KEPASTIAN HUKUM DAN PENGAKUAN PARA PIHAK HASIL PENGUKUHAN KAWASAN HUTAN NEGARA DI PROVINSI RIAU
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
Legal certainty and legitimacy of forest area can be gained through the gazettment process of forest area that starts from the designation, boundary demarcation, mapping, and ends up with the establishment. In Riau Province, these processes are stagnant, and, therefore, the legal certainty and legitimacy is difficult to achieve. What is really happenned is something that needs to be answered in this study. By using the analysis of strategy typology and descriptive qualitative analysis, this study has found that the gazettment issues of forest area consisted of three aspects, namely: designation, boundary demarcation and establishment. Social conflict has been accumulated along the gazettment process, so that the legal certainty did not lead to legitimacy. This problem happened due to: claims avoidance (PTB) to avoid failure in boundaries determination; policy narrative of the boundaries are not informed to community; inconsistency between the objective of boundary demarcation with the implementation; domination of all informed knowledge and information (BPKH); stages of gazettment were done just to fulfill administrative procedure; BPKH tasks issues; and state forest area regarded as the common pool resources (CPRs). This result proves that the improvement of government, policy in gazettment of forest area is seriously required.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 it