Views of dairy farmers, agricultural advisors, and lay citizens on the ideal dairy farm
Notice bibliographique
Résumé
The aim of this qualitative study was to explore the shared and divergent views among Brazilian dairy farmers, agricultural advisors, and lay citizens on what characteristics they viewed were most important on an ideal dairy farm. Responses from 107 dairy farmers, 170 agricultural advisors (including veterinarians), and 280 lay citizens were subjected to thematic analyses. Five themes were identified: milk quality, animal welfare, economics, society, and the environment. Although all 3 groups made reference to each of the 5 themes, they emphasized different characteristics. The lay citizens placed the most emphasis on milk quality. In contrast, both the farmers and the advisors highlighted economics as the most important characteristic of an ideal dairy farm. When considering only animal welfare, we noted differences in the use of the constructs of animal welfare: farmers and advisors referred mostly to aspects related to biological functioning, whereas lay citizens emphasized affective states and naturalness. All 3 stakeholder groups referred to the use of pasture as being an important component of an ideal dairy farm but again differed in their reasons; citizens referred to pasture in the context of naturalness, whereas the other 2 stakeholder groups almost always referred to pasture using economic terms. Technology was highlighted by all 3 groups as an important characteristic of an ideal dairy farm but differences were noted in their justification for this view. For example, lay citizens viewed technology as a tool to improve milk quality, whereas farmers and advisors both referred to technology as an important vehicle to improve quality of life for those working in the industry. Lay citizens raised several concerns associated with the overuse of antibiotics and other chemicals, but farmers and advisors rarely mentioned these types of concerns. The latter 2 stakeholders placed considerable emphasis on the quality of life of dairy farmers and workers, an issue rarely discussed by lay citizens. Overall, our findings highlight several disconnects between the expectations of the lay citizens, and farmers and their advisors. We suggest that dairy farmers and agricultural advisors should both reflect on the desires of the lay public in what they view to be an ideal dairy farm, as this may help bridge some of the current disconnects.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,002 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».