Is the face a window to the soul? Investigation of the accuracy of intuitive judgments of the trustworthiness of human faces.
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Although trustworthiness judgments based on a stranger's face occur rapidly (Willis & Todorov, 2006), their accuracy is unknown. We examined the accuracy of trustworthiness judgments of the faces of 2 groups differing in trustworthiness (Nobel Peace Prize recipients/humanitarians vs. America's Most Wanted criminals). Participants viewed 34 faces each for 100 ms or 30 s and rated their trustworthiness. Subsequently, participants were informed about the nature of the 2 groups and estimated group membership for each face. Judgments formed with extremely brief exposure were similar in accuracy and confidence to those formed after a long exposure. However, initial judgments of untrustworthy (criminals') faces were less accurate (M = 48.8%) than were those of trustworthy faces (M = 62.7%). Judgment accuracy was above chance for trustworthy targets only at Time 1 and slightly above chance for both target types at Time 2. Participants relied on perceived kindness and aggressiveness to inform their rapidly formed intuitive decisions. Thus, intuition plays a minor facilitative role in reading faces.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.002 | 0.013 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.004 | 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 it