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Assessing the Viability of Desalination for Rural Water Supply: A Case Study of Chwaka, Zanzibar

2012· article· en· W1801770845 on OpenAlexvenueno aff
Roy Yu, Daniele Packard

Bibliographic record

VenueCross-cultural communication · 2012
Typearticle
Languageen
FieldNursing
TopicChild Nutrition and Water Access
Canadian institutionsnot available
Fundersnot available
KeywordsDesalinationWater supplyGovernment (linguistics)BusinessInvestment (military)Consumption (sociology)TanzaniaUnit (ring theory)Natural resource economicsWater resource managementScarcityEnvironmental planningEnvironmental engineeringEconomicsEnvironmental sciencePolitical science

Abstract

fetched live from OpenAlex

Zanzibar has been struggling with water scarcity issues over the last few decades due to an increase in consumption on the island and a deterioration of existing supply infrastructure. Poor distribution has affected rural communities most, due to their absence of tourism development, which has gone hand in hand with infrastructure establishment. Foreign aid has begun to address the issue by investing in alternative forms of water supply. In November 2011, a solar and wind powered desalination unit was inaugurated in the village of Chwaka, which, previous studies have shown, suffers from salt contaminated wells. This study sought to assess the viability of this alternative source of water in Chwaka and found that the desalination unit installed is not a viable source of freshwater for the entire village of Chwaka compared to government piped well water. Installed with the best intentions for the people of Chwaka, the presence and purpose of the machine is unknown to most of the village and its production capacity could only hope to supplement drinking water. Relative investment costs of distributing similar volumes of water show that piped water is the cheaper option. The intentions of the project are nonetheless laudable and this type of innovative investment should be encouraged as long as the government is not asked to take the bill. Zanzibar has access to adequate freshwater resources and must look to efficient consumption before turning to alternative forms of water production. Key words : Advantages; Alternative; Chwaka; Desalination; Disadvantages; Drinking; Freshwater; Supply; Tanzania; Viability; Water; Zanzibar

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.088
Threshold uncertainty score0.176

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 studies0.0040.002
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.052
GPT teacher head0.410
Teacher spread0.357 · 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 designObservational
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

Citations1
Published2012
Admission routes1
Has abstractyes

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