From Canada to Scotland: The Incorporation of Ethical Wildlife Control Principles: A Review
Bibliographic record
Abstract
In 2015, 20 experts from academia, industry, and non-governmental organisations on 5 continents agreed to a set of seven international principles for ethical decision making (“the principles”) in managing human–wildlife conflict. The principles have since been recognised in wildlife management policy and standards in parts of British Columbia, Canada. In 2022, the principles were introduced to the Scottish Parliament by means of a formal Motion lodged by Colin Smyth MSP. Smyth expressed the view that opportunities existed to integrate the principles into the Scottish Government’s strategic approach to wildlife management and its species licensing review. The (now former) Minister for Environment, Biodiversity and Land Reform at the Scottish Government, Mairi McAllan, stated in the Motion debate that followed that she was committed to working to understand how the principles could sit alongside the Scottish Government’s ambitious programme to protect animals and wildlife. The Hunting with Dogs (Scotland) Bill was introduced to the Scottish Parliament prior (February 2022) to the Motion debate but passed on 24 January 2023, following various debate and amendment stages. It offered parliamentarians the first opportunity to align wildlife-specific legislation with the principles. The Bill received Royal Assent on 7 March 2023 and is now the Hunting with Dogs (Scotland) Act 2023 (“The Act”). A review of The Bill (and subsequent Act) can assist in identifying where it could have aligned more closely with the principles to assist decision makers in understanding how to usefully incorporate the principles into future wildlife legislation and policy.
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 | 0.018 | 0.064 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.016 | 0.025 |
| Science and technology studies | 0.004 | 0.007 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".