From this Earth: NECRC & the evolution of a development system in Winnipeg's North End
Bibliographic record
Abstract
The power and promise of the community development corporation (CDC) lies in the way residents can use it to co-ordinate and focus the energy that people and organizations, near and far, are willing to pour into local revitalization. How does such a sophisticated instrument arise out of the organization of a distressed community and remain true to citizen engagement? Winnipeg's North End Community Renewal Corporation reads like a textbook example of the evolution of a multi-stakeholder, multi-functional CDC. \nIt is useful to review this case alongside that of RESO (Richard, 2004) since this Winnipeg CED organization modelled itself along the same lines, adapting the structures and lessons of Montreal to the very different urban context of north end Winnipeg. Also important to note is that just as this organization concluded its developmental phase, the provincial government designed and initiated financing of a policy and several programs that provided for long term core support for neighbourhood-based CED organizations (see Perry, 2002).
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.007 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".