Bibliographic record
Abstract
It is with great interest that I read the recent commentary on public policy and veterinary medicine by Drs. Nielsen, Buntain, Stemshorn, and Evans (1). The authors are highly respected individuals who have done much in their respective careers to advance critical thinking in public veterinary medicine. As a recently retired provincial Chief Veterinary Officer, over the last several months I have had the opportunity to reflect on the role of public veterinary medicine, without having to face the daily issues and pressures of my former position. I agree wholeheartedly with the authors that, for too long, public veterinary practice has been overlooked, both as a recognized discipline and as a field for research. But why is that? My personal view is that the practice of public veterinary medicine has largely been viewed within the profession as government regulatory work, focussing on the details of learning the regulations and applying the rules. This largely misses the heart of public practice, which is to contribute to the development of policy that deals with significant real life issues — policy that makes sense and that takes a balanced approach to what are often competing interests. Getting policy right is the first step towards developing the strong regulatory framework which is essential to good public practice. Developing good policy is often not a simple task. How do we balance the rights and interests of the individual against the greater societal good? Or, how do we balance the rights of two interest groups with very different points of view? These are often difficult discussions which go beyond the realm of science, venturing into a competition between belief systems. Nowhere is this more evident than in discussions involving animal welfare. Sure, science does matter, but people’s feelings and moral views will hold much more sway in the discussion than will any scientific research paper. I suspect that some veterinarians and perhaps some producer associations have not yet realized that most of the public debate about animal welfare is centred on moral issues, not scientific ones. Good policy making is based on science, but it must also take into account these social mores. In the past, there has been only limited involvement of the academic community in studying how to formulate policy. Most of us who have had to develop public policy have done so by learning on the job, usually by taking on new positions with increased responsibilities within government. In the face of an emergency, public officials may consult with academic experts for technical advice, but often decisions must be made quickly and there is no time to conduct the research we might wish to have. It is in these times, where we draw on our previous experience with similar situations to make the best decision possible. The weight of this decision-making is significant, and I might argue especially far-reaching in animal health. For example, if a medical officer of health quarantines a school, then all of the students, teachers, and parents are affected. This is a substantial consequence, but one that is mainly confined to the local area. However, if a chief veterinary officer quarantines a farm, then international trade for the entire country could be stopped. We have seen examples in the past where some countries apply international sanctions to Canadian products even in in the case of diseases that are not officially reportable. Canada has successfully faced challenges with outbreaks of emerging diseases such as bovine spongiform encephalopathy (BSE), pandemic H1N1 influenza, food-borne listeriosis, and now porcine epidemic diarrhea. These have provided valuable lessons that should be reviewed and studied in an academic realm so that these lessons are not lost. I think what we will find most valuable from this exercise will be to outline, not so much the technical details, but rather the guiding principles that were used to arrive at major policy decisions during these challenging times. It is inevitable that some new disease in some species will arise in the not-too-distant future so it is critical that we learn from the past as to what principles worked and what did not, and under what context they were applied. This retrospective analysis is where the academic community can add real value to public policy-making. To formulate policy prospectively; however, we need to broaden the discussion to include not just government (federal, provincial, and territorial) and academic veterinarians, but also other stakeholders, such as non-government organizations, producer associations, and consumer groups. The National Farmed Animal Health and Welfare Council (www.ahwcouncil.ca) is comprised of senior policy advisors from federal/provincial/territorial governments (such as the Council of Chief Veterinary Officers), producer industry associations, public health and academia (one member). The Council has commissioned a number of excellent policy advisory papers on topics such as national animal health surveillance, animal welfare, and antimicrobial use in food animals. This work is based on supporting the guiding principles outlined in the National Farmed Animal Health and Welfare Strategy. The strength of the Council is that it represents a broad range of stakeholders within its members. In addition, the Council’s annual national animal health and welfare forum provides an opportunity for even broader input from interest groups. It is clear that no single agency, department or organization can manage the evermore complex challenges that we will face in the future. Having all the important players at the policy-formulating table just makes good sense. In conclusion, I wholeheartedly support the authors’ call for increased academic involvement in researching policy in animal health, animal welfare, veterinary public health and food safety by applying the principles of One Health. I also support the proposal to develop an organization of veterinarians interested in public practice. Developing sound public policy within the realm of public veterinary medicine is a specialty in its own right. However, we need to go further and actively support a broadly based policy think tank, such as the National Farmed Animal Health and Welfare Council, where practical solutions can be developed.
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 | 0.011 | 0.036 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.016 |
| Scholarly communication | 0.012 | 0.014 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.027 | 0.038 |
| Insufficient payload (model declined to judge) | 0.028 | 0.013 |
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".