The face of an angel: Effect of exposure to details of moral behavior on facial recognition memory.
Bibliographic record
Abstract
a b s t r a c t The Dangerous Decisions Theory (DDT; Porter & ten Brinke, 2009) posits that instantaneous perceptions of trustworthiness based on a stranger's face influence the manner in which ensuing information about the target is processed. This study tested a bi-directional DDT model, proposing that information concern- ing a target's moral behavior could distort eyewitness memory for the individual's facial trustworthiness. Participants (N = 141) viewed a target individual's face (previously rated as appearing neutral on trust- worthiness) and then were exposed to one of the three vignettes describing the target's behavior (either immoral, morally neutral, or altruistic). Following a delay, observers were asked to identify the target individual on a facial morph video (continuously ranging in levels of perceived trustworthiness). Results indicated that behavioral information varying in morality influenced facial recognition memory; specifi- cally, faces were recalled as having less trustworthy features following a disclosure of immoral/criminal behavior.
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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 | 0.001 | 0.010 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".