Bibliographic record
Abstract
Unsustainable commercial exploitation poses a serious threat to many of Vietnam’s native bird species. Here we report on a survey of the country’s online bird trade, conducted across four major online platforms. Between 9 March and 3 April 2020, a total of 434 posts were recorded, accounting for 834 individuals of at least 50 species, ten of which have not been recorded in Vietnamese trade before. Ninety-two percent of the recorded species were native to Vietnam and 18% (n=9) of the species, accounting for 15% (n=115) of the recorded individuals, are protected under Vietnamese law. Recorded prices ranged between VND16,667 (~US$0.7) and VND7 million (~US$303), depending on the species and on a bird’s specific singing qualities. The highest trade numbers were found on Chợ Tốt (186 posts, 335 birds), followed by Facebook (161 posts, 325 birds), Chợ Vinh (82 posts, 169 birds) and Chim Cảnh Đất Việt (5 posts, 5 birds). The scale of the observed trade appears to confirm a partial shift towards online platforms in Vietnam’s bird trade, or at least an increase in the use of online platforms to trade wild birds. In anticipation of a further development of this trend, we urge the Government of Vietnam to improve regulations and to take greater enforcement action against illegal online trading practices.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.009 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.015 | 0.002 |
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 source (direct Gemma or distilled Codex), 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".