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Record W2062767910 · doi:10.5539/ass.v9n9p94

The Management of Water Points in Niger under the Communalization

2013· article· en· W2062767910 on OpenAlexvenueno aff
Zakari Aboubacar

Bibliographic record

VenueAsian Social Science · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicWater Governance and Infrastructure
Canadian institutionsnot available
Fundersnot available
KeywordsCommissionOrder (exchange)Water supplyRural areaGovernment (linguistics)BusinessProcess (computing)Local governmentEnvironmental planningPolitical sciencePublic administrationEnvironmental scienceComputer scienceEnvironmental engineeringFinance

Abstract

fetched live from OpenAlex

This paper seeks to analyze the management of water points in Niger according to the communalization process. It explains how the new reform of management in the supply of water, as a government policy, in the local areas raises new issues in Sahel and Niger countries. It looks into the issue of water supply which is at the heart of public policy to the countryside. It analyzes not only the importance of water points in Niger but also some sources of concern in the use according to the different logics involved. The paper further relates the role of media in social change according to the using of water in order to protect climate change. The paper concludes that, if, the aim for central and local authorities is to achieve local development, the confrontation between these two approaches must contribute to achieve the desired effect. The paper recommends that in order to solve this social problem, the mayors and central authorities must take into consideration the reaction of the different actors and should install in all the country the Land Commission under the Rural Safety Program.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.004
Scholarly communication0.0030.001
Open science0.0000.003
Research integrity0.0010.001
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 head0.010
GPT teacher head0.268
Teacher spread0.258 · 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 designQualitative
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
Published2013
Admission routes1
Has abstractyes

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