Indonesia's sustainable development goals in relation to curbing and monitoring the illegal wildlife trade
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 Indonesia has committed to implement the sustainable development goals (SDG) by 2030 including the ending trafficking of protected species and addressing the illegal wildlife demand and supply. As such, there is a need for long‐term data on wild animal trade and its contribution to the wider economy. We initiated a long‐term monitoring programme of live civet trade in wildlife markets (120 surveys, 2010–2023). Civets are traded to be kept as exotic pets and to produce civet coffee and are a proxy for other high‐profile wildlife. We recorded 2289 civets of six species, including ones with strict regulations in place. Despite the trade being illegal, and contra to Indonesia's commitments as part of the SDG to curb this trade, it remained remarkably stable over time (numbers, species, prices). As such, Indonesia is not meeting its SDG targets that are related to curbing illegal wildlife trade and illicit financial flows.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 it