Détruire les animaux inutiles à la production : une activité centrale du point de vue de la souffrance éthique des salariés en production porcine industrielle
Bibliographic record
Abstract
Relying on enquiries in occupational psychodynamics realised in 2006 with employees in swine industrial production in Québec, this paper shows how the economical destruction of animals is experienced by them as a “dirty work” which goes against the moral sense they confer to their working relation toward animals. To rear is to contribute to animal lives in trying to save them from diseases and death. It is also to have the courage to take the moral responsibility for killing animals suffering from an incurable disease, in order to avoid useless sufferings. To endure this death job, employees deploy collective defence strategies. However, the adoption of behaviours based on manly courage stigmatises the difficulties of those who cannot manage to destroy animals, while these behaviours are themselves weakened by an important turn-over.
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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 | 0.012 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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; a candidate call from one teacher head, 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".