Co-operative Canada : empowering communities and sustainable businesses
Bibliographic record
Abstract
Introduction: Where We Stand - Place, Enterprise, and Community / Brett Fairbairn Part 1: Globalization, Autonomy, and Cohesion 1 Globalization, Co-operatives, and Social Cohesion / William D. Coleman 2 Nuna Is My Body: What Northerners Can Teach about Social Cohesion / Isobel M. Findlay Part 2: Social Enterprises and Networks 3 Felt That I Had Lost Myself: Credit Unions, Economies, and the Construction of Locality / Brett Fairbairn with Rob Dobrohoczki 4 Autonomy and Identity: Constraints and Possibilities in Western Canada's Co-operative Retailing System / Jason Heit, Murray Fulton, and Brett Fairbairn 5 Social Cohesion in Times of Crisis: Atlantic Canada's Consumers' Community Co-operative / Leslie H. Brown Part 3: New Partnerships and Models 6 Reclaiming Community: Co-operatives and Sectoral Governance in Quebec Forestry / Patrick Gingras and Mario Carrier 7 Rebuilding Home in a Transient World: Globalization, Social Exclusion, and Innovations in Co-operative Housing / Mitch Diamantopoulos and Jorge Sousa 8 Co-operation Reinvented: New Partnerships in Multi-Stakeholder Co-operatives / Jean-Pierre Girard and Genevieve Langlois 9 To See Our Communities Come Alive Again with Pride: (Re)Inventing Co-operatives for First Nations' Needs / Lou Hammond Ketilson 10 Imagination and the Future: Learning from Social Enterprises / Brett Fairbairn Appendix: The Enterprise with Many Names: Establishing a Common Language / Brett Fairbairn Index
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.017 | 0.006 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.031 | 0.002 |
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".