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Record W2524393979 · doi:10.22500/sodality.v4i2.13372

LINGKARAN SETAN KEMISKINAN DALAM MASYARAKAT PEDESAAN, STUDI KASUS PETANI TEMBAKAU DI KAWASAN PEDESAAN PULAU LOMBOK -- The Vicious Circle of Poverty in Rural Society, Case Study of Tobacco Farmers in the Rural Area of Lombok Island

2016· article· en· W2524393979 on OpenAlexaff
Muhammad Nurjihadi, Arya Hadi Dharmawan

Bibliographic record

VenueSodality Jurnal Sosiologi Pedesaan · 2016
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgricultural Development and Management
Canadian institutionsWiLAN (Canada)
Fundersnot available
KeywordsPovertyVirtuous circle and vicious circleSocioeconomicsNonprobability samplingAgricultureEconomic growthAgricultural sciencePolitical scienceEconomicsGeographyPopulationSociologyDemography

Abstract

fetched live from OpenAlex

ABSTRACT Poverty is the cause of hunger, marginalization, neglectand the other social problems. Rural area, which most of its people work in agriculture, generally have more poor people than urban area. Lombok Island in NTB Province as one of the main producers of tobacco in Indonesia is one of the region with higher poor people percentage comparing to national percentage of poor people. This research aimed to know the pattern of vicious circle of poverty in tobacco farmers in Lombok Island. This research used qualitative method with descriptive approach. The number of respondents in this research are a hundred persons which were choosed by random sampling. While the research areas were choosed by purposive method. The research result revealed that the tobacco farmers in rural Lombok experienced the new pattern of vicious circle of poverty. Since the farmers had low level of capital, it encourage the farmers to make a collaboration with Tobacco Company which was create the dependence of farmers to tobacco commodity and Tobacco Company. Dependence on Tobacco Company make bargaining positions of farmerslowin transaction processwhich cause the farmers income become low. Low income lead the tobacco farmers to the ‘debt trap’ and low capital. Keywords: poverty, rural, farmers, tobacco, Lombok ABSTRAK Kemiskinan adalah penyebab dari kelaparan, marginalisasi dan keterlantaran serta fenomena-fenomena negatif sosial lainnya. Kawasan pedesaan yang sebagian besar penduduknya bekerja di sektor pertanian umumnya memberikan sumbangan yang lebih besar dalam hal jumlah penduduk miskin dari pada kawasan perkotaan. Pulau Lombok di NTB sebagai penghasil utama tembakau di Indonesia adalah salah satu daerah dengan prosentase penduduk miskin lebih tinggi dari pada prosentase penduduk miskin nasional. Penelitian ini bermaksud untuk mengetahui pola lingkaran setan kemiskinan pada petani tembakau di Pulau Lombok. Penelitian ini menggunakan metode kualitatif dengan pendekatan diskriptif. Responden berjumlan seratus orang dipilih secara random sampling di wilayah penelitian yang ditentukan secara purposive. Hasil penelitian menunjukkan bahwa petani tembakau di pedesaan Pulau Lombok mengalami lingkaran setan kemiskinan dengan pola baru. Rendahnya tingkat modal petani mendorong petani untuk bermitra dengan perusahaan tembakau, kemitraan ini kemudian menciptakan ketergantungan petani pada komoditas tembakau dan perusahaan mitra, ketergantungan itu membuat posisi tawar petani lemah dalam proses transaksi yang mengakibatkan rendahnya pendapatan petani, pendapatan yang rendah membuat petani terjebak pada debt trap dan tidak mampu mengakumulasi modal, dengan demikian petani kembali memiliki modal yang sangat rendah. Kata kunci: kemiskinan, pedesaan, petani, tembakau, Lombok

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0050.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
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 head0.021
GPT teacher head0.240
Teacher spread0.219 · 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 designQualitative
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".

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Citations1
Published2016
Admission routes1
Has abstractyes

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