ADHD Assessment and Diagnosis in Canada: An Inconsistent but Fixable Process
Bibliographic record
Abstract
Canadian teachers in inclusive classrooms are encountering more students with ADHD-like behaviours and making more referrals for formal diagnosis of the condition. Previous research suggests that ADHD diagnoses are susceptible to highly inconsistent and arbitrary assessment processes/criteria (Sanford & Rid-ley, 1995), thus probably contributing to teachers’ lack of effective interventions. This study sought to establish whether Canadian ADHD diagnosticians were spe-cifically identified, whether common diagnostic criteria/guidelines were used, and whether diagnostic processes were empirically grounded. One-hundred and se-venty-six official documents from the prominent Canadian organizations vested in ADHD diagnosis were examined. The results revealed that various professionals provide ADHD diagnoses, that few organizations had clear diagnostic guidelines, and that few organizations outlined theoretical foundations for ADHD aside from references to DSM-IV-TR criteria. This evidence suggests a three-fold potential for compounding inconsistencies in ADHD diagnoses. Recommendations for standardized criteria and processes to remediate these pervasive inconsistencies are provided.
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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 | 0.017 | 0.055 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.009 |
| Science and technology studies | 0.013 | 0.004 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".