Group Decision Making in an Intersectoral Mental Health Community Partnership
Bibliographic record
Abstract
Background: In a major Canadian jurisdiction that includes several regions, an intersectoral working group with community partners was formed to enable change in systems and policies for individuals with serious and persistent mental illness. The top priority of the working group was housing. Purpose: The study explored how the working group members experienced decision-making power in their efforts to enable change in housing policies. Method: The research used a qualitative single-case design to study the decision-making processes as experienced by the group members. Data were collected through individual semi-structured interviews, two focus groups and review of key public documents. The data were analysed using the constant comparative method, with critical reflection on group decision making and the contextual influences of system-level policies. Group members contributed to the analysis. Findings: Amid positive experiences of working together, group members experienced challenges related to power differentials between service providers, government personnel and consumers, and the impact of the systemic environment on the group processes. Implications: Implications are raised for occupational therapy education and practice, and for studying group decision making as an occupation.
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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 | 0.030 | 0.033 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.026 | 0.021 |
| Scholarly communication | 0.011 | 0.005 |
| Open science | 0.003 | 0.017 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".