Rethinking diagnosis-based service models for childhood neurodevelopmental disabilities in Canada: a question of equity
Bibliographic record
Abstract
Neurodevelopmental disability in children covers a vast array of congenital and acquired long-term conditions associated with brain or neuromuscular impairments that impact function. While some presentations of neurodevelopmental disability align with diagnostic labels, many do not, leaving children whose conditions don't fit neatly under diagnostic labels struggling to access services or families and professionals feeling pressured to assign a diagnostic label in order to access services. In this paper, we (1) discuss the evidence showing that there is often a mismatch between a child's neurodevelopmental diagnosis, or lack of diagnosis, and function, (2) comment on the inequities exacerbated by diagnosis-based approaches for services, and (3) highlight the potential benefits of using a function and participation-based approach for providing services to children with neurodevelopmental disabilities. We close with three calls to action for function and participation-based approaches that could better support equitable services for children with neurodevelopmental disabilities.
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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 | 0.045 | 0.090 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.018 | 0.016 |
| Scholarly communication | 0.015 | 0.011 |
| Open science | 0.009 | 0.013 |
| Research integrity | 0.007 | 0.016 |
| Insufficient payload (model declined to judge) | 0.007 | 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".