Les collaborations public-privé en santé publique au Canada et la responsabilité publique des acteurs participants: une analyse juridique d'un phénomène émergent
Bibliographic record
Abstract
This thesis penetrates the complex and often opaque universe of collaborations between public and private actors in Canada's public health sector. The thesis examines the diverse facets of four public-private collaborations evolving at the federal level, in Quebec and in British-Columbia, and demonstrates how the law ensures these actors are accountable towards three forums: elected representatives, the auditor general and the citizens. On the basis of these examples, we address the foreseen challenges to public accountability, a pillar of democracy, arising from collaborative governance. Our analysis sheds light on the contribution of the law in this regard, but also on its deficiencies, by distinguishing the respective inputs of the norms stemming strictly from the State and of legal norms developed jointly by collaborating public and private partners. Finally, we conclude that there is a gap between the enthusiasm for public-private collaborations in the public health sector and the recognition of this governance model in the legal norms framing the actors' accountability. This gap might be symptomatic of a difficulty or a delay in the law's adaptation to this emerging governance model.
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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 | 0.009 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.009 |
| Science and technology studies | 0.023 | 0.015 |
| Scholarly communication | 0.018 | 0.005 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".