The dynamic time course of stereotype activation: Activation, dissipation, and resurrection.
Bibliographic record
Abstract
Stereotypes activated upon initial exposure to a stereotyped individual may dissipate as the exposure continues. Participants observing a videotaped interview with a Black person showed activation of the stereotype of Black people following 15 s of observation but not following 12 min of observation. However, the discovery of a disagreement with the stereotyped individual may bring the dissipated stereotype back to mind. Participants who discovered, at the end of a 12-min videotaped interview with a Black person, that this person disagreed with them about the verdict in a court case showed activation of the stereotype of Black people, whereas participants who discovered instead that the Black person agreed with them did not. Participants who disagreed with a Black person also applied the Black stereotype to him, but this stereotype application was detected only on an implicit measure of application, not on an explicit measure.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".