PERTANGGUNGJAWABAN PIDANA PELANGGARAN HAK CIPTA LAGU DAN MUSIK TERHADAP SUBJEK HUKUM TINDAK PIDANA KORPORASI
Bibliographic record
Abstract
Flows of globalization are increasing rapidly and developments of information technology are increasingly stimulating the acceleration of economic dynamics. It takes personal co-operation to create a group collaboration for economic gain. The group is a group of businesses that do not have legal entities, as well businesses that already have incorporated entities called corporations. Combining personal persons into a corporation will increase the strength of the existence of a corporation as a legal subject in the economic realm. A Subject of law (tumjuris subject) is anything that can be a supporter of rights and obligations. There is two subject of laws. the first subject is human (natuurlijke person) and the second is legal entities (rechts person). Corporate position as an economic power outside the state. It creating corporations tend to take control or monopolize all economic system without control from the government. These conditions generate corporations' activities can abuse the public interest that known as corporate crime. Corporate crime is committed to benefiting the company's business, this type of crime is part of white collar crime. This crime also pan of violation of economic rights of creator and owner rights related to Copyrights in the field of songs and/or music. Ideally, the existence of corporations in the field of economy is aimed to increase the economic growth of a country, then, a country can improve people's welfare. However, there are some corporations that violate the principle by committing a crime.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.054 | 0.009 |
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".