Translating Critical Social Work into Clinical Practice: A Pilot Simulation-Based Study from Canada
Bibliographic record
Abstract
Focused primarily on addressing racial and social injustices through theoretical and critical analysis, critical social work is a well-established paradigm in Canadian social work education. This pilot study explored how clinical social workers might translate critical social work principles into clinical practice. We used simulation-based research methods to observe social workers’ engagement with a Simulated Client (SC; i.e. trained actor). Social workers with at least a Master’s degree (n = 8) were recruited from across Canada to conduct a session with the SC via Zoom followed by a post-session interview to reflect on the session. Data were analyzed inductively, using coding methods from Grounded Theory. The following categories emerged as concrete practice skills informed by critical social work: (1) create and hold a space of safety, (2) take an unassuming position while holding theoretical assumptions, (3) peel off the layers of the presenting problems, and (4) take a non-neutral therapeutic stance. Implications for clinical social work practice and further research are discussed.
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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 | 0.011 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.014 | 0.006 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".