Producer Perceptions Toward Prevention and Control of Lameness in Dairy Cows in Alberta Canada: A Thematic Analysis
Bibliographic record
Abstract
Lameness in dairy cattle poses both an animal welfare and economic threat to dairy farms. Although the Canadian dairy industry has identified lameness as the most important health issue, lameness prevalence in the province of Alberta has not decreased over the last decade. Factors related to lameness have been reported, but the prevalence remains high. Therefore, this study was conducted to investigate dairy producers' perceptions on lameness and how these perceptions influence lameness prevalence in their cows. Qualitative interviews with open-ended questions were conducted with nine dairy producers in Alberta, Canada presenting farms with a wide variety of lameness prevalence. Thematic analysis of these interviews revealed five major themes, as well as five distinct types of producers regarding their perceptions. All nine producers mentioned similar challenges with lameness prevention and control. Identifying lameness, taking action, delays in achieving success, various approaches to prevention and control strategies, and differences between farms were the challenges encountered. However, producers' attitudes when dealing with these challenges varied. We concluded that understanding producers' perceptions is essential as no "one size fits all", when advising them regarding how to address lameness, as guidance and support will be most successful when it is aligned with their viewpoint.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".