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Record W2616514390 · doi:10.1177/1087724x17709791

P3 Infrastructure Projects: A Recipe for Corruption or an Antidote?

2017· article· en· W2616514390 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuePublic Works Management & Policy · 2017
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicPublic-Private Partnership Projects
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsLanguage changeProcurementStructuringBusinessPerspective (graphical)Public economicsPublic administrationPolitical scienceEconomicsFinanceMarketingComputer science

Abstract

fetched live from OpenAlex

Public–private partnerships (P3s) have emerged as a leading means of structuring large, complex infrastructure projects in both developed and developing economies alike. However, P3s, due to their unique characteristics, can present opportunities for corruption. The purpose of this article is to promote the development of a nuanced and thorough understanding of P3 corruption risks such that those involved in developing, designing, and implementing P3s can more effectively harness the benefits of P3s while mitigating the corruption risks they introduce. This article also seeks to encourage further research into how infrastructure P3s can be better shaped to decrease the probability of corruption risks materializing. This article unpacks how and why P3s, as a distinct form of public procurement, are at once more and less susceptible to corruption as compared with traditional procurement methods and as such deserve special attention from an anticorruption perspective.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.818
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0020.000
Scholarly communication0.0090.011
Open science0.0020.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.082
GPT teacher head0.336
Teacher spread0.254 · 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