An Ethical Perspective of Animal Rights Protection in Indonesia
Bibliographic record
Abstract
An environment is a meeting place for every living creature. They have an important role in respecting each other's rights in the environment. One of the living creatures in the environment is fauna. As part of the environment, fauna also has rights that must be fulfilled in the environment to avoid fauna becoming rare and even extinct. However, nowadays, many types of fauna are becoming rare and even on the verge of extinction. Of course, this is also caused by the pace of human development with all its interests in the environment. Often, human interest underestimates the existence of rare and even endangered fauna. To overcome this, humans must have an awareness of the rights of fauna. One of the steps that can be taken is to incorporate moral awareness into the legal domain. Therefore, to build moral awareness in the conservation of endangered species, it is hoped that there will be regulations that can accommodate all of them. Simply, to build moral awareness of animal rights, a law that specifically guarantees animal rights is needed, if necessary, to guarantee its constitutionality in the state constitution.
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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 | 0.005 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.006 | 0.020 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.003 | 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".