Tindakan Preventif Kepolisian dalam Menanggulangi Penyalahgunaan Minuman Keras (Miras) di Wilayah Hukum Polda Bali
Bibliographic record
Abstract
Alcohol is a stimulant because the elements it contains can rejuvenate the body, but this view is wrong because stimulants are only temporary. People who drink alcohol lack a sense of prevention or inhibition.People who drink alcohol lack a sense of prevention or inhibition. The research used in this research is a type of empirical research, where research is carried out on the real condition of the community or environment, with the aim of finding facts or existing legal problems. Seeing the obstacles faced by the police in implementing the "Alcohol Abuse Law" in the Bali police area, many factors have caused the Bali Police to face many obstacles in implementing the Anti Alcohol Abuse (Miras) Law, including internal and external factors that make Bali. Based on the background of the problems described, it can be concluded that the actions taken by the police to address alcohol abuse in the Bali Police area. Within the jurisdiction of the Polda in Bali, the obstacles faced by the police in enforcing laws regarding alcohol abuse.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 0.001 |
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".