Bibliographic record
Abstract
The CVJ December 2008 ethical question prompted us to forward the following comments. Legislation is developed as a tool to ensure that societal norms are respected by all members of society. Animal welfare legislation requires skilled hands and a planned approach and needs to be recognized as a part of a set of tools that promote animal welfare. Canadian Food Inspection Agency (CFIA) legislation provides authority to control unacceptable actions by what is often a minority of bad players. Within the boundaries of the jurisdiction, it levels the playing field. The argument that legislation will drive socially unacceptable behavior elsewhere is not reason to allow that behavior to continue within a jurisdiction for which one has responsibility. Good legislation developed within the boundaries of societal values and science sets an example and other pressures, such as trade, can be used to effect changes elsewhere. Legislation can only impose minimum acceptable requirements, and is difficult to update in response to changing needs. Animal welfare legislation is best applied where animals are abused or neglected, or their needs are not being met, and animal owners/users are not controlling problems. Well structured and organized industries can demand high voluntary welfare standards from their members in the absence of legislation (1). Inappropriate or poorly designed legislation can exacerbate rather than solve problems. Legislation is not always the most effective option, especially when employed as a sole measure, without widespread stakeholder “buy-in.” In Canada, the federal regulatory process (2) requires that, before regulating, departments and agencies demonstrate that: a problem exists and government intervention, by regulation or other means, is justified; Canadians have been consulted; the benefits outweigh the costs; adverse impacts on the economy are minimized; intergovernmental agreements are respected; and regulatory resources are managed effectively. Legislation must be supported by factual information such as that derived from valid science and successful experience. Regulators must therefore consult with stakeholders and qualified experts when contemplating new or revised mandatory animal welfare standards. Regulated standards are effective only when enforced in a fair and consistent manner and are kept up-to-date and relevant. In Canada, regulatory jurisdiction for animal welfare is shared among the federal and provincial governments. The federal Health of Animals Regulations (3) and the Meat Inspection Regulations (4), regulate humane transportation anywhere in Canada and humane slaughter of animals in federally registered slaughter plants, respectively. In addition, the Criminal Code prohibits anyone from wilfully causing animals to suffer from neglect, pain, or injury. Provincially, on farm animal care activities are governed by a variety of regulations (5). Voluntary standards can raise the bar by implementing optimal practices. They also provide more flexibility and adaptability to change, and achieve commitment by industry and other animal owners. These standards work well if the leaders are well organized and communicate expectations to their constituents. Some of the many Canadian (6–8) and international (9–11) voluntary initiatives are referenced below. All of these complement Canadian regulated standards, which they facilitate with respect to awareness, industry commitment, and government enforcement. While not perfect, these various regulated standards and industry initiatives do advance animal welfare. They are continually under review with the goal of continuous improvement. As an example, the number of transportation of animal inspections conducted by the CFIA has increased more than 10-fold over the past 10 years, to approximately 36 000 per year in 2008. Of these, 95% of inspected transports were found to be in full compliance with the Health of Animals Regulations. In summary, the optimal approach to advancing animal welfare is a balanced blend of relevant legislation that is enforced and voluntary standards that are applied in practice.
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 | 0.000 | 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".