Awareness and perceived barriers to the adoption of best management practices for the transportation of lactating cull dairy cows of dairy producers in Ontario
Notice bibliographique
Résumé
The objective of this study was to understand dairy farmers' awareness of and perceived barriers to the implementation of best management practices (BMP) for the transportation of lactating culled cows being moved to auction or abattoir. An invitation to participate was emailed to all dairy farms in Ontario, Canada. Responses to this invitation were used to recruit additional participants through criterion purposive snowball sampling. In total, 28 dairy producers participated in 1 of 5 semistructured focus groups. All focus groups were audio recorded, transcribed verbatim, and analyzed with applied thematic analysis. Four themes were identified, including (1) transfer of responsibility, (2) interpersonal relationships, (3) juggling priorities, and (4) complexities of long-term planning. Individual participant knowledge varied, and participants also described misconceptions that other producers held surrounding transport duration and distances or the number of possible sales points for lactating culled cows. Participants did not agree on whether the producer's responsibility ended once the cow left their property or if all stakeholders from the farm to the final destination shared responsibility. Participants discussed the importance of existing trusted relationships with local cattle transporters and veterinarians to ensure information on best practices is shared. Participants also discussed how business pressures (e.g., production demands, space limitations) often challenge their ability to dry off lactating cows before transport; however, they mentioned that the degree of milk production may influence the destination of their animal (e.g., direct to slaughter for animals with high milk production). Some participants described a dynamic balance between business pressures and the potential for declining welfare of the animals under consideration for culling during lactation. Participants posited that producers who did not prioritize proactive herd management and producers nearing retirement had limited long-term planning for culling individual cows, which might lead to the transport of vulnerable or unfit animals. Finally, the lack of access to direct transportation to local slaughter was identified as an important barrier to adherence with the BMP for cull cows. In summary, many participants did not have an accurate understanding of what happens to cull cows after departing the farm, and they were unsure whether they retained a level of responsibility for an animal after it was transported from their farm. The priority placed by participants on trusted interpersonal relationships, the greater availability of peer-to-peer farmer training, and the professional accreditation of animal transporters, in addition to structural changes to increase local slaughter capacity, could potentially be leveraged to increase implementation of BMP and enhance lactating cull cow welfare.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,006 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,005 | 0,002 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 source (Gemma direct ou Codex distillé), 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 ».