Deficit, Decay and Deprioritization of Transport Infrastructure in Nigeria: Policy Options for Sustainability
Bibliographic record
Abstract
<p>It is common knowledge that Nigeria’s road infrastructure, and indeed the general infrastructure of sub-Saharan Africa, is in a most despicable condition. This paper formalises this observation by providing current data to support the hypothesis. By deploying descriptive and theoretical methodological approaches, it demonstrates that road infrastructure is not only deteriorating but also suffers from a twin evil of deficit and deprioritisation in the public sector’s preferential scale–a state of indifference of sorts. Long and short term policy choices have to be made to urgently address the issue. In the short term, infrastructure concessions, public private partnerships (PPP), pension funds, sovereign wealth fund, savings from reduction in fuel subsidies, leveraging on the Africa Growth and Opportunity Act (AGOA) mechanism–are part of the portfolio of choices that government can readily choose from. In the long term however, the paper recommends increase in the statutory allocation to the states and local governments which would ensure that component units of the federation control more resources to deploy and develop infrastructure in their immediate domain.</p>
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".