Canadian dairy farmers' perception of the efficacy of biosecurity practices
Bibliographic record
Abstract
The adoption of biosecurity practices on dairy farms is limited worldwide. Multiple aspects, one of which is the perception of the effectiveness of these practices, influence the adoption of preventive behavior. The objectives of the present study were to investigate the general understanding of biosecurity by Canadian dairy farmers and to describe their perception of the effectiveness of specific biosecurity practices. In 2015, 368 Canadian dairy farmers were selected to participate in an on-farm national cross-sectional benchmarking study during which they were asked about their general understanding of biosecurity and their perception of the effectiveness of 17 practices to minimize biosecurity risk. For these same biosecurity practices, respondents were asked whether they discussed that particular practice with a veterinarian and whether they implemented it on their farm. Herd and respondent characteristics were also recorded. Associations between the perception of effectiveness of each biosecurity practice and the discussion with a veterinarian, its implementation on farm, and the herd and respondent characteristics were examined using ordered regression models. Most respondents thought the purpose of on-farm biosecurity was to prevent both entry of a new pathogen and spread of an existing pathogen (73%) and considered general biosecurity to be effective (92%) and important (58%). When asked about specific biosecurity practices, respondents considered most of them to be effective (60-94%). Practices related to direct animal-to-animal contact were perceived as effective by more respondents than biosecurity practices related to fomites and visitors. Less than 20% of the respondents reported discussing the different biosecurity practices with a veterinarian, and less than 60% reported implementing these practices on their farm. Geographical region, involvement of a veterinarian, and implementation of the practice on farm were associated with the perception of effectiveness for multiple practices. Finally, the reasons chosen by most respondents as motivation to implement biosecurity practices were (1) if the practice helped to regionally prevent the introduction or the spread of a disease and (2) if it was proven to be beneficial to the health and welfare of animals. These results show that there is a positive perception of the effectiveness of specific biosecurity practices, that there might be a lack of understanding of the practices involving transmission of diseases via indirect contact, and that the perceived threat associated with not adopting practices is minimal.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".