MétaCan
Menu
Back to cohort
Record W2972182074 · doi:10.1111/padm.12626

How do professionals perceive the governance of public–private partnerships? Evidence from Canada, the Netherlands and Denmark

2019· article· en· W2972182074 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

VenuePublic Administration · 2019
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicPublic-Private Partnership Projects
Canadian institutionsUniversity of Toronto
FundersRijkswaterstaatDeltaresNederlandse Organisatie voor Wetenschappelijk Onderzoek
KeywordsCorporate governancePublic administrationBusinessPolitical sciencePublic relationsFinance

Abstract

fetched live from OpenAlex

Abstract In public–private partnerships (PPPs), the collaboration between public and private actors can be complicated. With partners coming from different institutional backgrounds and with different interests, governing these partnerships is important to ensure the projects' progress. There is, however, little knowledge about the perceptions of professionals regarding the governance of PPPs. This study aims to exlore professionals' viewpoints about governing PPPs, and to explain potential differences using four theoretical governance paradigms. Using Q methodology, the preferences of 119 public and private professionals in Canada, the Netherlands and Denmark are explored. Results show four different viewpoints regarding the governance of PPPs. Experience, country and the public–private distinction seem to influence these viewpoints. Knowledge of these differences can inform efforts to govern PPPs and contribute to more successful partnerships.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.286
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0020.003
Open science0.0010.000
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 head0.064
GPT teacher head0.268
Teacher spread0.204 · 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