Perceptions of Creepiness and the “Kubrick Stare”
Bibliographic record
Abstract
Abstract Creepiness is a commonly experienced but little understood construct. The present study examined the impact of target facial image gender and orientation on perceptions of creepiness, and whether perceptions varied by participant sex and discomfort with ambiguity (DAS). Participants [n = 137, 68.6% female; Mage = 23.71 (9.73) years] rated the creepiness, trustworthiness, and attractiveness of 44 target images – 11 male and 11 female images, in each of two conditions: upright and downward tilted head or “Kubrick stare”. After controlling for participant age, results did not vary significantly by participant sex or DAS level (high vs. low). As predicted, creepiness ratings were significantly higher in the Kubrick stare (vs. upright) condition and for male (vs. female) faces with the magnitude of difference significantly higher for male (vs. female) faces in the Kubrick stare (vs. upright) condition; η2 = .46 [lower limit = .35 and upper limit = .54] vs. η2 = .32 [lower limit = .21 and upper limit = .41], respectively. There was no association between creepiness and trustworthiness in either condition. Results extend our understanding of how we perceive creepiness and the importance of face orientation in social processing.
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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 | 0.002 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".