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Record W4411300727 · doi:10.1080/13600818.2025.2517579

Fishing rights to water estates and food security in coastal Bangladesh

2025· article· en· W4411300727 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

VenueOxford Development Studies · 2025
Typearticle
Languageen
FieldNursing
TopicChild Nutrition and Water Access
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsFishingFood securityWater securityNatural resource economicsBusinessFisheryWater resource managementAgricultural economicsEconomicsGeographyEnvironmental scienceWater resourcesAgricultureEcology

Abstract

fetched live from OpenAlex

We examine how access rights to water estates affect food security outcomes of 211 rural households in coastal Bangladesh under the Jalmahal Management Policy. Using distance to water estates as an instrument, we employ IV-2SLS and instrumental variable quantile treatment effect methods to address endogeneity and examine distributional effects. Results indicate that fishing rights significantly improve macro and micronutrient consumption for the average household. However, these benefits primarily accrue to households already meeting or close to meeting their nutritional requirements. We find that socioeconomic factors – higher income, assets, and education – enhance households’ ability to translate access rights into improved food security. Our findings suggest that while rights-based approaches can improve average nutritional outcomes, complementary support mechanisms are needed to benefit the most vulnerable households.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.540
Threshold uncertainty score0.502

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 head0.017
GPT teacher head0.278
Teacher spread0.261 · 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