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Record W2761531911 · doi:10.33997/j.afs.2007.20.4.002

Wild Shrimp Larvae Harvesting in the Coastal Zone of Bangladesh: Socio-economic Perspectives

2007· article· en· W2761531911 on OpenAlex
Abul Kalam Azad, Chung‐Kwei Lin, Kathe R. Jensen

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

VenueAsian Fisheries Science · 2007
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicMicrofinance and Financial Inclusion
Canadian institutionsUniversity of British Columbia
FundersDanish International Development Agency
KeywordsShrimpFisheryLivelihoodShrimp farmingBENGALBusinessGovernment (linguistics)PovertyBayEstuaryGeographyEnvironmental resource managementAquacultureFish <Actinopterygii>EcologyEconomic growthAgricultureBiologyEconomics

Abstract

fetched live from OpenAlex

About 0.42 million people are involved in shrimp post larvae collection along the estuaries and coastline of the Bay of Bengal in Bangladesh. Shrimp fry collection from wild sources has assumed a notorious image for being ecologically destructive. In 2000, the Government of Bangladesh imposed regulation to stop shrimp seed collection to protect the fisheries resources. But thousands of people involved in post larvae collection are defying the ban. There is an apprehension that strict implementation of the banning ordinance may displace the people who depend upon the income from catching the larvae. To get the socioeconomic patterns of fry collection 72-85 collectors were interviewed weekly from three harvesting sites. This paper analyzes the larvae collection and distribution efficiency, livelihood strategy of fry collectors, user options for fisheries management and role of various stakeholders empirically. Results show that poverty, migration, credit systems and lack of coordination of service-providing agencies all have important influence on shrimp fry collection in the coastal zone. With an ever-increasing demand for sustainable use of coastal fisheries resources there is a need for consensus among the stakeholders. We propose alternative employment opportunities for fry collectors, community participation and integrated coastal zone management approach for the development of fisheries resources.

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)0.003
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 score0.521
Threshold uncertainty score0.545

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
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 head0.023
GPT teacher head0.233
Teacher spread0.210 · 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