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Record W2966244126 · doi:10.1002/wat2.1376

Water resilience lessons from Cape Town's water crisis

2019· article· en· W2966244126 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueWiley Interdisciplinary Reviews Water · 2019
Typearticle
Languageen
FieldEngineering
TopicWater resources management and optimization
Canadian institutionsUniversity of British Columbia
FundersSocial Sciences and Humanities Research Council of CanadaUniversity of British ColumbiaCoordenação de Aperfeiçoamento de Pessoal de Nível Superior
KeywordsCapeResilience (materials science)Corporate governancePsychological resilienceWater supplyPoliticsWater scarcityWater sectorFace (sociological concept)Environmental planningGeographyBusinessPolitical scienceSociologyEnvironmental scienceEnvironmental engineeringArchaeologySocial science

Abstract

fetched live from OpenAlex

Abstract In the aftermath of the acute water crisis, building resilience in the water sector has become a priority for the City of Cape Town. In this piece, I discuss several emerging lessons from Cape Town's experience and their implications for water resilience more broadly. While having avoided “Day Zero,” Cape Town has also demonstrated how unprepared many municipalities might be as they face growing variability and uncertainty in the hydrologic cycle. Second, Cape Town's experience also signals the limits of conventional demand and supply paradigms that focus on high efficiency and overallocation of water resources. Furthermore, Cape Town's deeply unequal waterscape and acutely divisive politics are among the most important factors that shaped not only how the crisis unfolded, but also the ability of governance systems to respond in a timely and adequate manner. This article is categorized under: Engineering Water > Planning Water Human Water > Water Governance

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.332
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0080.016

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 head0.015
GPT teacher head0.253
Teacher spread0.238 · 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