Wildlife conservation in Myanmar: trade in wild sheep and goats for meat, medicine, and trophies, with links to China, India, and Thailand
Bibliographic record
Abstract
Abstract In Myanmar, the hunting and trade of wildlife are increasingly recognised as a major threat to the persistence of species. We here focus on the trade and conservation of wild sheep and goats (Caprinae; Antilopinae) as these species are indeed hunted and traded for a variety of reasons. Seizure reports from 2000 to 2020 and 20 visits to four wildlife markets between 1998 and 2017 resulted in records of ~ 2,000 body parts, the equivalent of ~ 1,200 wild sheep and goats. When combined with data from previous surveys conducted over the same period, the number of wild sheep and goats recorded in trade increase substantially, i.e. serow (the equivalent of 1,243 animals), goral (213 animals), takin (190 animals), blue sheep (37 animals), and Tibetan antelope (10 animals). With records from 10 out of 15 States, trade appears to be widespread and persistent over time. There was poor concordance between seizure data and trade observations, but data from various surveys are largely in agreement. The most prevalent body parts in trade were horns, followed by plates (the frontal portion of the skull with horns still attached) and heads of freshly killed animals. These parts are offered for sale both for decorations and for their purported medicinal properties. Meat, fat, and rendered oils were observed frequently but because of mixture with other wildlife, it was challenging to confirm species identify or to convert this to number of animal equivalents. Tongues and eyes were offered for sale as medicine. In order to better protect wild sheep and goats in Myanmar, it is imperative that the illegal trade in their parts is more effectively curbed than at present. This is the responsibility of both the Myanmar authorities and, given the high prevalence of trade in border towns, their international partners, including China and Thailand.
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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 | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".