Quality of Life Research in Saskatoon, Canada: Fifteen years of co-creating knowledge and action in the community
Bibliographic record
Abstract
The quality of life research program was envisioned as an undertaking to achieve deep and balanced (quantitative and qualitative) understanding of the community and to use this knowledge to guide change to improve quality of life for all in Saskatoon. To accomplish this, the program set its sights on undertaking participatory action research, soliciting meaningful and frequent input from the community at large not only on research questions and methods but also on the implication of results, and disseminating knowledge widely. The program was intended to be longterm and longitudinal (repeated cohorts) to allow ongoing evaluation and monitoring of community outcomes, and continued guidance for ways of improving quality of life.
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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 | 0.031 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.017 | 0.008 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.001 | 0.005 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".