Interactions between Habitats of Asian Elephants and Socioeconomic Factors in the Teknaf Wildlife Sanctuary (TWS), Bangladesh
Bibliographic record
Abstract
We conducted a one-year study in TWS, Bangladesh, to test socioeconomic-related impacts on the sanctuary caused by three performers marked as forest-endorsed settlers, illegal settlers, and forest-nearest villagers. The performer’s activities were marked as cattle ranching, gardening, paddy cultivation, vegetable growing, betel-leaf growing, and forest resource collection. These factors had a marked impact on the elephant’s use of fodder species, water bodies, feeding trails and resting places, as well as soil types. We revealed that 8% of the intruders were engaged in cattle ranching, 17% in gardening, 32% in paddy cultivation, 25% in vegetable growing, 6% in betel-leaf growing and 12% were forest resource collectors. These numbers were taken out of a recorded total of 26,937 incidences of forest intrusions, including forest endorse settlers (4%), illegal settlers (35%) and nearest forest villagers (61%). The disturbance rate differed statistically significantly across 6 study sites on the east coast and 4 study sites on the west coast in response to socioeconomic-related activities. Almost 2827 hectares of forestland was replaced by paddy cultivation (575 ha), vegetable growing (529 ha), betel-leaf growing (480 ha), gardening (448 ha), and illegal settlement (795 ha). Thus, a total of 11615 hectares of the sanctuary was permanently damaged, posing challenges to elephant survival.
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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 | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".