Health Canada: Pollinator Protection and Pesticides
Bibliographic record
Abstract
Health Canada’s Pest Management Regulatory Agency (PMRA) is responsible for regulating pesticides in Canada, including assessing potential risk to pollinators. Pollinator health is a complex issue that may be affected by multiple factors including pests, diseases, habitat and nutrition, bee management practices, and pesticides. The pesticide risk assessment framework for pollinators has been recently updated and improved in collaboration with the United States Environmental Protection Agency and the California Department of Pesticide Regulation. Health Canada is also working with international partners and stakeholders to develop improved measures to reduce pollinator exposure to pesticides through improved labelling, best management practices, and mandatory and voluntary mitigation measures. Many of the measures being developed are related to planting of insecticide treated seed, an area that was highlighted in 2012 and 2013 when Health Canada received a significant number of honey bee mortality reports from corn growing regions of Ontario and Quebec. Exposure to insecticides from dust generated during planting of treated corn seeds was determined to contribute to the majority of these bee mortalities. With the cooperation of multiple partners and stakeholders, including the provinces, registrants, seed distributors, equipment manufacturers, growers, beekeepers, and researchers, technical solutions and best management practices have been developed and implemented to reduce pollinator exposure to pesticides during planting of treated seed. Efforts are continuing to better understand the potential risks to pollinators from all areas of pesticide use and to develop additional measures that will further reduce exposure and risks.
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 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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".