Nurses and the Discursive Construction of Procedural Justice in Review Board Hearings
Bibliographic record
Abstract
There has been growing interest about procedural justice in mental health tribunals. A process considered procedurally just increases adherence to treatment, increases compliance with judicial decisions and allows efficient community reintegration. Yet, little is known about how procedural justice is carried out and the role of professionals in its implementation. Stemming from the results of a critical ethnography of the Ontario Review Board, in this article we examine how procedural justice materializes during Review Board hearings and the role of nurses in this materialization. We do so by leveraging Goffman’s work on total institutions and institutional ceremonies. Our findings suggest that nurses participate in activities that provide a perception of procedural justice, rather than serve their patients’ right to true procedural justice. We conclude by recommending that nurses engage in reflections about the distal effects of their clinical practice to broaden the possibilities for resistance within the forensic psychiatric system.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".