Traditional Climate and Environment Forecasting Based on Local Knowledge of Urug Societies in Bogor West Java
Bibliographic record
Abstract
The aim of this research to find out about Indigenous of Knowledge Urug Community for forecasting climate and environment dynamic toward community resilience. The research method used is the ethnographic approach or cultural anthropology. Ethnography is sorts of qualitative research that need observation, documentary and interview in local societies. Ethnographic deal with discovers about description about culture including local knowledge, behaviour, cultural, ritual, traditional ceremonies, and language of Urug community. The selection of sample as informant exert purposive sampling technique. The result is probed meticulously through triangulation technique and triangulation sources. The result shows that the Indigenous community have implemented the sort of Traditional and calendar years with animals symbol for forecasting season and climate. The community can adapt season and climate dynamic and create community resilience for environment and climate. Besides that, there is the connection of planting local paddy to attaint community resilience including environmental change, cultural and social resilience.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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 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".