Stabilizing Privatization: Crisis, Enabling Fields, and Public-Private Partnerships in Canada
Bibliographic record
Abstract
Public-private partnerships (P3s) -or "cooperative ventures between the state and private business" (Linder, 1999, p.35) -are now commonly used in Canada to deliver public infrastructure such as hospitals, highways, water treatment facilities, and schools.However, despite their growing popularity, P3 arrangements are seldom able to provide better value for money than traditional public procurement given the higher costs associated with private financing and for-profit service delivery.Problems of this sort were only further compounded during the recent global financial crisis as private financing became more expensive and difficult to secure, leading to several project delays and cancellations across the country (Mackenzie, 2009).With the onset of a new round of fiscal austerity as of late, one might reasonably expect that this policy would be scrapped in favour of lower cost public procurement.Instead, as of 2010, the P3 model is flourishing once again.This is particularly problematic given that these arrangements link important public services to highly volatile global financial markets and poorer value for money leads to additional unnecessary costs over the long run.The relatively quick recovery of the P3 model in the face of recent and longstanding concerns requires explanation.One obvious driver is neoliberal ideology and its dogged commitment to privatization.Yet however accurate this explanation may be, on its own it is inadequate since it tells us very little about the specific policy forms that these normative commitments take.To this end, attention is paid here to the changes in public infrastructure decision-making that have occurred 1 Heather Whiteside is a Ph.D.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.023 | 0.008 |
| Scholarly communication | 0.014 | 0.004 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.012 | 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".