Limited Trade and the CITES Ivory Trade Ban: Sustainable Use As a Viable Means of Conservation
Bibliographic record
Abstract
The over-exploitation of African elephants for their ivory has led to a dangerous decline in their overall population. As a result, they were granted protection under the CITES international trade agreement and given an Appendix I listing, which completely bans their international trade. I investigate the following question: under what circumstances is the limited trade allowed under the CITES ivory trade ban an effective strategy to stall the illicit trafficking of elephant ivory? Using Kenya and Zimbabwe as case studies, the feasibility of the preservationist and utilitarian viewpoints on elephant conservation are explored. This paper argues that the CITES ban on trade in elephant ivory is not the most effective way to protect elephant populations. Instead, limited and regulated trade should be instituted to ensure that African range states receive tangible benefits from elephant conservation. This could be achieved through keeping the more endangered forest elephants classified under Appendix I while moving the more stable savannah elephants to Appendix II. Community-based rights to elephants, specifically, should be put in place to ensure that locals living in close proximity to elephants have significant incentives to actively participate in elephant conservation, rather than participating in poaching or turning elephant habitat into agricultural land. While community-based wildlife rights under an Appendix II listing for savannah elephants are in no way perfect, they are a more effective and realistic means of conserving elephants than the alternative of a blanket ban.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".