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Record W2765411183 · doi:10.18352/ijc.742

Social wellbeing and commons management failure in a small-scale bag net fishery in Gujarat, India

2017· article· en· W2765411183 on OpenAlex
Rajib Biswal, Derek Johnson, Fikret Berkes

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

VenueInternational Journal of the Commons · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicCoral and Marine Ecosystems Studies
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsFishingCommonsFisheries managementBlameFisheryCorporate governanceScale (ratio)PessimismBusinessPolitical scienceGeographyLawFinance

Abstract

fetched live from OpenAlex

Social scientists have long recognized that fishing is perceived by many coastal communities as a way of life that does much more than just provide material benefits. A corollary to this is that fishers are often reluctant to quit fishing. Marine fisheries are complex and dynamic, and are often subject to classic commons dilemmas. These dilemmas have become much more acute in recent decades as pressures on the world’s small-scale fisheries have mounted. We argue that a holistic social wellbeing approach provides a valuable perspective from which to view changing fisher perceptions of bag net fishing in the face of commons management failure in Gir Somnath District in Gujarat State, India. Fishers’ perceptions of fishing as a desirable occupation are not shaped by only their job satisfaction. Ineffective governance and largely failed institutions are the factors that fishers blame for the recent crisis in their fishery. Many fishers are pessimistic about the future of fishing and do not want their children to be a part of this occupation that was vibrant until recently.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.057
Threshold uncertainty score0.960

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 science0.0010.001
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 head0.014
GPT teacher head0.245
Teacher spread0.232 · 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