Opini: Perusahaan perkebunan di Indonesia kerap menyalahi aturan hukum. Bagaimana mereka bisa lolos begitu saja?
Bibliographic record
Abstract
Berbagai kajian menunjukkan bahwa perusahaan-perusahaan perkebunan di Indonesia biasa menyalahi aturan hukum hingga mengakibatkan kerusakan besar terhadap lingkungan alam dan membahayakan masyarakat pedalaman. Ini bukanlah cerminan dari tidak adanya hukum yang mengatur jalannya perusahaan. Namun, ini dikarenakan wilayah Indonesia yang diduduki perusahaan perkebunan diatur dengan serangkaian aturan tak tertulis, yang memungkinkan perusahaan untuk mengendalikan pejabat pemerintahan demi kepentingan mereka sendiri. Artikel opini ini ditulis oleh Tania Li, seorang profesor di Universitas Toronto dan peneliti di Pusat Kajian Asia Tenggara, Universitas Kyoto, Jepang, yang telah melakukan banyak penelitian mendalam tentang kehidupan masyarakat pedalaman di Indonesia. Isi artikel ini mencerminkan pandangan penulis sendiri, dan tidak sepenuhnya mewakili pandangan The Gecko Project.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".