CLE Working Paper No.2/2021--Defending Nature Against Rodenticides
Bibliographic record
Abstract
Anticoagulant rodenticides (i.e., rat poisons) are highly toxic compounds that have been recognized for decades to have devastating effects on wildlife species and the wider ecosystem. In this paper, I argue that the continued use of anticoagulant rodenticides is entirely inconsistent with the provincial and federal governments' obligations to citizens and the environment under their respective pesticide legislation, and that the governments' failure to fulfill these obligations is due in part to the refusal to acknowledge rights of nature. I provide an overview of the current statutory and regulatory framework for pesticides in Canada and examine the practical effects of the legislation, evidencing the harms associated with rodenticide use and inefficacy of these products to illustrate the dubious value of their continued registration. I further discuss the inadequacy of the implemented risk mitigation measures and viability of existing alternative methods of rodent control to support my argument that the use of rodenticides is inconsistent with the current regulatory framework. To address these inconsistencies, this paper sets out recommendations for action that can be taken in British Columbia by municipal governments and the provincial government, as well as the federal government of Canada. Examples of similar action taken in other jurisdictions are also provided.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.013 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.008 | 0.003 |
| Scholarly communication | 0.013 | 0.003 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.030 | 0.009 |
| Insufficient payload (model declined to judge) | 0.060 | 0.030 |
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".