Promoting the Transition to Non-Lead Hunting Ammunition in the European Union Through Regulation and Policy Options
Bibliographic record
Abstract
Regulation (EU) 2021/57, banning the use of lead gunshot in wetland hunting, and adoption of the proposed European Union (EU) restriction on lead ammunition use by civilians in other types of hunting and target shooting, would complete the transition to non-lead ammunition use in the EU and ensure major compliance among hunters and shooters. The transition is possible since non-lead substitutes for all types of shotgun and rifle ammunition are produced already by leading European manufacturers. To ensure ammunition non-toxicity, EU standards are needed for lead substitutes to accompany both existing and potential future lead ammunition restrictions. Meat from wild game birds and mammals is a large and important commodity in the EU. Setting a maximum lead level in all marketed game meats under Regulation (EC) 1881/2006, aided by mandatory food labelling, would add extra health protection to human consumers. This regulatory step would help ensure that all wild game destined for retail markets were taken with non-lead ammunition, would complement existing and proposed European Commission restrictions on lead hunting ammunition and aid monitoring and enforcement. Increased public awareness of the risks posed by lead from ammunition to the health of humans, wildlife, and the environment, and especially their associated externalized costs to society, would promote and facilitate the passage of regulation to protect human and environmental health from toxic lead ammunition.
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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 | 0.024 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.012 | 0.007 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.030 | 0.005 |
| Insufficient payload (model declined to judge) | 0.006 | 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".