Working with Toronto neighbourhoods toward developing indicators of community capacity
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Often the goal of health and social development agencies is to assess communities and work with them to improve community capacity. Particularly for health promoters working in community settings and to ensure consistency in the definition of health promotion, the evaluation of health promotion programmes should be based on strengths and assets, yet existing information for planning and evaluation purposes usually focuses on problems and deficits. A model and definition of community capacity, grounded in community experience and focusing on strengths and assets, was developed following a 4-year, multi-site, qualitative, action research project in four Toronto neighbourhoods. There was significant community involvement in the four Community Advisory Committees, one for each study site. Semi-structured, open-ended interviews and focus groups were conducted with 161 residents and agency workers identified by the Community Advisory Committees. The data were analyzed with the assistance of NUDIST software. Thematic analysis was undertaken in two stages: (i) within each site and (ii) across sites, with the latter serving as the basis for the development of indicators of community capacity. This paper presents a summary of the research, the model and the proposed indicators. The model locates talents and skills of community members in a larger context of socioenvironmental conditions, both inside and outside the community, which can act to enable or constrain the expression of these talents and skills. The significance of the indicators of community capacity proposed in the study is that they focus on identifying and measuring the facilitating and constraining socioenvironmental conditions.
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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 | 0.003 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it