Brazilian attitudes towards the use of animals in research
Bibliographic record
Abstract
Há poucos estudos sobre a opinião de latino-americanos quanto ao uso de animais em pesquisa. Este estudo avaliou o grau de apoio e as motivações de brasileiros em relação a essa questão. Os participantes foram aleatoriamente apresentados a dois cenários, um biomédico e outro ambiental, variando também o número de animais usados. Cada cenário se iniciava com o uso de suínos convencionais e prosseguia com o desenvolvimento e uso de animais geneticamente modificados. Foram analisadas 151 respostas quantitativas e 307 qualitativas. O cenário e o número de animais tiveram pouco efeito no apoio ao uso dos animais, no entanto, a oposição aumentou de 25% para 58% quando o uso de suínos geneticamente modificados foram apresentados no cenário ambiental. O apoio ao uso de animais em pesquisa estava frequentemente condicionado ao grau de bem-estar animal, e o apoio à pesquisa diminuiu com o uso de animais geneticamente modificados, em parte, devido aos riscos associados a essa tecnologia.
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How this classification was reachedexpand
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 | 0.026 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.018 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.000 | 0.003 |
| 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 itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
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".