PENDAPATAN ASLI DAERAH SEKTOR KEHUTANAN PADA ERAOTONOMI DAERAH DI KABUPATEN MUNA
Bibliographic record
Abstract
This research was aimed to know contribution of forestry sector to Local Government Revenue at district of Muna in regional autonomy era. The research result is expected to contribute in evaluating and compiling Regional Budget and Expenditure Plan. The result is also intended as an evaluation of forest product restribution policy. Data were collected with purpossive sampling using observation technique/survey, interview and discussion with related stakeholders. The data was then processed, tabulated, clasified base on with research aim, and analysed descriptively. The results show that the contribution of forestry sector to Local Government Revenue to Muna district during 2000-2004 in average was 36.77% of Local Government Revenue in total. Key words: contribution, forestry sector, Local Government Revenue, regional autonomy
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.004 |
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".