Exploring industry perspectives and preferences about calf handling and restraint methods used during spring processing of calves in western Canada
Bibliographic record
Abstract
Abstract Calf processing events have important animal health, management, and sociocultural roles in the beef cattle industry. In western Canada, the three most commonly used methods for spring processing are roping and wrestling (RW), roping and Nord fork (NF), and tilt table (TT). The objective of this study was to understand the preferences and perceptions of handling event participants about calf handling and restraint methods commonly used during western Canadian beef calf processing events during the spring season. Data were collected using a mixed-methods online questionnaire. Quantitative analysis was used to describe the study participants and determine preference rankings. Qualitative, thematic analysis was used to explore participants’ perceptions about the common handling and restraint methods and to identify values within and across participants. The majority of participants were farm hands or staff members (92.8%), followed by owners (4.9%), family members (1.4%), friends (0.5%), and others (0.4%). The most preferred method to use was RW, and TT was the least preferred (χ2 = 3239.1, df = 6, p < 0.001). Participants shared values regarding calf safety and stress, processing efficiency, convenience, human safety, and labour intensity when explaining their preference to use calf handling and restraint methods for spring processing. Responses highlighted the need for understanding and skill in low stress handling and processing tasks in order for any of the methods to be effective. These values identify aspects to address when developing best practice recommendations for calf handling and restraint. Furthermore, focusing communication through the lens of these shared values will likely positively engage participants in extension efforts and community discussions.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".