Fetal alcohol spectrum disorder diagnostic clinics in Canada: “It wouldn’t happen if nobody wanted it to happen”
Bibliographic record
Abstract
BACKGROUND: We address the question: If you wanted to start a fetal alcohol spectrum disorder (FASD) diagnostic clinic, what would you need to do, think about, and plan for, from a policy perspective? Our aims were to understand how clinics are developed and established and the key factors that facilitate their success. METHOD: Within a pragmatist epistemology, we conducted a basic qualitative study using semistructured interviews. Interviews were conducted with 12 key informants from 10 diagnostic clinics. Data were analysed using iterative thematic analysis. RESULTS: We derived five themes pertaining to our objectives: (i) listening and responding to your community; (ii) community buy-in and practical steps; (iii) multidisciplinary team trust, respect, and collaboration; (iv) the clinic coordinator; and (v) promoting uniqueness and learning from each other. CONCLUSIONS: Our findings demonstrated the importance of local, community-based planning, team cohesion, and opportunities for mentorship in the development of new FASD clinical services.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.011 | 0.005 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".