Prinsip Pencemar Membayar untuk Mendorong Akses Kompensasi di Kebijakan ASEAN dalam Kasus Polusi Kabut Asap Lintas Batas
Bibliographic record
Abstract
Kebakaran hutan telah terjadi semenjak 1980-an dan tiga tahun lalu masih terjadi dengan dampak masif di Asia Tenggara. ASEAN selaku organisasi regional menjadi pelopor untuk membuat perjanjian asap lintas batas yang mengatur pencegahan asap lintas batas. Namun, tidak ada alur pemenuhan kompensasi untuk korban dalam perjanjian tersebut. Artikel ini mengargumentasikan bahwa Prinsip pencemar membayar (polluter-pays principle/PPP) dapat digunakan sebagai salah satu upaya dalam untuk memberikan akses kompensasi dari pencemar untuk korban. Terutama, dalam perkembangannya PPP menjadi prinseip yang memiliki banyak alternatif dalam alur pemberian kompensasi. Artikel ini merupakan tulisan yuridis-normatif dengan bentuk deskriptif.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.008 | 0.006 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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; both teacher heads agree on what is shown here.
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".