KAJIAN LINGKUNGAN HIDUP STRATEGIS (KLHS) KAWASAN PERUNTUKAN PARIWISATA DI KABUPATEN BOLAANG MONGONDOW
Bibliographic record
Abstract
This research aims to (1) identify and review strategic priority issues of tourism in Bolaang Mongondow Regency, (2) identify, assess and analyze the impact of RTRW Program of tourism designation in BolaangMongondow Regency on the environment, (3) review efforts to minimize the negative impact that will occur as a result of the implementation of the Program in the area of tourism designation in Bolaang Mongondow District. The research was conducted in Bolaang Mongondow Regency of North Sulawesi Province, from September to October 2017. This research uses purposive sampling method with semi-detailed method based on field observation and Focus Group Discussion (FGD) and key informant interview. Sources of data obtained are: primary data through interviews with key informants and implementation of Focus Group Discussion (FGD). Research results show that 1) The priority strategic issues of the tourism designation area in Bolaang Mongondow District are biodiversity,waste, distruption of security and comfort, Increasing prosperity, Damage of mangrove and coral reefs. (2) The positive impact is the increase of people's welfare with the business opportunities around the tourism area. Negative impacts caused by the implementation of the tourism area programming program in Bolaang Mongondow District are biodiversity, waste, disruption of security and comfort, mangrove damage and coral reefs. (3) Mitigation efforts to minimize negative impacts are making local regulations on the protection of biodiversity around the tourism area, preparing shelters and processing solid and liquid waste from tourism activities, preparing security officers and disaster management team teams around the tourism area, local regulations as a limiting factor of diving and coastal tourism activities to minimize mangrove and coral reef damage.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.017 | 0.002 |
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 source (direct Gemma or distilled Codex), 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".