“You tested, now what?”: Exploring British Columbian dairy producers' perceptions on Salmonella Dublin management and mitigation
Bibliographic record
Abstract
Salmonella Dublin ( S. Dublin) is a bacterial disease that affects dairy cattle, causing calf loss, abortions, and reduced milk yield, and is often difficult to control as some animals become chronic carriers. In British Columbia bulk tank milk serology found that 30 % of dairy farms in the province were positive for Salmonella Dublin, which prompted a need for investigation into S. Dublin disease management and mitigation. The objective of this study was to explore BC dairy producers' perceptions and experiences of S . Dublin and how they relate to their actions in S . Dublin management and mitigation, and to leverage this information to inform provincial S . Dublin management programs. Semi-structured interviews were held with 10 BCE dairy producers, which were recorded, transcribed and analyzed using the Health Belief Model. Overall, dairy farmers in this study expressed uncertainty surrounding S. Dublin and its management. This uncertainty stemmed from several key sources: 1. Unclear roles and responsibilities regarding disease management among stakeholders, specifically government; 2. Differing views on the necessity of government regulation; 3. Confusion about how information on S. Dublin and disease management is communicated; and 4. Challenges with self-efficacy in the management of S. Dublin. Together, this points towards a need for improved communication and messaging surrounding S. Dublin in BC. Given the perceived value of peer-to-peer communication and narratives, disease messaging may be more effective when coming from sources like producer-led organizations, herd health veterinarians, and “boots on the ground” government officials, as opposed to faceless, top-down government messaging. Ultimately, a deeper understanding of how producers approach S. Dublin management over time and across Canada would strengthen the development of effective strategies for the management of and mitigation of S. Dublin.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.005 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".