LOBBYING SEMINAR A SUCCESS: Top government relations experts as speakers.
Bibliographic record
Abstract
Veterinary leaders from across the country came to Ottawa to participate in the CVMA training seminar on lobbying and public policy advocacy, held at the end of October (see ( Can Vet J 2001;42:683-684). The 2-day seminar, which involved specific veterinary case studies, focused on government relations at both the federal and provincial levels. The ultimate goal of the seminar was to enhance the influence that the veterinary profession has on government decision-makers and public opinion leaders. Provincial veterinary associations sent representatives, who joined members of the CVMA Executive and the chairs of the CVMA priority committees, a total of 25 participants. They all left the seminar with a sense of having acquired sound knowledge on how governments work and how the veterinary community can have an impact on public policy. On day 1, participants heard speakers with expertise in different fields. On day 2, they undertook case study examinations and developed scenarios and plans on the following 4 veterinary topics: Erosion of veterinary services in government (and the use of nonveterinarians in positions previously occupied by veterinarians); establishing greater visibility and credibility of the veterinary profession; implications for food safety in Canada, etc. Dealing with the Veterinary Drugs Directorate (formerly the Bureau of Veterinary Drugs) (its concerns about overuse of certain drugs and implications for disease resistance) Provincial issues (professional self-regulation; right to practice, etc.) Preserving and sustaining Canadian veterinary colleges. The course leader was one of Ottawa's most respected lobbyists, Mr. Sean Moore, of the firm Gowling-Lafleur-Henderson. Mr. Moore impressed participants with his knowledge, experience, and exceptional communication and presentation skills. A former senior deputy minister at both the provincial and federal levels, Mr. Bruce Rawson, gave a presentation on how to prepare oneself to meet a minister or senior government officials, and left a list of 50 practical tips to consider. Another speaker was Dr. Maurice Foster, a veterinarian who served 25 years as a Member of Parliament and, subsequently, worked for the Prime Minister of Canada as Special Assistant for Caucus Liaison. Dr. Foster provided compelling information and anecdotes on the workings of government that only a person with his experience could have. A presentation by Ms. Chantal Courchesne of the Canadian Medical Association dealt with effective strategies and tactics to influence elected officials. Dr. Gordon Dittberner, CVMA's Senior Advisor on Veterinary Affairs and a former Assistant Deputy Minister at Agriculture Canada, led the issues-specific workshops. The CVMA President, Dr. Michael Baar, wants to ensure that this group of veterinarians interested in government relations not lose contact with each other. To that end, the CVMA will set up a discussion board on lobbying on its website: www.canadianveterinarians.net. Members of the CVMA interested in public advocacy are welcome to contribute to the discussions. (by Claude Paul Boivin, Executive Director, CVMA) (From left to right) Ms. Chantal Courchesne, Mr. Bruce Rawson, Dr. Maurice Foster, Dr. Michael Baar, CVMA President, Mr. Sean Moore and Dr. Gordon Dittberner. Dr. Maurice Foster, speaks to the seminar participants at the National Press Club.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.002 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.090 | 0.028 |
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".