A survey of the 16 Canadian child and youth protection programs: A threadbare patchwork quilt
Bibliographic record
Abstract
BACKGROUND: Child abuse and neglect (CAN) represents an international public health and societal problem, the extent and nature of which are inadequately understood. Child and youth protection programs (CYPPs), based in 16 Canadian paediatric academic health science centres, identify, manage, treat and prevent cases of CAN. OBJECTIVES: To ascertain the structure, resources and functioning of Canadian CYPPs. METHODS: Telephone interviews were conducted with the directors of the 16 CYPPs. RESULTS: Full-time equivalent staffing ranged from 0.25 to 18.7 people. All programs were staffed with physicians. The majority of programs had social workers (14 of 16) and administrative staff (12 of 16), while fewer programs had a dedicated nurse (nine of 16) or psychologists (six of 16). All CYPPs provided medical examinations and psychosocial assessments, consultation and coordination of CAN cases within the hospital and with community professionals, expert medico-legal opinions and representation in court, and hospital in-service and community outreach education and advocacy. Nine centres participated in regular multi-agency reviews of cases. Fourteen centres had specialized teams for acute sexual assault. Academic activities include lectures to medical students (16 of 16), undergraduate clinical electives (11 of 16), mandatory clinical rotations for paediatric residents (10 of 16) and/or electives (15 of 16), a fellowship (one of 16) and research on CAN-related issues (11 of 16). CAN documentation was inconsistent and limited, underestimating the number of cases assessed within the CYPPs. CONCLUSION: CYPPs appear to need further resources to care for maltreated children and their families. A national, standardized database to document CAN cases would aid in the allocation of resources to help develop policies and programs that effectively address the needs of CAN victims and their families, and to prevent CAN.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".