Autonomy and paternalism in quality of life determinations in veterinary practice
Bibliographic record
Abstract
Abstract Assessments and predictions of patient quality of life (QoL) permeate many veterinary decisions, including (1) whether to perform a procedure due to concurrent QoL issues, (2) whether a procedure will negatively affect QoL in the near or distant future, and (3) whether QoL is poor enough to warrant euthanasia. In order to understand how veterinarians manage decisions relating to patient well-being, interviews with 41 veterinarians and over 100 hours of observations of 10 veterinarians were conducted. Participants held diverse views regarding the type of parameters that should be included when defining QoL. Interestingly, they also held differing views about who should be assessing patient QoL, with some participants believing that animals' owners were better able to assess patient QoL than veterinarians. For these veterinarians, respecting the client's autonomy in deciding what was best for the patient weighed heavily in their decisions. Other veterinarians felt that they, rather than the client, were the best assessors of QoL and felt justified in persuading clients to follow a certain course of action (often considered a paternalistic approach). These findings raise some interesting questions for the profession. What role should veterinarians play when assessing patient QoL? When is paternalism acceptable or even mandatory in veterinary medicine? Does respecting client autonomy also require an evaluation of the client's abilities to make appropriate decisions for the patient? The lack of uniformity in defining and assessing patient QoL highlights the need for increased dialogue with respect to veterinarians' responsibilities to both animals and clients.
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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 | 0.083 | 0.184 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.018 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".