The Entrepreneurs: Dairy farmer perspectives on finding an industry solution for the surplus calf issue – a participatory case study
Bibliographic record
Abstract
The main objective of this case study was to pilot a novel methodology to deepen our understanding of how dairy producers envision the future of surplus calves in Atlantic Canada, including identifying who they felt were important to speak to as they discussed this topic. A second objective was to understand the perspectives of a key group the producers requested to speak to, representing a variety of dairy industry partners, including veterinarians, genetics companies and animal welfare scientists amongst others (referred to as the allied industry) on the future of surplus calves. To reach these objectives, we used an inclusive participatory approach that, to our knowledge, has not yet been applied to the surplus calf issue. This approach included a series of five participatory group discussions with volunteer dairy farmers from Atlantic Canada; the allied industry group was invited to two group discussions. Key themes from the discussions included: 1) challenges with surplus calf production on the dairy farm, such as a lack of knowledge about what type of calf would be desired by the marketplace, 2) the role of leadership and partnership in the creation of a dairy beef system, including the need to overcome communication barriers between different stakeholders, 3) post-farm gate aspects of surplus calf production, including the desire to cater to a local market, and 4) ensuring that the proposed system is economically and socially sustainable.
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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 | 0.015 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.015 | 0.004 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".