Analisis Tingkat Ketimpangan Dan Karakteristik Sosial Ekonomi Penduduk
Bibliographic record
Abstract
Although the poverty rate continues to decline, the trend of inequality in Merauke Regency tends to fluctuate and increase compared to 2007. Whereas the economic growth of Merauke Regency is consistently above 7 percent in 2011 and the contribution of the agricultural sector reaches a quarter in GRDP. In addition to the lack of research on the level of inequality in Merauke Regency, this research was conducted with the aim to find out the level of population inequality according to the World Bank's size and to understand the socio-economic characteristics of each population group. This study uses descriptive analysis to answer more clearly the purpose of this study. As a result, the level of inequality in Merauke Regency in 2017 is classified as moderate. Meanwhile, the low-income population mostly lives in the village, more likely to allocate income to consume food but less calorie, accept raskin butdid not receive a Social Protection Card. An important finding in this study is that the accessibility of low-income populations to social protection programs is still low. So it is necessary to evaluate the implementation of the program to be on target.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.015 | 0.002 |
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".