The Role of Zakat in North Sumatra Province in Allevating the Poor
Bibliographic record
Abstract
Zakat distribution by BAZNAS is divided into utilization and distribution. The use of zakat for productive business is carried out when the basic needs of mustahik have been met. The Covid-19 pandemic caused the North Sumatra economy to experience growth of -2.37 percent in the 2nd quarter and -2.60 percent in the 3rd quarter. The sizeable economic inequality in North Sumatra is a challenge for BAZNAS in reducing the income gap between communities. The business income of productive zakat recipients before and after the pandemic is indicated to have differences. Asnaf in Medan City is quite representative portraits to see whether there are differences in income or otherwise. This study uses descriptive analysis and the Wilcoxon test model to examine the impact of productive assistance provided by BAZNAS on micro and small businesses. Researchers used net income before and after receiving productive assistance from North Sumatra BAZNAS. It is revealed stated that the provision of Zakat to asnaf could increase the income of asnaf, however during pandemic, the giving of zakat is decreasing as well as the income of asnaf also decreasing in North Sumatra Province
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How this classification was reachedexpand
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 | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".