Are people with autism prosopagnosic?
Bibliographic record
Abstract
Difficulties in various face processing tasks have been well documented in autism spectrum disorder (ASD). Several meta-analyses and numerous case-control studies have indicated that this population experiences a moderate degree of impairment, with a small percentage of studies failing to detect any impairment. One possible account of this mixed pattern of findings is heterogeneity in face processing abilities stemming from the presence of a subpopulation of prosopagnosic individuals with ASD alongside those with normal face processing skills. Samples randomly drawn from such a population, especially relatively smaller ones, would vary in the proportion of participants with prosopagnosia, resulting in a wide range of group-level deficits from mild (or none) to severe across studies. We test this prosopagnosic subpopulation hypothesis by examining three groups of participants: adults with ASD, adults with developmental prosopagnosia (DP), and a comparison group. Our results show that the prosopagnosic subpopulation hypothesis does not account for the face impairments in the broader autism spectrum. ASD observers show a continuous and graded, rather than categorical, heterogeneity that span a range of face processing skills including many with mild to moderate deficits, inconsistent with a prosopagnosic subtype account. We suggest that pathogenic origins of face deficits for at least some with ASD differ from those of DP.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.013 |
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".