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Record W4404068469 · doi:10.3390/su16219583

Socio-Economic Profile and Vulnerabilities Assessment in Small-Scale Fisheries of Lower Gangetic Flood Plain Wetland: An Initiative Towards Achieving Wetland Ecosystem Sustainability and Community Well-Being

2024· article· en· W4404068469 on OpenAlexaff
Shreya Bhattacharya, Basanta Kumar Das, Aparna Roy, Prateep Kumar Nayak, Avishek Saha, Pranaya Kumar Parida, Lianthuamluaia Lianthuamluaia, Kausik Mondal, Sangeeta Chakraborty

Bibliographic record

VenueSustainability · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgricultural Systems and Practices
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsWetlandSustainabilityEcosystemFlood mythEnvironmental resource managementScale (ratio)Environmental scienceFisheryEnvironmental planningGeographyEcology

Abstract

fetched live from OpenAlex

ICAR-CIFRI has been continuously working to develop wetland fisheries in a transdisciplinary knowledge-to-action mode to upscale the livelihood of vulnerable small-scale fishermen communities. The integrated development approach was initiated in different lower Gangetic floodplain wetlands of North 24 Parganas, West Bengal, India, to increase the fish production and socio-economic development of small-scale fishermen communities of the wetlands. Duma is one of the most extensive horseshoe-shaped wetlands in Asia. To augment the fish production from this wetland, the pen culture system was adopted by the fishers under the supervision of ICAR-CIFRI in 2021. Within a year, they received 15 tons of commercial fish, valued at around 30 lakhs apart from the small indigenous fish. It has recently been advised that auto-stocked, high-value minor carp in the wetland be adopted to improve income and conserve small indigenous species. In this article, SDG 14 (Life below water) addresses sustainable ecosystem management and livelihood enhancement for the wellbeing of the local people (SDG 3). Nutritional security of the local people is maintained through the small indigenous fish species which is crucial for addressing ‘No hunger’ as per SDG-2. The research also proves that women can play a crucial role in small-scale fisheries and they can economically stand alone, which is the main aim of SDG-5 (gender equality). However, significant issues such as lack of jurisdictional coordination, ecological changes, inequitable distribution of benefits, and income reduction persist in wetland management. The need for urgent reformation of policy and resource management systems is crucial to boost the economic efficiency of the SSF in the wetland. Training for more knowledge on fishing and fish farming, acquiring alternative livelihood and education on financial management should be brought to the fishermen’s communities. These could develop a resilient community that is more equipped to respond to future crises.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.029
Threshold uncertainty score0.057

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.015
GPT teacher head0.261
Teacher spread0.246 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations7
Published2024
Admission routes1
Has abstractyes

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