Is gene editing an acceptable alternative to castration in pigs?
Why this work is in the frame
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Bibliographic record
Abstract
Male piglets are commonly castrated to eliminate the risk of boar taint. Surgical castration is the commonly used procedure and is known to induce pain. Gene modification targeted at eliminating boar taint in male pigs has been proposed as a possible alternative to surgical castration. The aims of this study were to explore public acceptability of this biotechnology using a mixed methods approach. Quantitative data to assess acceptability of 570 participants from southern Brazil were analysed with multinomial logistic regression models and Spearman correlations; qualitative responses of the reasons provided in support of their position were coded into themes. Just over half of the participants (56%) considered gene modification of male pigs acceptable. Acceptability was lower among participants who grew up in an agricultural environment (ρ = 0.02), but was not influenced by sex, age, religion, urban or rural living, or level of education. Acceptability of gene modification of male pigs as an alternative to surgical castration was positively related to the perception of benefits (r = -0.56, ρ<0.0001) and negatively related to the participant's perception of risks (r = -0.35, ρ<0.0001). Acceptability was not related to knowledge of basic concepts of genetic biotechnologies (r = 0.06, ρ<0.14), or to awareness of issues related to pig castration or boar taint (r = 0.03, ρ<0.44), both of which were low among participants. Participants that considered gene modification of pigs acceptable justified their position using arguments that it improved animal welfare. In contrast, those that were not in favour were generally opposed to genetic modification. Unforeseen downstream consequences of using genetic modification in this manner was a major concern raised by over 80% of participants. Our findings suggest that perceived animal welfare may encourage public support of gene editing of food animals. However, potential risks of the technology need to be addressed and conveyed to the public, as many participants requested clarification of such risks as a condition for support.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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