Reading the room: Autistic traits, gaze behaviour, and the ability to infer social relationships
Bibliographic record
Abstract
Individuals high in autistic traits can have difficulty understanding verbal and non-verbal cues, and may display atypical gaze behaviour during social interactions. The aim of this study was to examine differences among neurotypical individuals with high and low levels of autistic traits with regard to their gaze behaviour and their ability to assess peers' social status accurately. Fifty-four university students who completed the 10-item Autism Quotient (AQ-10) were eye-tracked as they watched six 20-second video clips of people ("targets") involved in a group decision-making task. Simulating natural, everyday social interactions, the video clips included moments of debate, humour, interruptions, and cross talk. Results showed that high-scorers on the AQ-10 (i.e., those with more autistic traits) did not differ from the low-scorers in either gaze behaviour or assessing the targets' relative social status. The results based on this neurotypical group of participants suggest that the ability of individuals high in autistic traits to read social cues may be preserved in certain tasks crucial to navigating day-to-day social relationships. These findings are discussed in terms of their implications for theory of mind, weak central coherence, and social motivation theories of autism.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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 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".