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Adaptive Capacity of Fishermen in Facing Tidal Floods with Vulnerability to Viability (V2V) Approach

2024· article· en· W4396700583 on OpenAlexaff
Nugroho SBM, Prateep Kumar Nayak, Indah Susilowati, Aini Nur Furoida, Ika Suciati, Siti Khasanah, Tedy Pratama Putra

Bibliographic record

VenueECSOFIM (Economic and Social of Fisheries and Marine)/ECSOFiM (Economic and Social of Fisheries and Marine) · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicFood Security and Socioeconomic Dynamics
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsAdaptive capacitySnowball samplingFlooding (psychology)Vulnerability (computing)FishingEnvironmental resource managementPsychological resilienceGovernment (linguistics)Capacity buildingGeographyData collectionNatural resourceEnvironmental planningBusinessFisheryEcologyClimate changeSociologyEnvironmental scienceEconomicsEconomic growthPsychologyComputer scienceSocial science

Abstract

fetched live from OpenAlex

Tambakrejo’s small-scale fishing households have low socio-economic capabilities and must face the problem of tidal flooding. Therefore, this research has the following objectives: 1) To identify the vulnerability of fishing households in Tambakrejo Fishermen Village to social-ecological changes due to tidal flooding. 2) To investigate the adaptive responses of fishermen households in facing socio-ecological changes due to tidal flooding. This research uses primary data by using semi-structured interviews. The number of respondents in the study was 60, determined by the snowball sampling technique. The data were analyzed using descriptive statistical methods. The results of the research show that the community is vulnerable to both natural and institutional aspects. Adaptive responses shape community resilience through increased collaboration capacity and community learning capacity. This research contributes to the government's ability to distribute assistance to the community, especially fishing households affected by tidal flooding.

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)0.001
metaresearch head score (Gemma)0.003
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 score0.004
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.002
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.199
Teacher spread0.183 · 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

Citations2
Published2024
Admission routes1
Has abstractyes

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