Language acquisition can be truly atypical in autism: Beyond joint attention
Bibliographic record
Abstract
Language profiles in autism are variable and atypical, with frequent speech onset delays, but also, in some cases, unusually steep growth of structural language skills. Joint attention is often seen as a major predictor of language in autism, even though low joint attention is a core characteristic of autism, independent of language levels. In this systematic review of 71 studies, we ask whether, in autism, joint attention predicts advanced or only early language skills, and whether it may be independent of language outcomes. We consider only conservative estimates, and flag studies that include heterogenous samples or no control for non-verbal cognition. Our review suggests that joint attention plays a pivotal role for the emergence of language, but is also consistent with the idea that some autistic children may acquire language independently of joint attention skills. We propose that language in autism should not necessarily be modelled as a quantitative or chronological deviation from typical language development, and outline directions to bring autistic individuals' atypicality within the focus of scientific inquiry.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".