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Record W3109809880 · doi:10.5296/jpag.v10i4.17956

Transport Administration in Nigeria and Britain: Prospects, Issues and Recommendations

2020· article· en· W3109809880 on OpenAlexaff
Adeniyi Olufemi Oluwakoya, Stephen Olufemi Obasa

Bibliographic record

VenueJournal of Public Administration and Governance · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicAfrican Education and Politics
Canadian institutionsTransport Canada
Fundersnot available
KeywordsAdministration (probate law)DisequilibriumGovernment (linguistics)Intervention (counseling)Corporate governancePosition (finance)Transport policyBusinessEconomic interventionismEconomic growthPublic administrationEconomicsPolitical scienceFinancePoliticsPublic transportMedicine

Abstract

fetched live from OpenAlex

Transport, due to its ubiquitous nature, takes a key position in contemporary discourse as a critical sector that impacts governance, economic and social wellbeing of the national development. The unprecedented transportation challenges, particularly in the sub-Saharan states, have a significant implication on the performance of their economies. These challenges, more often than not, are generated by disequilibrium in the policy of the government as it affects transport administration. The study takes a comparative evaluation of the extent, dimension and manner of transport administration in Nigeria and Britain. The approach involves a documentary search of the policy intervention of transport administration in both countries. The study identifies the issues and challenges of transport administration lapses, especially on the part of Nigeria and relevant recommendation to improve transport administration for national economic development.

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)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.037
Threshold uncertainty score0.073

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0030.002
Scholarly communication0.0070.007
Open science0.0010.002
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0090.001

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 head0.038
GPT teacher head0.342
Teacher spread0.304 · 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 designNot applicable
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
Published2020
Admission routes1
Has abstractyes

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