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Record W4406361699 · doi:10.37149/jimdp.v9i4.1223

Analisis Adaptasi dan Biaya Adaptasi Masyarakat Desa Sriwulan terhadap Banjir Rob

2024· article· en· W4406361699 on OpenAlexaff
Nabilah Kamal

Bibliographic record

VenueJurnal Ilmiah Membangun Desa dan Pertanian · 2024
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic Growth and Fiscal Policies
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsForestryGeography

Abstract

fetched live from OpenAlex

As a coastal area, Sriwulan Village in Sayung District, Demak Regency, often faces increasingly severe tidal flooding problems. To survive, the people in this village have developed various adaptation methods in their social, economic, and physical lives. This study aimed to describe in detail the adaptations implemented by the residents of Sriwulan Village and measure the costs they have to spend to deal with the impact of tidal flooding. This research was conducted from January to August 2022. This research was conducted from January to August 2022 with a rationalistic deductive qualitative approach. The research sample consisted of 10 respondents representing the people of Sriwulan Village. The variables studied included the form of adaptation (physical, social, economic) and the amount of adaptation costs calculated using the averting behavior method. The study results showed that the total adaptation costs incurred by all respondents over the past 20 years reached IDR 663,010,000.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.742
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.035
GPT teacher head0.232
Teacher spread0.198 · 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 designNot applicable
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
Published2024
Admission routes1
Has abstractyes

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