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Record W4411656876 · doi:10.51847/4md8v3jx4a

10.51847/4Md8v3jx4a

2000· article· en· W4411656876 on OpenAlexvenueno aff

Bibliographic record

VenueTime to knit · 2000
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicPublic-Private Partnership Projects
Canadian institutionsnot available
Fundersnot available
KeywordsGeneral partnershipPublic–private partnershipBusinessFinance

Abstract

fetched live from OpenAlex

The general objective of this study is to examine the operational guidelines for the adoption of PPP with the view of assessing its success in Nigeria.This is significant because infrastructure development has in recent times assumed a central importance in Nigeria's quest for social and economic stability.Dearth of infrastructure and the unavailability of adequate fund for its development are major challenges to governments.In line with the practices in other developing countries, Nigerian governments at all levels now call on private investors to come to their aid in the form of partnership for the provision of infrastructure.In order to fully reap the benefits of PPP, there are some pre-requisites or critical factors which must be present.The data for this study was generated from Focus Group Discussion and documentary sources from books, journals and online sources.Data was analyzed through the use of analytic techniques derived from qualitative research, primarily thematic analysis (Mannning and Luyt, 2011).Data analysis involved breaking up the data into manageable themes, patterns, trends and relationships (Mouton, 2005:108).Themes that emerged from the data were identified using the technique of content analysis.This article examined the critical factors that inhibit infrastructure development in the polity and analyzed the constraints to the effective implementation of PPP which include difficulty in securing credit, delay in receiving payments, and absence of effective maintenance culture, corruption and dearth of visionary leaders.It then proffers suggestions towards minimizing these challenges.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.718
Threshold uncertainty score0.738

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.9890.995

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 head0.015
GPT teacher head0.196
Teacher spread0.181 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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
Published2000
Admission routes1
Has abstractyes

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