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Record W3132538454 · doi:10.51594/ijmer.v3i1.200

DETERMINANTS OF THE PERFORMANCE OF DEVELOPMENT PROJECTS IN DEVELOPING COUNTRIES

2021· article· en· W3132538454 on OpenAlexaff
Mahamadi Nanéma, Théophile Bindeouè Nassè, Prof . Alidou Ouédraogo

Bibliographic record

VenueInternational Journal of Management & Entrepreneurship Research · 2021
Typearticle
Languageen
FieldDecision Sciences
TopicConstruction Project Management and Performance
Canadian institutionsUniversité de Moncton
Fundersnot available
KeywordsContext (archaeology)Project managementProcess managementDeveloping countrySample (material)BusinessKnowledge managementManagement scienceComputer scienceEngineeringEconomic growthEconomicsSystems engineeringGeography

Abstract

fetched live from OpenAlex

This article aims to analyze the determinants of the performance of development projects in developing countries in general and in particular in the Burkinabé context. This involves identifying the internal and external factors that explain the performance of development projects in the Burkinabé context. The methodology used is essentially based on the hypothetico-deductive approach which led to the definition of a sample of 44 respondents on the quantitative aspect of the study. The results of the study show that two explanatory variables positively and significantly influence the performance of development projects in Burkina Faso. This concerns in particular the technical organization of projects and the environment or the project intervention area. Notwithstanding these results, recommendations are formulated for more efficiency in the implementation of development projects. Keywords: Performance, Project Management, World Bank, Project Management.

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)0.003
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.178
GPT teacher head0.439
Teacher spread0.260 · 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 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

Citations2
Published2021
Admission routes1
Has abstractyes

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Same venueInternational Journal of Management & Entrepreneurship ResearchSame topicConstruction Project Management and PerformanceFrench-language works237,207