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Record W44905361

Internalising a Crisis? Household Level Response to Water Scarcity in the City of Harare, Zimbabwe

2012· article· en· W44905361 on OpenAlexaboutno aff
Emmanuel Manzungu, Rennie Chioreso

Bibliographic record

VenueJournal of Social Development in Africa · 2012
Typearticle
Languageen
FieldEngineering
TopicWater resources management and optimization
Canadian institutionsnot available
Fundersnot available
KeywordsWater scarcitySocioeconomic statusSocioeconomicsEconomic growthQuarter (Canadian coin)Corporate governanceDevelopment economicsGeographyPolitical scienceBusinessSociologyEconomicsAgriculturePopulationDemography
DOInot available

Abstract

fetched live from OpenAlex

In the last quarter of 2008, Zimbabwe grabbed international news headlines because of a cholera outbreak that was said to be the worst in Africa in 15 years. The outbreak was attributed to inadequate and poor quality of domestic water at household level. This paper examines how households from different socioeconomic backgrounds responded to the water crisis between 2008 and 2011. The paper’s analysis of the extent of the water shortage in Harare and the resultant household responses is based on information gleaned from household level surveys that were undertaken in 2008 and 2010/2011. This was complemented by interviews held with key informants and focus group discussions with residents of the city of Harare. The study established that, in the absence of clear prospects for changing water governance arrangements in the city, households had resorted to ‘internalising the crisis’. The ability to adequately respond depended on the socioeconomic status of the household, with poorer households showing less ability to cope. The paper argues that internalisation of the crisis by households cannot be said to represent a sustainable and long-term solution to the water crisis, and that the perseverance on the part of the households to engage with the water situation. It however, concludes that, this perseverance can be used as a base for forging meaningful partnership between the city and its residents in the quest for finding a lasting solution to the water crisis.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.804
Threshold uncertainty score0.285

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.065
GPT teacher head0.238
Teacher spread0.172 · 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.

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

Citations17
Published2012
Admission routes1
Has abstractyes

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