Struktur Nafkah Rumahtangga Petani Transmigran : Studi Sosio-Ekonomi di Tiga Kampung di Distrik Masni Kabupaten Manokwari
Bibliographic record
Abstract
Among the primary objectives of transmigration program are to increase the economic status of transmigrant farm-households and enhancing rural infrastructures of the local region. To see wether such objective is attainable, a study of transmigrant farm households has been conducted in West Papua. The study attempts: (1) to know whether there is any relation between the socio-cultural/ethnical background of the transmigrant farm-household with the achievement of welfare status, (2) to analyze factors influencing to the income level of transmigrant farm-households, and (3) to understand how the farm households enhance the degree of economic status by building numerous livelihood strategies. The methods as used in the analysis are: (1) income level analysis of the households, (2) gini-ratio analysis, and (3) descriptive analysis. The results of this study are: socio-cultural (ethnical) setting of transmigrant has a substantial influence to the achievement of welfare level. Javanese transmigrant showed a much higher income achievement due to their strong engagement in the non-farm economy, as compared to Papuanese transmigrant farm-households. The non-farm economy provides a strong basis for economic growth at household level. However, the growth of non-farm economy unexpectedly caused an increasing tendency of income disparity among different farm household strata. Since non-farm economy shares a positive contribution for regional economic growth, the study concludes, that the government needs to take seriously this economic sector into account when regional development needs to be well-accomplished in West Papua.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".