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Record W4411353587 · doi:10.18280/ijsdp.200518

The Sustainable Development Status of Farming in Dam Service Area on the Indonesia-Timor Leste Border

2025· article· en· W4411353587 on OpenAlexvenueno aff
Werenfridus Taena, Boanerges Putra Sipayung, Fried Markus Allung Blegur, Anggelina Delviana Klau

Bibliographic record

VenueInternational Journal of Sustainable Development and Planning · 2025
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgricultural Systems and Practices
Canadian institutionsnot available
Fundersnot available
KeywordsTimor lesteAgricultureBusinessSustainable developmentService (business)Environmental planningEnvironmental resource managementEconomic growthGeographyEnvironmental sciencePolitical scienceEconomicsMarketing

Abstract

fetched live from OpenAlex

The research focuses on the objectives of ( 1) to analyze the sustainable development index of farming based on the development dimension in dam service area on the Indonesia-Timor Leste border, (2) to analyze the influence of economic, social and ecological factors on sustainable development farming in dam service area on the Indonesia-Timor Leste border.The research uses a survey method.Primary data were obtained from 300 farmers who were determined randomly.Secondary data were obtained from the Food Crops and Horticulture Department, Central Statistics Agency, BMKG and other agencies.Data analysis using RAP Farm and PLS.The results of the RAP Farm analysis found that the sustainability index of farming in dam service area on the border country was moderate sustainable.Then, the results of the PLS analysis also found that economic factors significantly, influence sustainability, while social and ecological factors do not significantly influence sustainability.Likewise, production and income factors have an impact on sustainability, while equity and reduction of greenhouse gas emissions are not sustainable.Therefore, agriculture policies in dam service area are needed that guarantee linkages between development dimensions so that sustainable economic growth, income distribution and reduced gas emissions can be achieved simultaneously; and to expand the study of impacts across time and across countries.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.390
Threshold uncertainty score0.336

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0000.000
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 head0.021
GPT teacher head0.268
Teacher spread0.247 · 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.

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

Citations0
Published2025
Admission routes1
Has abstractyes

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