Impact Evaluation of Local Government Regulation on Protection and Empowerment of Micro, Small, and Medium Enterprises in Tulungagung District
Bibliographic record
Abstract
Peraturan Daerah tentang Perlindungan dan Pemberdayaan Usaha Mikro, Kecil, dan Menengah (UMKM) di Tulungagung (Perda 4/2013) diharapkan dapat berkontribusi dalam pemulihan pasca pandemi. Perda 4/2013 bertujuan meningkatkan pertumbuhan ekonomi, menurunkan kemiskinan, dan mengurangi pengangguran melalui perlindungan dan pemberdayaan UMKM. Tujuan ini sesuai dengan kebutuhan pemulihan pasca pandemi. Perda 4/2013 hanya akan efektif dalam pemulihan pasca pandemi, jika sebelumnya perda ini memang terbukti mampu mewujudkan tujuan pembentukannya. Untuk mengetahui pencapaian tujuan tersebut, dilakukan evaluasi dampak kebijakan dengan pendekatan single interrupted time series analysis. Hasil analisis menunjukkan, setelah 8 tahun periode implementasi, Perda 4/2013 tidak berdampak dalam meningkatkan pertumbuhan ekonomi, mengurangi pengangguran, dan menurunkan kemiskinan.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".