Do CITES trade restrictions work? Some evidence from the markets for sawfish trophies
Bibliographic record
Abstract
The durability of animal parts that are collected and traded as trophies has an impact on species sustainability, especially when animals are slow-growing, have low fecundity, or are particularly vulnerable to capture. CITES (the Convention on International Trade in Endangered Species of Wild Fauna and Flora), aims to control the trade of wild fauna and flora specifically by using trade restrictions as a policy option. However, specialists in international trade have advised against using trade restrictions to correct social cost issues. The reasons for this advice have to do with the unintended economic consequences of animals being placed on an endangered species list, coupled with the trade restrictions themselves. We focused on Pristis spp. (sawfish), a species in danger of extinction found in Appendix I of the CITES convention. An extensive search of sawfish saws for sale on the internet was performed during 2016 and 2017. A total of 174 observations of market prices were collected. We estimated several models linking prices to the size of the saw with other variables that might explain price variability using OLS regression, and which included data from both the original internet searches and additional variables, including a dummy variable which indicated the year in which the species group was placed in Appendix I. These models show that rather than slow down the extinction pathway for this species, CITES may have sped it up, as well as driving the sawfish trophy markets underground.
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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 | 0.006 | 0.045 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.034 | 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".