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Record W4400055242 · doi:10.53555/sfs.v10i2.2822

“Beyond the Catch: A Holistic Socioeconomic Evaluation of Aghanashini's Fishing Communities”

2023· article· en· W4400055242 on OpenAlexvenueno aff
Sujal K. Revankar, Jagannath Rathod

Bibliographic record

VenueJournal of Survey in Fisheries Sciences · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicSocial and Economic Development in India
Canadian institutionsnot available
Fundersnot available
KeywordsFishingSocioeconomic statusFisheryGeographySociologyDemographyBiology

Abstract

fetched live from OpenAlex

Aghanashini river is one of the productive riverine systems of coastal Karnataka with reference to fishery resources which drains into Arabian Sea at Tadadi village of Uttara Kannada District. In order to understand educational back ground, fishery related lively hood and economic status of fishing communities residing across the Aghanashini estuary, a questionnaire was prepared to conduct the interview. Based on the interactions with 250 number of fishermen/women we came to know that total number of persons directly involved in collection of bivalves, clams, oysters etc. are around 600. On an average of 250 fishermen/women venture to harvest bivalves on daily basis particularly during low tide.  On an average each person gets the fishes for 16 days in month, each person collects around 14kgs of bivalves in a day. Usually bivalves are sold Rs. 80/kg, October to May is the peak season for the fishery. Around 19 villages are directly involved in fishing which consists of 2398 fishers of which 1548 male and 850 female.  Harikantra community is dominant followed by Gowdas, Ambigas, Gabits, Muslims, Patagar and Naik communities, literacy level of majority of  these are uneducated, some have done matriculation and few passed secondary school. Fishing is the main source of livelihood to majority of the communities in this area.

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 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)0.041
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.063
Threshold uncertainty score0.988

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0410.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.002
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 head0.473
GPT teacher head0.377
Teacher spread0.096 · 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 teacher head, not a consensus.

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

Citations0
Published2023
Admission routes1
Has abstractyes

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