Challenges Facing Child Psychiatry in Quebec at the Dawn of the 21st Century
Bibliographic record
Abstract
OBJECTIVES: This study aimed to identify hospital resources by region, determine human resources by type of service and region, and describe how services generally operate in child psychiatry within the province of Quebec. METHODS: Data collection took place from May to October 2001. We sent a semistructured questionnaire to all child psychiatry service heads. We collected human resource data and produced organizational charts based on the responses obtained. These charts were forwarded to each of the participating services for validation. We grouped Quebec's 18 social health regions into 3 categories: central (4 regions with 606 370 youths), adjoining (4 regions with 589 750 youths), and peripheral (10 regions with 368 635 youths). RESULTS: The response rate was 100%. We identified 35 child psychiatry services: 13 in the central regions, 9 in the adjoining regions, and 13 in the peripheral regions. Overall, we identified 177 short-stay beds, 476 places in day or evening hospitals, and 113 places in day or evening centres. Most of these resources were located in the central regions. Quebec had 138.2 full-time equivalent (FTE) child psychiatrists (69.8% in the central regions) and 706 FTE professionals. At March 31, 2001, 4285 youths were waiting for services. CONCLUSIONS: We observed a shortage of child psychiatrists and professionals, regardless of the norm used. Adjoining and peripheral regions should have access to a minimal range of human and hospital resources in child psychiatry.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".