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Record W2463589781 · doi:10.1080/07900627.2016.1202099

Managing water-related risks in the West Bengal Sundarbans: policy alternatives and institutions

2016· article· en· W2463589781 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.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueInternational Journal of Water Resources Development · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicFlood Risk Assessment and Management
Canadian institutionsnot available
FundersDepartment for International Development, UK GovernmentSimon Fraser UniversityAustralian Agency for International DevelopmentWorld Bank Group
KeywordsFlooding (psychology)Vulnerability (computing)West bengalEnvironmental planningNatural disasterClimate changeBusinessWater resource managementLeveeWetlandNatural resource economicsGeographyEnvironmental resource managementEnvironmental scienceSocioeconomicsEconomicsGeologyOceanography

Abstract

fetched live from OpenAlex

Persistent pressures from water-related threats – sea-level rise, soil and water salinization, and flooding due to embankment overtopping and failure – have made the West Bengal Sundarbans a challenging place to live, and effects of global climate change will only worsen conditions. Four alternative policy directions are examined: business as usual; intensive rural development; short-term out-migration of residents; and embankment realignment and facilitation of voluntary, permanent out-migration. The last of these is the recommended approach. Study findings have informed ongoing deliberations to build consensus on future policy directions for reducing the region’s vulnerability to natural disasters.

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)0.001
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 score0.477
Threshold uncertainty score0.412

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0010.000
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 head0.024
GPT teacher head0.291
Teacher spread0.266 · 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