Teaching Note—Proposing a School Social Work Practice Course for Master of Social Work Students: Call for a Canadian Perspective
Bibliographic record
Abstract
The role of a school social worker in Ontario is multifaceted and evolving. School social work (SSW) practice includes, but is not limited to, advocacy, attendance support, well-being education, equity work, system capacity building, and mental health intervention. Increasingly, SSW practice in Ontario receives implementation support from School Mental Health Ontario, which promotes the delivery of identity-affirming, culturally responsive, and evidenced-informed mental health services within a multitiered system of support (MTSS). This teaching note proposes that, now more than ever, SSW practice is a specialized area of social work that deserves a special topic course to prepare students for work in this unique practice context. Furthermore, this teaching note outlines suggested content themes for an introductory course that is aligned with the MTSS model that encourages a range of service delivery.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.015 | 0.005 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.032 | 0.008 |
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".