Trade in Southeast Asian Box Turtles from Indonesia: Legality, Livelihoods, Sustainability and Overexploitation
Bibliographic record
Abstract
Southeast Asian box turtles Cuora amboinensis are distributed in mainland Southeast Asia and throughout most of insular Southeast Asia and are often found in habitats shared with humans. In the 2000s evidence emerged of an enormous illegal export of Southeast Asian box turtles from Indonesia estimated at a hundred times larger than the legal exports. Using publicly available data we show that one or two exporters in Sampit in the province of Central Kalimantan, one of nine provinces where harvest of Southeast Asian box turtles is authorised, continue to trade above permitted levels. Harvest quotas for Central Kalimantan are set at 1000 turtles a year, and this is divided between five approved traders, two of whom are based in Sampit. A single visit to one of these two traders in April 2019 documented the presence of 549 Southeast Asian box turtles. Based on documented data from middlemen we estimate that the number of Southeast Asian box turtles that are harvested in Central Kalimantan to supply the traders in Sampit amounts to 19,000–45,000 individuals a year. If the Sampit traders stay within their quotas potential profits are less than USD 400 year−1, compared to up to USD 40,000 year−1 when trading the higher numbers. It is not known how many box turtles are traded by the other three exporters in the province. With the annual harvest quota for all of Indonesia set at less than 15,000 the massive illegal trade as documented in the 1990s and 2000s continues unabated. Assessments of the harvest and trade in Southeast Asian box turtles must consider both the sustainability and legality of this trade.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".