Sex differences in the ability to recognise non-verbal displays of emotion: A meta-analysis
Bibliographic record
Abstract
The present study aimed to quantify the magnitude of sex differences in humans' ability to accurately recognise non-verbal emotional displays. Studies of relevance were those that required explicit labelling of discrete emotions presented in the visual and/or auditory modality. A final set of 551 effect sizes from 215 samples was included in a multilevel meta-analysis. The results showed a small overall advantage in favour of females on emotion recognition tasks (d=0.19). However, the magnitude of that sex difference was moderated by several factors, namely specific emotion, emotion type (negative, positive), sex of the actor, sensory modality (visual, audio, audio-visual) and age of the participants. Method of presentation (computer, slides, print, etc.), type of measurement (response time, accuracy) and year of publication did not significantly contribute to variance in effect sizes. These findings are discussed in the context of social and biological explanations of sex differences in emotion recognition.
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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 | 0.008 | 0.023 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.012 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".