Positive, negative, neutral—or unknown? The perceived valence of emotions expressed by young autistic children in a novel context suited to autism
Bibliographic record
Abstract
Starting early in life, autistics are characterized as having atypical facial expressions, as well as decreased positive and increased negative affect. The literature on autistic facial expressions remains small, however, with disparate methods and results suggesting limited understanding of common autistic emotions. Furthermore, unlike non-autistics’ emotions, autistics’ emotions have been assessed without considering this population’s characteristics. In this study, the valence of young children’s facial expressions was thus rated as positive, negative, neutral, or “unknown”—a term for perceived emotions observers do not understand. Facial expressions were assessed using the Montreal Stimulating Play Situation, a context incorporating potential autistic interests. Comparing 37 autistic and 39 typical young (27–56 months) age-matched children, we found no group differences in expressed positive, negative, and neutral emotions. We did find differences in unknown emotions, which were unique to the autistic group. Preliminary data also showed that autistic children’s repetitive behaviors co-occurred with positive, neutral, and unknown emotions, but not with negative emotions. In a novel context that considers their characteristics, we did not find decreased positive or increased negative emotions in young autistic children. Instead, they uniquely expressed emotions perceived as unknown, showing the need to improve our understanding of their full emotional repertoire. Lay abstract Autistic people are believed to have emotions that are too negative and not positive enough, starting early in life. Their facial expressions are also persistently judged to be unusual, as reflected in criteria used to identify autism. But it is possible that common autistic facial expressions are poorly understood by observers, as suggested by a range of findings from research. Another issue is that autistic emotions have always been assessed in contexts suited to non-autistics. In our study, the facial expressions of young autistic and typical children were rated as positive, negative, neutral, or “unknown”—a category we created for emotions that observers notice but do not understand. These emotions were assessed using a context suited to autistic children, including objects of potential interest to them. We found that in this context, autistic and typical children did not differ in positive, negative, or neutral facial emotions. They did differ in unknown emotions, which were found only in autistic children. We also found that repetitive behaviors in autistic children co-occurred with positive, neutral, and unknown emotions, but not with negative emotions. In a context which suits their characteristics, autistic children do not show emotions that are too negative or not positive enough. They do show emotions perceived as unknown, which means we need to improve our understanding of their full emotional repertoire.
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How this classification was reachedexpand
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 | 0.000 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".