Public-Private Partnerships: When Ethics and Policy Making are an Afterthought
Bibliographic record
Abstract
The interest of governments in public-private partnerships (P3s) has increased in the last decade. In Canada, this fervor is no exception; decision makers recognize an ideal tool of governance, in the logic of the “new public management.” While academic literature has focused on the actual benefits or problems associated with this form of service delivery - namely cost calculations, risk sharing, contract duration and efficiency - little attention has been paid to the ethical character of this policy instrument. As far as public management in general is concerned, ethics is generally an afterthought (Ghere, 1996). Where P3s are concerned, this quote is even more relevant. Given the efficiency mantra at the heart of P3s as a new policy instrument, it is no wonder that questions of values and public interest come second to promised or expected financial savings sought by political leaders. In order to tackle the role of ethics in public-private partnerships, this article takes a policy formulation stance and stresses the conflicts of values at the heart of this political choice and the challenges it involves for public interest and policy making in the long run.
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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 | 0.078 | 0.081 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.017 | 0.072 |
| Scholarly communication | 0.042 | 0.060 |
| Open science | 0.003 | 0.020 |
| Research integrity | 0.029 | 0.044 |
| Insufficient payload (model declined to judge) | 0.005 | 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".