Accuracy in Categorizing Perceptually Ambiguous Groups
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
Since the 1940s, social psychologists have conducted research testing whether it is possible to accurately identify members of perceptually ambiguous groups. This study quantitatively reviews the research on the perception of ambiguous groups to better understand the human capacity to accurately identify others based on very subtle nonverbal cues. Standard random-effects meta-analytic techniques were used to examine the distinctions between different target groups in terms of their identifiability, as well as to compare rates of accuracy across perceptual modalities (e.g., photographs, audio, video) and other study design differences. Overall, the accuracy of identifying targets was significantly better than chance guessing (i.e., 64.5%). Furthermore, stimulus modality was found to be a moderator of accuracy. Other moderators (e.g., time of exposure, analytic approach) were identified and examined. These data help to document and characterize broad trends in the proliferating and expanding study of the perception and categorization of ambiguous social groups.
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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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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 it