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Record W2341881595 · doi:10.1177/1070496515625091

Sustainable Flows

2016· article· en· W2341881595 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.

Bibliographic record

VenueThe Journal of Environment & Development · 2016
Typearticle
Languageen
FieldEngineering
TopicWater resources management and optimization
Canadian institutionsYork UniversityUniversity of Toronto
Fundersnot available
KeywordsWork (physics)Flexibility (engineering)Government (linguistics)Scale (ratio)Climate changeBusinessSoutheast asiaEnvironmental planningKey (lock)Environmental resource managementComputer scienceEconomicsGeographyEcologyEngineeringSociology

Abstract

fetched live from OpenAlex

There is widespread recognition that cities in the Global South need to transition toward sustainable water practices. This is particularly true of places experiencing growth and impacts from climate change concomitantly, as are Bangkok and Hanoi. We evaluate case studies in each of these two Southeast Asian cities to explore possible sustainable water management practices that their urban communities, and others experiencing similar issues, could adopt in the near term. Our analysis of these case studies supports four key conclusions: Simple expansion of rigid infrastructure does not necessarily meet local needs for water, communities can themselves provide insights and creative models, governments at any scale can be flexible and such flexibility can achieve appropriate solutions, and small-scale experimentation can and does work and can be successfully scaled up with government encouragement and support.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.937
Threshold uncertainty score0.284

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.004
GPT teacher head0.144
Teacher spread0.140 · 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