Northern Initiative for Social Action: An Occupation-Based Mental Health Program
Bibliographic record
Abstract
Northern Initiative for Social Action (NISA) is a consumer-run, occupation-based, nonprofit organization located in northeastern Ontario, Canada. The NISA organization has grown in response to research revealing few opportunities for participation in personally meaningful and socially valued occupation for persons with mental illness living in the community of study. This article describes a mixed-design research study conducted by the ParNorth Research Unit of NISA and an occupational therapist. The study purposes were to (a) better understand the emerging characteristics of the NISA program and identify which the participants found helpful; (b) evaluate whether participation in NISA improved members' quality of life; and (c) ascertain whether participation reduced members' need for more traditional and costly methods of care (e.g., hospitalization, crisis services). Focus groups, daily participant observation, a quality of life interview, a consumer member survey and objective review of hospitalization data were used for data collection. Qualitative results indicated that NISA helped to meet participants' being, belonging, and becoming needs. Quantitative data indicated that overall, NISA members perceive an improvement in their subjective quality of life and sense of well-being. Their perceptions are supported by minimal use of crisis services and hospitalization, improved socioeconomic status, and several members' success in obtaining paid employment either within or outside NISA. Future challenges include the need to clearly describe the evolving NISA model and to ensure that the growth of this new organization does not exceed secured human or fiscal resources.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 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".