Local Government and Poverty Eradication in Rural Nigeria LE GOUVERNEMENT LOCAL ET L'ÉRADICATION DE LA PAUVRETÉ RURALE AU NIGERIA
Bibliographic record
Abstract
Poverty is a universal phenomenon that cut across both developed and underdeveloped countries. In Nigeria poverty is deep, widespread and multidimensional, and Nigerians are all victims of this condition in one way or the other even though the degree differs. However, available statistics reveals that poverty is more pronounced among the rural dwellers that form 70% of the country’s population. Efforts by successive government to eradicate poverty especially in the rural areas since independence have not yielded any desirable result in spite of huge amount of resources committed to it. This article focuses on the causes of rural poverty as well as strategies adopted to eradicate it made by successive regimes in Nigeria. It also analysis some of the main weaknesses of the past attempt aimed at eradicating poverty and highlights the potential role that local government can play in poverty eradication efforts. Keywords: Poverty; Causes of Poverty; Local Government; Rural Areas and Poverty Alleviation Programmes Resume: La pauvrete est un phenomene universel dans les pays developpes et sous-developpes. Au Nigeria, la pauvrete est profonde, generalisee et multidimensionnelle, et les Nigerians sont touts les victimes de cette condition dans un sens ou dans l'autre, meme si le degre differe. Cependant, les statistiques disponibles revelent que la pauvrete est plus prononcee chez les habitants des zones rurales qui constituent 70% de la population du pays. Les efforts deployes par les gouvernements successifs pour eradiquer la pauvrete, en particulier dans les zones rurales depuis l'independance, n'ont pas donne de resultat souhaitable, en depit des enormes ressources engagees. Cet article se concentre sur les causes de la pauvrete rurale ainsi que les strategies adoptees par les regimes successifs au Nigeria pour l'eradiquer. Il analyse egalement certaines des faiblesses principales de la derniere tentative visant a eradiquer la pauvrete et met en evidence le role potentiel que les gouvernements locaux peuvent jouer dans les efforts d'eradication de la pauvrete.Mots-cles: pauvrete; causes de la pauvrete; gouvernements locaux; zones rurales et programmes de lutte contre la pauvrete
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".