Law Enforcement of SMEs Licensing in Empowerment of People's Economy Connected to Regional Autonomy in North Sumatra, Indonesia
Bibliographic record
Abstract
law enforcement on SME licensing aims to encourage the empowerment of the people's economy through improving the quality of licensing services in the regional autonomy government and for better chances in the future in North Sumatra Province. The research method used is normative legal research (juridical normative), juridical sociology, and empirical to find the truth related to the enforcement of SME licensing laws that have been stipulated in the regulations. Result of this study, the process for obtaining SME licensing in North Sumatra has been regulated through the One-Stop Integrated Licensing Service Agency based on the Minister of Home Affairs Regulation followed by Governor, Regent, and Mayor regulations through regional regulations. In the implementation, it will be carried out using technology systems and facilities or still manual. From the actual conditions, licensing services are still problematic so that to achieve the goal of law enforcement in empowering the people's economy or even to improve the economy of the community is not yet optimal, because the implementation of regulations has not been implemented properly and correctly so that the people applying for permits still have difficulty obtaining business licenses. From the results of the delegation of the authority of the regional head to the BPPTSP, it has not been fully implemented, there are still other offices that accept delegations so that permit applicants find it difficult and convoluted and their implementation overlaps in the difficult bureaucracy, finally the timeliness and expenditure of costs are not as expected.
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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 | 0.000 | 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 | 0.001 |
| 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 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".