Who is killing the tiger <i>Panthera tigris</i> and why?
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
Abstract We investigated the range of people involved in killing tigers Panthera tigris in the Bangladesh Sundarbans, their motives and methods, and their links to the commercial trade. Using snowball sampling we conducted 141 qualitative interviews with local people. We identified five categories (village residents, poachers, shikaris, trappers and pirates), each with different motives, methods and networks. Village residents kill tigers predominantly for safety, whereas others kill in the forest professionally or opportunistically. Poachers kill tigers for money, but for others the motives are more complex. The motives of local hunters are multifaceted, encompassing excitement, profit, and esteem and status arising from providing tiger parts for local medicine. Pirates kill tigers for profit and safety but also as a protection service to the community. The emerging international trade in tiger bones, introduced to the area by non-local Bangladeshi traders, provides opportunities to sell tiger parts in the commercial trade and is a motive for tiger killing across all groups.
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 | 0.000 | 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) | 0.003 | 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