Analysis of Village Residents Receiving Social Assistance Using Linear Regression Method
Why this work is in the frame
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Bibliographic record
Abstract
This study aims to analyze the recipients of social assistance in Banyumas Village using the simple linear regression method. The research examines how household income affects the amount of social assistance received. Data was collected from the Banyumas Village Office, including information on income and the amount of social assistance received by residents. The results show a negative relationship between household income and the amount of assistance received, where higher income leads to smaller assistance. The model also demonstrates good accuracy with an average prediction error (MAPE) of 9.38%. Additionally, an R² value of 0.999972 indicates that the model can explain almost all variations in the data. This study provides valuable insights into the effectiveness of the social assistance program in Banyumas Village and to help improve the program in the future.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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