Shifts of trade in Javan ferret badgers Melogale orientalis from wildlife markets to online platforms: implications for conservation policy, human health and monitoring
Bibliographic record
Abstract
Wildlife trade is increasingly impeding the conservation of imperilled wildlife and is a potential threat to human health. Ferret badgers are extensively traded in China, although the trends, drivers and health implications of ferret badger trade in other parts of Asia remain poorly known. Here, we focus on the pet trade of a little known endemic small carnivore species, Javan ferret badger Melogale orientalis in Indonesia, over a 10 yr period (2011-2020). The Javan ferret badger is listed as Least Concern on the IUCN Red List of Threatened Species with an unknown population trend. We aimed to gain insight into the magnitude of this trade, its purposes, price trends, distribution records, health risks and shifts to online platforms. We documented 44 ferret badgers in 11 wildlife markets in Java and Bali and 100 ferret badgers for sale on online platforms. We observed a shift in trade from traditional animal markets only, to trade in these markets as well as online. Asking prices, corrected for inflation, declined significantly from ~USD 37 in 2012 to ~USD 22 in 2020, and were related to the purchasing power in cities where trade occurred. Widespread sale of the species highlights that enforcement continues to be overly passive as any trade in the species is illegal. We recommend that the Javan ferret badger be afforded full national protection and prioritised in monitoring efforts to establish its true conservation status. Additionally, concerted efforts are needed to determine if online trade poses a risk to conservation and human health.
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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 | 0.001 |
| 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 | 0.000 |
| 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".