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Record W2058849321 · doi:10.1177/0095399711413868

The Public–Private Partnership Enabling Field

2011· article· en· W2058849321 on OpenAlexaboutno aff
Stephan F. Jooste, W. Richard Scott

Bibliographic record

VenueAdministration & Society · 2011
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicPublic-Private Partnership Projects
Canadian institutionsnot available
FundersRoyal SocietyInter-American Development BankAsian Development Bank
KeywordsIntermediaryGeneral partnershipSalientOrganizational fieldField (mathematics)Public–private partnershipPublic administrationPrivate sectorPublic relationsThrough-the-lens meteringBusinessPolitical scienceRegional scienceSociologyLens (geology)Institutional theoryMarketingEngineeringFinanceSocial science

Abstract

fetched live from OpenAlex

This study investigates the emergence of a collection of diverse organizations designed to enable and govern infrastructure public–private partnerships (PPPs). The authors use the concept of organizational fields as a theoretical lens to investigate this panoply of organizations in three international contexts: British Columbia (Canada), Victoria (Australia), and South Africa. They observe a similar set of actors in each of these “PPP-enabling fields” but detect significant variation in the actor characteristics and the way that they are arranged on different projects. They theorize on a number of PPP-enabling fields aspects, including typical project arrangements, predominant field intermediaries, and salient institutional logics.

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)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.004
Science and technology studies0.0050.007
Scholarly communication0.0060.007
Open science0.0010.006
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.091
GPT teacher head0.280
Teacher spread0.189 · 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 designTheoretical or conceptual
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

Citations77
Published2011
Admission routes1
Has abstractyes

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