The Effect of Village Income on Village Expenditure: A Case Study of Belitung Regency
Why this work is in the frame
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Bibliographic record
Abstract
The development progress of rural areas generally lags behind that of urban areas.To bridge this gap, the support of various factors is essential, with financing being one of the key elements.In rural regions, several financing sources can be utilized to bolster development efforts, such as Village Original Income (PAD), Transfer Funds, and other financial resources.Belitung Regency, as an archipelagic area within the Bangka Belitung Islands Province, undoubtedly requires financial support to foster developmental progress within its jurisdiction, given the pivotal role of financing in development.To comprehend the impact of financing, particularly on village expenditures in rural locales, it is imperative to undertake research.Hence, this study is designed to examine and analyze the influence of village income on village expenditures in Belitung Regency.The Geographically Weighted Regression (GWR) is one analytical model applicable for assessing the impact of village income on village expenditure.Data for this study is amassed through observation, with some obtained from specific agencies.Utilizing the GWR analytical model will elucidate the varying influences of village income on village expenditure across individual villages, since the GWR method is an advanced form of simple regression analysis that incorporates spatial elements to yield more granular, regionspecific outcomes.The findings from the GWR analysis indicate that village funds and allocations have a positive effect on village expenditures in certain areas, signifying that they can increase spending.However, in other regions, these same financial instruments display a negative impact due to poor planning.Additionally, variables such as profit sharing, bank interest, aid grants, and general village original income positively influence village spending, suggesting that an increase in these variables can bolster spending in Belitung Regency.It is recommended that stakeholders engage in meticulous financial planning to maximize the potential of village funds.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it