Little work has examined whether implicit evaluations can be effectively “undone” after learning new revelations. Across 7 experiments, participants fully reversed their implicit evaluation of a novel target person after reinterpreting earlier information. Revision occurred across multiple implicit evaluation measures (Experiments 1a and 1b), and only when the new information prompted a reinterpretation of prior learning versus did not (Experiment 2). The updating required active consideration of the information, as it emerged only with at least moderate cognitive resources (Experiment 3). Self-reported reinterpretation predicted (Experiment 4) and mediated (Experiment 5) revised implicit evaluations beyond the separate influence of how thoughtfully participants considered the new information in general. Finally, the revised evaluations were durable three days later (Experiment 6). We discuss how these results inform existing theoretical models, and consider implications for future research.

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Stereotypes are associations between social groups and semantic attributes that are widely shared within societies. The spoken and written language of a society affords a unique way to measure the magnitude and prevalence of these widely shared collective representations. Here, we used word embeddings to systematically quantify gender stereotypes in language corpora that are unprecedented in size (65+ million words) and scope (child and adult conversations, books, movies, TV). Across corpora, gender stereotypes emerged consistently and robustly for both theoretically selected stereotypes (e.g., work–home) and comprehensive lists of more than 600 personality traits and more than 300 occupations. Despite underlying differences across language corpora (e.g., time periods, formats, age groups), results revealed the pervasiveness of gender stereotypes in every corpus. Using gender stereotypes as the focal issue, we unite 19th-century theories of collective representations and 21st-century evidence on implicit social cognition to understand the subtle yet persistent presence of collective representations in language.

Intergroup attitudes (evaluations) are generalized valence attributions to social groups (e.g., white-bad/Asian-good), whereas intergroup beliefs (stereotypes) are specific trait attributions to social groups (e.g., white-dumb/Asian-smart). When explicit (selfreport) measures are used, attitudes toward and beliefs about the same social group are often related to each other but can also be dissociated. The present work used three approaches (correlational, experimental, and archival) to conduct a systematic investigation of the relationship between implicit (indirectly revealed) intergroup attitudes and beliefs. In study 1 (n = 1,942), we found significant correlations and, in some cases, evidence for redundancy, between Implicit Association Tests (IATs) measuring attitudes toward and beliefs about the same social groups (mean r = 0.31, 95% confidence interval: [0.24; 0.39]). In study 2 (n = 383), manipulating attitudes via evaluative conditioning produced parallel changes in belief IATs, demonstrating that implicit attitudes can causally drive implicit beliefs when information about the specific semantic trait is absent. In study 3, we used word embeddings derived from a large corpus of online text to show that the relative distance of 22 social groups from positive vs. negative words (reflecting generalized attitudes) was highly correlated with their distance from warm vs. cold, and even competent vs. incompetent, words (reflecting specific beliefs). Overall, these studies provide convergent evidence for tight connections between implicit attitudes and beliefs, suggesting that the dissociations observed using explicit measures may arise uniquely from deliberate judgment processes. attitudes | Implicit Association Test | implicit social cognition | stereotypes | word embeddings

Other 415 Correction to Tenney et al. (2018) 443 Correction to Williams, George-Jones, and Hebl (2018) 466 E-