Debate: How far can we modify the expression of autism by modifying the environment?
Bibliographic record
Abstract
Following Green (Child and Adolescent Mental Health, 2023, 28, 438) the emergence of a manifest autistic phenotype, during preschool years, represents a discontinuity from preclinical or subclinical states. We propose that this discontinuity suggests that autistic children experience superior interest for, and processing of non-social information, whereas children without autism favor social information processing. This is produced by perceptual over-functioning, still allowing self-taught non-social language learning in a substantial fraction of prototypical autistic children. A new set of rigorous intervention studies using Pediatric Autism Communication Therapy (PACT), based on the synchrony principle, brought autistic children below the ADOS diagnostic threshold (Whitehouse et al., JAMA Pediatrics, 2021, 175, e213298). We now know that adaptation of the child's social environment can produce changes in the manifestations of autism in the pre-school period and later. However, the limitation of these changes, combine with evidence of non-social learning of language suggests that clinicians should combine lateral tutorship (the parallel, unsynchronous exposure of information) with the synchrony (early dyadic communication and engagement) principle to create a new generation of strength-based interventions.
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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 | 0.027 | 0.043 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.019 |
| Scholarly communication | 0.004 | 0.016 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.021 | 0.024 |
| Insufficient payload (model declined to judge) | 0.010 | 0.006 |
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".