An analysis of Canada's declared live wildlife imports and implications for zoonotic disease risk
Bibliographic record
Abstract
In Canada, there have been calls for increased research into and surveillance of wildlife trade and associated zoonotic disease risks. We provide the first comprehensive analysis of Canadian live wildlife imports over a 7-year period (2014–2020), based on data from federal government databases obtained via Access to Information requests. A total of 1 820 313 individual animals (including wild-caught and captive-bred animals but excluding fish, invertebrates, Columbiformes (pigeons), and Galliformes (game birds)), from 1028 documented import records, were imported into Canada during 2014–2020. Birds were the most imported taxonomic class (51%), followed by reptiles (28%), amphibians (19%), and mammals (2%). In total, 22 taxonomic orders from 79 countries were recorded as imported. Approximately half of the animals (49%) were imported for the exotic pet market. Based on existing literature and a review of the Canadian regulatory apparatus, we gesture to these importations' potential implications for zoonotic disease risk and discuss potential biosecurity challenges at the Canadian border. Finally, we identify data gaps that prevent an extensive assessment of the zoonotic disease risk of live wildlife imports. We recommend data collection for all wildlife importation and improved coordination between agencies to accurately assess zoonotic disease risk.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 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".