Moving forward: a call for Critical ADHD Studies
Bibliographic record
Abstract
Highly effective early autistic activism gave considerable impetus to changes in the way autism research is conceived and carried out, notably through Critical Autism Studies (CAS). Little, though, has been similarly formalised challenging pathology-driven views of other forms of neurodivergence in research. However, there are increasing signs that this is changing, perhaps most particularly concerning ADHD. Here, we propose a tentative outline for what a Critical ADHD Studies – drawing on, bleeding into, and yet retaining its own specificities from both CAS and emergent Neurodiversity Studies – might resemble. This is neither a gate-keeping exercise nor a definitive mapping out of a field. Neither is ‘critical’, here, concerned with discussion of the validity of ADHD diagnoses. Rather, we seek points of intersection and of potential ally-ship, pulling together approaches centring ADHD lived experience, depathologisation, and ADHD affirmative world-making with related fields such as CAS and Neurodiversity Studies.
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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 | 0.276 | 0.270 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.009 | 0.003 |
| Science and technology studies | 0.013 | 0.064 |
| Scholarly communication | 0.026 | 0.076 |
| Open science | 0.009 | 0.027 |
| Research integrity | 0.029 | 0.066 |
| Insufficient payload (model declined to judge) | 0.013 | 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".