Using a community of practice model to create change for Northern homeless women
Bibliographic record
Abstract
This is a story about three virtual and face-to-face communities which met in the capitals of Canada's three Northern territorial cities over a two-year period to discuss and act on culturally safe and gender-specific services for Northern women (and their children) experiencing homelessness, mental health and substance use concerns. It is a story of how researchers and community-based advocates can work across distance and culture, using co-learning in virtual communities as a core strategy to create relational system change. The three communities of practice were linked through a pan-territorial action research project entitled Repairing the Holes in the Net, in which all participants: learned together, mapped available services, discussed the findings from interviews with northern women about their trajectories of homelessness, analyzed relevant policy, planned local service enhancements, and generally took inspiration from each other.
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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 | 0.026 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.029 | 0.055 |
| Scholarly communication | 0.015 | 0.012 |
| Open science | 0.005 | 0.020 |
| Research integrity | 0.006 | 0.006 |
| 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".