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Record W2196734308

Innovation and Adaptation The Future of PPPs within a New Financial Paradigm

2011· preprint· en· W2196734308 on OpenAlexaboutno aff
Martin Haran, Alastair Adair, Michael McCord, Norman Hutchison

Bibliographic record

VenueRePEc: Research Papers in Economics · 2011
Typepreprint
Languageen
FieldBusiness, Management and Accounting
TopicPublic-Private Partnership Projects
Canadian institutionsnot available
Fundersnot available
KeywordsInvestment (military)StakeholderPrivate sectorBusinessComparabilityPublic sectorMaturity (psychological)Quality (philosophy)FinanceEconomicsPublic economicsEconomic growthEconomyPolitical science
DOInot available

Abstract

fetched live from OpenAlex

<p>Public Private Partnerships have made a substantive contribution to the upgrade in infrastructure quality around the world enhancing resident quality of life and supporting economic development. The rollout of the PPP model has not met with universal approval however; indeed in some countries there has been strong resistance to PPPs with misgivings centered on the level of private sector profiteering as well as the long-term obligations placed on the tax-payer. The scale of the infrastructural investment challenge will nonetheless necessitate greater collaboration between the public and private sectors going forward if the infrastructural investment gap is to be addressed. As economies around the world begin the process of transition between recession and recovery it is imperative that key stakeholder groupings work together to formulate long-term infrastructural objectives, create efficient and transparent implementation and operational strategies as well as conceptualising and developing innovative investment models. This paper examines the case for and against the continued expansion of PPPs as a conduit for private sector investment in essential infrastructural provision. The paper reflects the views and opinions of key stakeholder groupings across five PPP markets namely, Australia, Canada, India the US and the UK. The rationale was to reflect the experiences and challenges across jurisdictions at different stages in the PPP maturity cycle. To facilitate comparability, statistics used in the quantitative evaluation are drawn from the Infrastructure Journal (IJ) online database.</p>

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 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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.369
Threshold uncertainty score0.830

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.001
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 head0.073
GPT teacher head0.296
Teacher spread0.223 · 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 teacher head, 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

Citations0
Published2011
Admission routes1
Has abstractyes

Explore more

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