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Record W2331611935

Bringing Clean Water to Rural Communities in Developing Countries: A Well for the Community in Agrippa Todzi, Togo

2011· article· en· W2331611935 on OpenAlexvenueno aff
Laurent Ahiablame, Jacob Ohlemiller, Emily Stein, Samuel Noel, Bernard A. Engel

Bibliographic record

VenueJournal of rural and community development · 2011
Typearticle
Languageen
FieldNursing
TopicChild Nutrition and Water Access
Canadian institutionsnot available
Fundersnot available
KeywordsSanitationLatrinePer capitaWater supplyClean waterRural communityGeographyImproved sanitationSocioeconomicsPit latrineWater resource managementEnvironmental protectionEconomic growthBusinessEnvironmental scienceEnvironmental engineeringSociologyEngineeringEconomicsPopulation
DOInot available

Abstract

fetched live from OpenAlex

This paper presents a summary of a student funded project for the construction of a community water well in Agrippa Todzi, a small farming village in Togo. A survey was conducted to quantify daily water usage and investigate access to improved latrines in the village. Sixty eight percent of the survey participants reported having access to a clean water source. Based on estimates, the daily average water consumption per capita was near 17 L. Only 13% of respondents reported having access to an improved latrine. The completion of the project is a valuable contribution to the local water supply. The project provided a unique opportunity for international experience and service learning to the students involved. Keywords: Drinking water, well, sanitation, Togo, rural community

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.506
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.000

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 head0.045
GPT teacher head0.267
Teacher spread0.222 · 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 teacher head, not a consensus.

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
Published2011
Admission routes1
Has abstractyes

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