Sex and gender impacts on the behavioural presentation and recognition of autism
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
PURPOSE OF REVIEW: With increasing awareness of potential differences of autism presentation in nonmale versus male individuals, this review summarizes the rapidly evolving literature on sex and gender impacts on autism across nosology, behavioural presentation, developmental change and contextual recognition biases. RECENT FINDINGS: Most studies have not differentiated sex versus gender impacts. Regarding behavioural presentation, measurement invariance across sex/gender was found in several standard measures. On this basis, diagnosed females overall showed lower restricted/repetitive behaviour/interests/activities (RRBI) than males, with small and variable effects depending on age, developmental level and kinds of RRBI. Differences insufficiently captured by standard measures may include autistic females displaying female-gender-typical narrow interests, higher social attention, linguistic abilities, motivation for friendship and more camouflaging than autistic males. Regarding developmental change, diagnosed young girls were more likely to have better cognitive development, less intense autistic symptoms and reduction of symptoms over time. Difficulties in adaptive functioning and social challenges, however, may emerge more for females in adolescence. Regarding diagnosis, general expectancy biases and gender-stereotypes may impede timely recognition of autism in females. SUMMARY: Appreciating the multilevel sex and gender impacts on presentation, development, and diagnosis is key to sex-equitable and gender-equitable care for autistic individuals. A holistic approach to understanding the person in the contexts of sex and gender is essential for timely and accurate diagnosis and support.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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