Does Accountability Attenuate or Amplify Stereotyping? The Role of Implicit Theories
Bibliographic record
Abstract
Does accountability (the expectation that one will be called on to justify one's beliefs or actions to others) attenuate or amplify stereotyping? The authors hypothesized that the effect of accountability on stereotype use in impression formation depends on perceivers' implicit theory (entity versus incremental). The authors assessed the effects of accountability and implicit theories on participants' impression of the target (Studies 1 and 2), attention to the target's stereotype-consistent versus -inconsistent behavior (Study 1), and sense of being entitled to judge the target (Study 2). In both studies, accountability amplified the stereotypicality of entity theorists' impressions but, if anything, attenuated the stereotypicality of incremental theorists' impressions. Moreover, in Study 1, the more attention accountable entity (but not incremental) theorists paid to counterstereotypic information, the more stereotype-driven were their impressions. In Study 2, for entity theorists but not incremental theorists, perceived judgeability mediated the relationship between accountability and stereotypicality of judgment.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.034 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".