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Dasgupta and Greenwald (2001) demonstrated that exposure to positive Black exemplars (e.g., Colin Powell) and negative White exemplars (e.g., Jeffrey Dahmer) can reduce implicit pro-White/anti-Black evaluations, as measured by an Implicit Association Test. Here, we report seven preregistered online experiments conducted with volunteer U.S. participants (N = 6,953) that sought to replicate and probe the boundary conditions of this finding. Contrary to expectations, we found no shift in implicit racial evaluations in two close replication attempts (Experiments 1–2). Experiments 3–4 ruled out the possibility of insufficiently strong exemplar valence and subtyping as explanations for the failures to replicate. In Experiment 5, implicit racial evaluations did exhibit malleability in response to two different procedures relying on repeated evaluative pairings and evaluative statements, suggesting that they are capable of change. With insight from these studies, Experiments 6–7 were mounted with modifications to the Dasgupta and Greenwald (2001) procedure. Significant reductions in implicit pro-White/anti-Black evaluations were now observed when race, valence, and the contingency between the two were highlighted. In addition, across all experiments, the magnitude of shift in implicit racial evaluations was significantly predicted by participants' ability to recall the Black–positive and White–negative contingencies experienced during the exemplar exposure task. Together, these data suggest that exposure to counterattitudinal exemplars can shift implicit racial evaluations toward neutrality, but such malleability strongly depends on contingency awareness. We discuss implications for social cognitive theory, theoretically informed debiasing interventions, and different paths toward resolving initial replication failures. [ABSTRACT FROM AUTHOR]

People can predict their scores on the Implicit Association Test with remarkable accuracy, challenging the traditional notion that implicit attitudes are inaccessible to introspection and suggesting that people might be aware of these attitudes. Yet, major open questions about the mechanism and scope of these predictions remain, making their implications unclear. Notably, people may be inferring their attitudes from externally observable cues (e.g., in the simplest case, their demographic information) rather than accessing them directly. This problem is exacerbated by the fact that, in past work, predictions have been obtained only for a small set of targets, attitudes toward which are demonstrably possible to infer. Here, in an adversarial collaboration with eight preregistered studies (N = 8,011), we interrogate implicit attitude awareness using more stringent tests. We demonstrate that people can predict their implicit attitudes (a) across a broad range of targets (many of which are plausibly difficult to infer without introspection), (b) far more accurately than third-party observers can based on demographic information, and (c) with similar accuracy across two different widely used implicit measures. On the other hand, predictive accuracy (a) varied widely across individuals and attitude targets and (b) was partially explained by inference over nonintrospective cues such as demographic variables and explicit attitudes; moreover, (c) explicit attitudes explained considerably larger portions of variance in predictions than implicit attitudes did. Taken together, these findings suggest that successful predictions of one's implicit attitudes may emerge from multiple mechanisms, including inference over nonintrospective cues and genuine introspective access. [ABSTRACT FROM AUTHOR]

Based on 660 effect sizes obtained from 23,255 adult participants across 51 reports of experimental studies, this meta-analysis investigates whether and when explicit (self-reported) and implicit (indirectly revealed) evaluations reflect relational information (how stimuli are related to each other) over and above co-occurrence information (the fact that stimuli have been paired with each other). Using a mixed-effects metaregression, relational information was found to dominate over contradictory co-occurrence information in shifting both explicit (mean Hedges' g = 0.97, 95% CI [0.89, 1.05], 95% PI [0.24, 1.70]) and implicit evaluations (g = 0.27, 95% CI [0.19, 0.35], 95% PI [−0.46, 1.00]). However, considerable heterogeneity in relational effects on implicit evaluation made moderator analyses necessary. Implicit evaluations were particularly sensitive to relational information (a) in between-participant (rather than within-participant) designs; when (b) co-occurrence information was held constant (rather than manipulated); (c) targets were novel (rather than known); implicit evaluations were measured (d) first (rather than last) and (e) using an affect misattribution procedure (rather than an Implicit Association Test or evaluative priming task); and (f) relational and co-occurrence information were presented in temporal proximity (rather than far apart in time). Overall, the present findings suggest that both implicit and explicit evaluations emerge from a combination of co-occurrence information and relational information, with relational information usually playing the dominant role. Critically, variability in these effects highlights a need to refocus attention from existence proof demonstrations toward theoretical and empirical work on the determinants and boundary conditions of the influences of co-occurrence and relational information on explicit and implicit evaluations. [ABSTRACT FROM AUTHOR]

Implicit evaluations (attitudes) are often described as resistant to change, especially when they were initially formed in a seemingly associative manner, such as via repeated evaluative pairings (REP), and new learning is created via propositional material, such as evaluative statements (ES). The present research (total N = 2,124) tested the responsiveness of implicit evaluations instantiated via REP to updating via different types of ES. In Experiment 1, initial learning was created via repeatedly pairing a novel target with strongly negative stimuli (screams) in an aversive REP (A-REP) task. Subsequent ES of opposing valence providing diagnostic information about the target's behavior substantially updated implicit (IAT) evaluations. In Experiment 2, behavioral ES resulted in successful updating after A-REP whether or not they provided an explanation for the initial A-REP learning. A previously unobtained result emerged in Experiment 3 showing that updating was durable even after 1 day. Finally, in Experiment 4, implicit evaluations were updated via diagnostic behavioral ES, but not via an ES instruction to suppose that different pairings had occurred during A-REP. Taken together, these experiments challenge associative theories of implicit evaluation by demonstrating that diagnostic behavioral statements can durably override the effects of initial learning on implicit evaluations, even if such initial learning is aversive and involves direct experience with stimulus pairings. Moreover, by showing that verbal manipulations based on diagnostic behavior but not a mere supposition instruction had impact, the present project advances theory by starting to identify the nature of learning that can adaptively update social impressions. [ABSTRACT FROM AUTHOR]

Using data from 217 research reports (N = 36,071, compared to 3,471 and 5,433 in previous meta-analyses), this meta-analysis investigated the conceptual and methodological conditions under which Implicit Association Tests (IATs) measuring attitudes, stereotypes, and identity correlate with criterion measures of intergroup behavior. We found significant implicit–criterion correlations (ICCs) and explicit–criterion correlations (ECCs), with unique contributions of implicit (β =.14) and explicit measures (β =.11) revealed by structural equation modeling. ICCs were found to be highly heterogeneous, making moderator analyses necessary. Basic study features or conceptual variables did not account for any heterogeneity: Unlike explicit measures, implicit measures predicted for all target groups and types of behavior, and implicit, but not explicit, measures were equally associated with behaviors varying in controllability and conscious awareness. However, ICCs differed greatly by methodological features: Studies with a declared focus on ICCs, standard IATs rather than variants, high-polarity attributes, behaviors measured in a relative (two categories present) rather than absolute manner (single category present), and high implicit–criterion correspondence (k = 13) produced a mean ICC of r =.37. Studies scoring low on these variables (k = 6) produced an ICC of r =.02. Examination of methodological properties—a novelty of this meta-analysis—revealed that most studies were vastly underpowered and analytic strategies regularly ignored measurement error. Recommendations, along with online applications for calculating statistical power and internal consistency are provided to improve future studies on the implicit–criterion relationship. [ABSTRACT FROM AUTHOR]

When tested immediately, evaluative statements (ES; verbal information about upcoming categories and their positive/negative attributes) surprisingly shift implicit (IAT) attitudes more effectively than repeated evaluative pairings (REP; actual pairing of category members with positive/negative attributes). The present project (total N = 5,317) explored the shared and unique features of these two attitude change modalities by probing (a) commonalities visible in the extent to which propositional inferences created by ES infiltrate REP learning and (b) differences visible in performance of ES and REP learning over time. In REP. the number of stimulus pairings (varied parametrically from 4 to 24) produced no effect (Study 1), but verbally describing stimulus pairings as diagnostic versus nondiagnostic did modulate learning (Study 2), suggesting that even REP give rise to some form of propositional representation. On the other hand, learning from ES decayed quickly, whereas learning from REP remained stable over time both within an immediate session of testing (Study 3) and following a 15-min delay (Study 4), revealing a difference between these two forms of learning. Beyond their theoretical import, these findings may inform interventions designed to produce short- and long-term change in implicit attitudes. [ABSTRACT FROM AUTHOR]

Six experiments, involving a total of 6,492 participants, were conducted to investigate the relative effectiveness of repeated evaluative pairings (REP; exposure to category members paired with pleasant or unpleasant images), evaluative statements (ES; verbally signaling upcoming pairings without actual exposure), and their combination (ES + REP) in shifting implicit social and nonsocial attitudes. Learning modality (REP, ES, and ES + REP) was varied between participants and implicit attitudes were assessed using an Implicit Association Test (IAT). Study 1 (N = 675) used fictitious social groups (NIFFs and LAAPs), Study 2 (N = 1,034) used novel social groups (humans with long vs. square faces), Study 3 (N = 1,072) used nonsocial stimuli (squares vs. rectangles), and Study 4 (N = 848) and Study 5 (N = 958) used known social groups (young vs. elderly; American vs. foreign). ES were more effective than REP and no less superior than ES + REP in producing implicit attitude change. Results were robust across social and nonsocial domains and for known and novel groups. Study 6 (N = 1,905) eliminated time on intervention, levels of construal, and expectancy effects as possible explanations for these findings. Associative theories of implicit evaluation posit that implicit attitudes should shift piecemeal over time; yet, in these experiments, one-shot language-based learning led to larger shifts in implicit attitude than exposure to stimulus pairings. Moreover, the redundancy observed in REP + ES suggests that attitude acquisition from repeated pairings and evaluative instructions may rely on shared mental representations. [ABSTRACT FROM AUTHOR]

Open data collected from research participants creates a tension between scholarly values of transparency and sharing, on the one hand, and privacy and security, on the other hand. A common solution is to make data sets anonymous by removing personally identifying information (e.g., names or worker IDs) before sharing. However, ostensibly anonymized data sets may be at risk of re-identification if they include demographic information. In the present article, we provide researchers with broadly applicable guidance and tangible tools so that they can engage in open science practices without jeopardizing participants' privacy. Specifically, we (a) review current privacy standards, (b) describe computer science data protection frameworks and their adaptability to the social sciences, (c) provide practical guidance for assessing and addressing re-identification risk, (d) introduce two open-source algorithms developed for psychological scientists-MinBlur and MinBlurLite-to increase privacy while maintaining the integrity of open data, and (e) highlight aspects of ethical data sharing that require further attention. Ultimately, the risk of re-identification should not dissuade engagement with open science practices. Instead, technical innovations should be developed and harnessed so that science can be as open as possible to promote transparency and sharing and as closed as necessary to maintain privacy and security. (PsycInfo Database Record (c) 2024 APA, all rights reserved).