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Record W2498222143 · doi:10.55016/ojs/sppp.v9i1.42578

The Theory and Evidence Concerning Public-Private Partnerships in Canada and Elsewhere

2016· article· en· W2498222143 on OpenAlexaffabout
Matti Siemiatycki, Aidan R. Vining

Bibliographic record

VenueThe School of Public Policy Publications · 2016
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicPublic-Private Partnership Projects
Canadian institutionsSimon Fraser UniversityUniversity of TorontoUniversity of British Columbia
Fundersnot available
KeywordsPolitical sciencePublic administration

Abstract

fetched live from OpenAlex

The popularity of Public-Private Partnerships (PPPs), as a way for governments to get infrastructure built, continues to grow. But while the public is often led to believe that this is because they result in a more efficient use of taxpayer funds and a more streamlined process, this is not necessarily the case. In fact, the clearest advantage that PPPs offers is to politicians, who are able to transfer to private partners the risks of miscalculated construction costs and revenue projections (as with a toll road, for example). For taxpayers, the deals can often work out worse than if the government had simply pursued a fixedprice design-build Public Sector Alternative (PSA) arrangement. Even from the very start of the process, there are often a limited number of private consortia equipped to bid on major PPPs, which already leads to the potential for bidders to build in higher profits, and thus, higher costs for taxpayers. Nor are these private consortia oblivious to the risks they assume; they must therefore build into their bid an effective “insurance premium” to account for unforeseen delays and increased costs. The use of private debt to finance construction further inflates prices over a government’s lower cost of capital. To an incumbent government, a key advantage of PPPs is the ability to avoid upfront costs, and let the private consortium arrange financing until the project is complete, allowing politicians to take the credit for new infrastructure while passing future maintenance and operating costs off onto future politicians, taxpayers and/or users. This, however, only provides both the incentive and bookkeeping artifice — since costs are incurred off the government’s current balance sheet — for governments to build more infrastructure than might otherwise be justified. Advocates of PPP would argue that one clear benefit PPPs do offer the public is an impressive record of bringing in projects on time and on budget. It is true that the inflexibility of contracts and the financial risk transferred to the private partners have a powerful effect in keeping projects on track. However, the yardsticks by which the on-time and on-budget criteria are measured are typically flawed. The “start dates” of PPPs are marked after the conclusion of a lengthy negotiation and project-planning process between a government and a private consortium, making project completions seem more efficient than they really are. Meanwhile, the estimated cost of a project has a tendency to increase during that preliminary process. In other words, the delay and cost inflation that so often characterize traditional PSAs are not magically eliminated in a PPP: they just tend to occur prior to the first shovel breaking ground, rather than incrementally over the course of the project’s construction. Ultimately, several of the problems common to traditional government PSA projects, and supposedly absent from PPP arrangements, are still there, only much harder to discern. The costs can be just as high, if not higher than with a fixed-price PSA, the timeframes can be just as lengthy, when the entire process is accounted for, and the amount of government resources tied up in the negotiation and planning process will often rival that of traditional procurement methods. Furthermore, all those risks that are supposedly transferred to private players are never truly transferred: The government is always the residual risk holder should the consortium somehow fail. From a policy standpoint, the measure of whether PPPs are worthwhile should be based not on whether they come in on time or on budget, but whether they increase social value relative to a PSA. There is, currently, no convincing evidence that they do.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.036
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.854
Threshold uncertainty score0.990

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.036
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.014
Science and technology studies0.0170.009
Scholarly communication0.0110.005
Open science0.0030.005
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0210.001

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.

Opus teacher head0.111
GPT teacher head0.296
Teacher spread0.186 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations39
Published2016
Admission routes2
Has abstractyes

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