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Record W1991067126 · doi:10.1068/c12250

Fostering meaningful partnerships in public–private partnerships: innovations in partnership design and process management to create value

2015· article· en· W1991067126 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueEnvironment and Planning C Government and Policy · 2015
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicPublic-Private Partnership Projects
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsGeneral partnershipArgument (complex analysis)Process (computing)Public relationsPublic–private partnershipBusinessValue (mathematics)Scale (ratio)Political scienceComputer scienceFinance

Abstract

fetched live from OpenAlex

While public–private partnerships have become increasingly popular for delivering large-scale public infrastructure around the world, a common critique is that the structure of the relationship is typically more akin to contracting out than a truly meaningful collaboration between the partners. In this paper we aim to demonstrate how innovative public–private partnership models can be designed to deepen cooperation and deliver project outcomes that are better than any one partner could achieve on their own. To support our argument, we analyze the case study of a novel partnership between the Toronto District School Board and a condominium developer to redevelop a public high school in Toronto. Our results show that a process management orientation to partnership can build trust between the partners, effectively share project risks, and foster the public support necessary to realize controversial projects.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.319
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
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 head0.175
GPT teacher head0.305
Teacher spread0.130 · 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