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Record W6906661464 · doi:10.18280/ijsdp.200603

Diagnosing Government Responsibilities in the Implementation of Public-Private Partnership System for Infrastructure Procurement

2025· article· en· W6906661464 on OpenAlexvenueno aff

Bibliographic record

VenueInternational Journal of Sustainable Development and Planning · 2025
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicPublic-Private Partnership Projects
Canadian institutionsnot available
FundersCovenant University
KeywordsGeneral partnershipProcurementGovernment (linguistics)Government procurement

Abstract

fetched live from OpenAlex

Public-Private Procurement is a system that allows for collaboration between the government and private partners in infrastructure provision.However, researchers argued that the successful implementation of the procurement option rested more on the government's shoulders.Hence, the study aims to identify critical government roles and investigate their importance and performance in PPP projects in Nigeria using a survey approach.The targeted respondents are PPP stakeholders operating in Lagos and Abuja.However, due to the absence of comprehensive lists of the PPP stakeholders involved in PPP projects in Nigeria, a projectbased approach was used in attaining the representative samples for the study, including contractors, consultants, concessionaires, government agencies, and financiers.About 384 copies of questionnaires were randomly distributed to the sample representatives, and 274 copies were retrieved.The data generated were analyzed using descriptive and inferential statistical tools.Findings showed that all the roles identified are critical and showed significant interrelationships with each other.However, the government's performance in the highlighted roles is unsatisfactory, and recommendations were made on its shortfall.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.505
Threshold uncertainty score0.430

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
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 head0.029
GPT teacher head0.304
Teacher spread0.275 · 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 designObservational
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
Published2025
Admission routes1
Has abstractyes

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