was .24, with approximately half of the variability across correlations attributable to moderator variables. Correlations systematically increased as a function of (a) increasing spontaneity of self-reports and (b) increasing conceptual correspondence between measures. These results suggest that implicit and explicit measures are generally related but that higher order inferences and lack of conceptual correspondence can reduce the influence of automatic associations on explicit self-reports.

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Implicit attitudes toward an authoritarian regime

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What Is the Implicit Gender-Science Stereotype? Exploring Correlations Between the Gender-Science IAT and Self-Report Measures:

TL;DR: This paper found that implicit measures of the gender science stereotype are often better than explicit measures in predicting relevant outcomes, and this finding could reflect a discrepancy between implicit and explicit measures of gender stereotypes.
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How a growth mindset can change the climate: The power of implicit beliefs in influencing people’s view and action

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Biased by our imaginings.

TL;DR: It is argued that the proposed model accommodates characteristic features of implicit bias, does not face the problems of the doxastic model, and is uniquely placed to accommodate the structural heterogeneity in the category of implicit biases.
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The Self-Access Form

TL;DR: The Self Access Form (SAF) as discussed by the authors is a short scale of five items, including self-referential information, that individuals use to identify who they are, what they think, want, need, or feel, and is positively associated with emotion regulation, adaptive functioning, well-being, and meaning in life.
References
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Journal ArticleDOI

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

TL;DR: An implicit association test (IAT) measures differential association of 2 target concepts with an attribute when instructions oblige highly associated categories to share a response key, and performance is faster than when less associated categories share a key.
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The file drawer problem and tolerance for null results

TL;DR: Quantitative procedures for computing the tolerance for filed and future null results are reported and illustrated, and the implications are discussed.
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Attitude-behavior relations: A theoretical analysis and review of empirical research.

TL;DR: In this article, a review of available empirical research supports the contention that strong attitude-behavior relations can be obtained only under high correspondence between at least the target and action elements of the attitudinal and behavioral entities.
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Implicit Social Cognition: Attitudes, Self-Esteem, and Stereotypes.

TL;DR: The present conclusion--that attitudes, self-esteem, and stereotypes have important implicit modes of operation--extends both the construct validity and predictive usefulness of these major theoretical constructs of social psychology.
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Understanding and using the Implicit Association Test: I. An improved scoring algorithm.

TL;DR: 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, and strongly outperforms the earlier (conventional) procedure.
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