Mindshift in autism: a call to professionals in research, clinical, and educational settings
Bibliographic record
Abstract
Autistic people often have poor outcomes over the life course, including in health, education, employment, and community inclusion. Many professionals working with Autistic adults in research, clinical, and educational settings devote their careers to trying to improve such outcomes. However, we maintain that real progress cannot happen without a fundamental mindshift. The status quo for professionals is to view autism as an illness. Instead, the neurodiversity movement encourages us to value and embrace autism as an aspect of human diversity and asks us to view Autistic people as a marginalized group that experiences significant disparities. While some professionals may be adopting language and concepts from the neurodiversity movement, we argue that making this mindshift fundamentally changes our practice across research, clinical, and educational settings. In this perspective, we call on professionals to embrace this mindshift to reduce discrimination and stigma, halt the spread of harmful ideologies, and help Autistic adults live fulfilling lives.
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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 | 0.069 | 0.092 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.023 | 0.061 |
| Scholarly communication | 0.018 | 0.043 |
| Open science | 0.006 | 0.039 |
| Research integrity | 0.048 | 0.073 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
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".