Ecological Impacts and Socio-Legal Infrastructure as an Approach to Environmental Management in Ex-Mining Land Reclamation
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Mining, along with plantations, is one of the main economic backbones of the Indonesian provinces of Kalimantan. The main concern of extractive economics is deforestation and environmental damage that threatens natural sustainability. Most of the previous research focused on the issue of environmental sustainability in the industrial context and regional spatial planning. To fill this void, this study originally aims to analyze how local wisdom is useful in managing ex-mining reclamation practices. This research was conducted in Margahayu, Kutai Kertanegara, East Kalimantan Province. The method used in this research is empirical legal research by adopting a data-based approach. The results show that ex-mining reclamation in Margahayu aims to restore the land use according to its function and is beneficial for agriculture and small-scale plantations. The findings underline that the participation of local communities is very useful in restoring the function of the ex-mining land, due to their interest in rehabilitating spatial planning and ecological supports that are useful for their livelihoods. In this context, this finding requires inclusion of local interest-based participation as an important social infrastructure in reforestation and mine land reclamation in Kalimantan.
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.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it