Quebec’s Institutional Reconfiguration and the Reengineering Process: Lessons from Ontario
Bibliographic record
Abstract
The sustained interest in the potential of the public-private partnership formula (PPP) to take on the challenges relating to public finance crises and a gap in infrastructure faced by several countries is fuelled by a discourse on efficiency, and by the novelty and uniqueness of the way every political entity (state, province) is managing its PPPs. The discourse surrounding PPPs, built around themes like cooperation, corporate accountability and service improvement, is replacing the language of competition that was commonplace during the late 1970s and early 1980s. To some, these discourses represent the latest chapter in “the privatization of government services”, whereas others criticize the confusion and rhetoric built around a concept in the process “of becoming just another public policy reform fad.” Inspired by a text written by Neil Bradford, we explore the outcomes of two economic innovation strategies that occurred respectively under the reign of Bob Rae’s NDP government (1990-1995) and Mike Harris’ Conservatives (1995-2002) in Ontario. Bradford makes the point that the Conservatives narrow and market-based partnership approach succeeded where the NDP’s broad partnership approach failed. This was in part due to an inadequate institutional configuration. Based on this observation, the case of Quebec will be assessed in order to determine whether there is a better institutional fit between the reengineering process being considered and the Quebec government’s potential for innovation and its state capacity.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.026 | 0.008 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".