Bibliographic record
Abstract
Studies that seek to understand and improve health care systems benefit from qualitative methods that employ theory to add depth, complexity, and context to analysis. Theories used in health research typically emerge from social science, but these can be inadequate for studying complex health systems. Mental health rehabilitation programs for criminal courts are complicated by their integration within the criminal justice system and by their dual health-and-justice objectives. In a qualitative multiple case study exploring the potential for these mental health court programs in Arctic communities, we assess whether a legal theory, known as therapeutic jurisprudence, functions as a useful methodological theory. Therapeutic jurisprudence, recruited across discipline boundaries, succeeds in guiding our qualitative inquiry at the complex intersection of mental health care and criminal law by providing a framework foundation for directing the study's research questions and the related propositions that focus our analysis.
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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 | 0.412 | 0.296 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.009 | 0.008 |
| Science and technology studies | 0.028 | 0.248 |
| Scholarly communication | 0.027 | 0.023 |
| Open science | 0.006 | 0.028 |
| Research integrity | 0.013 | 0.018 |
| 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".