Barker's Grub: Easy, Wholesome Home Cooking for Your Dog
Bibliographic record
Abstract
Dave Perrin (WCVM '73) has done it again! In short, he has published a sequel to his very successful 1st book (Don't Turn Your Back in the Barn: Adventures of a Country Vet) (Can Vet J 2001;42:393). Don't Turn Your Back in the Barn has been on “Chapters” national best seller top 10 list, routinely, and has been named a required book to be handled by all stores in their chain. Perrin's 2nd book — the one reviewed here, Dr. Dave's Stallside Manner: More Adventures of a Country Vet, is similar in format to his first book in that it comprises a collection of short stories centered around his early years in veterinary practice in rural southeastern British Columbia. “Stallside Manner” has rocketed to the top of the best seller list in British Colombia since its release in December 2001 and is already in its 1st reprint. Several other countries — Australia, New Zealand, and the USA are in the process of printing the books. I enjoyed this book immensely. Many of the situations that arise really had me laughing, and, yes, I also shed a few tears (quite an admission for this hard-bitten older practitioner). The characters are colorful and well developed. More than that, they are all nonfictional and have come to us right from Dave's client list! We meet Eleanor — a well educated, but financially challenged, chain-smoking individual with a house full of cats, an old horse named O'Brien, and a heart of gold. We shiver through a bone chilling cesarean on a heifer at minus 40°C, and then experience the rest of the night with this solo rural practitioner during calving season. Through all the frustrations, pressures, and fatigue of being the only veterinarian in a rural community, Dave has the ability to extract the humor from difficult situations. He never loses sight of the real art of veterinary practice — that is, demonstrating compassion for and maintaining the dignity of both his clients and his patients. The 2 books together make a wonderful series of real practice stories with a great cast of characters for all veterinarians, hospital staff, and, especially, clients to enjoy. Dr. Perrin is truly our Canadian version of James Herriot; your clients will love the stories and our profession can only benefit from his unique talent. I suspect that Dr. Perrin is well and truly on his way to becoming a national veterinary treasure! A television series is currently being negotiated.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.110 | 0.064 |
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".