A Survey to Understand Public Opinion regarding Animal use in Medical Training
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
A random survey was performed by ORC International Telephone CARAVAN®, on 24-27 March 2016, by trained interviewers. The aim of this survey was to gain further understanding of public perceptions in the United States of laboratory animal use, specifically for the purposes of medical training. Five statements were read in random order to the participants, who were then asked whether they agreed or disagreed with the statement. Survey responses were obtained from 1011 participants. For the combined statements: "If effective non-animal methods are available to train a) medical students and physicians, b) emergency physicians and paramedics, and c) paediatricians, those methods should be used instead of live animals", most respondents (82-83%) agreed. For the statement: "You want your doctor to be trained by using methods that replicate human anatomy instead of live animals", most respondents (84%) agreed. For the statement: "If effective non-animal methods are available, it is morally wrong or unethical to use live animals to train medical students, physicians and paramedics", 67% of respondents agreed. Responses were similar among the 15 pre-specified demographic subgroups. Given that effective non-animal training methods are readily available, the survey suggests that a substantial majority of the public wants the use of animals in medical training to cease.
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.
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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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 it