Revolution Within A Revolution: Québec's experiment with co-operative health care & social service delivery
Bibliographic record
Abstract
Québec's decade of experimentation with health care and social service co-operatives has given rise to a reconfiguration of the actors in the health system. No longer do people talk about a system with two actors. Rather than wait for the State or for physician-entrepreneurs to supply needed services, more and more citizens are taking effective action through the structure of the solidarity co-op or that of the nonprofit community-based organization. Without discounting the importance of the state in health care, Girard invokes economist Gilles Paquet who “Forget the Quiet Revolution” whose analysis of state intervention in the 60’s across numerous sectors of Quebec society leads to his conclusion that a new social consciousness is required – “one that prizes initiative and local development and eases the grip of State supervision and protection”. Girard demonstrates that concrete results are being achieved. However, he points out that success it is not a foregone conclusion, citing several examples on the other side of the ledger. Nevertheless, the problems in the health care system and a steadily aging demographic will, Girard believes, lead to a multiplication of initiatives that reconfigure the relationship between citizens, professionals, insurance claimants and the community.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.016 | 0.010 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.010 | 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".