Supply management and the business activities of Ontario meat processors
Bibliographic record
Abstract
Canadian supply management policies in dairy, poultry and eggs have been hotly debated for over 50 years. During the most recent renegotiation of the North American Free Trade Agreement (NAFTA) in 2017-2018, the U.S. threatened to cancel NAFTA if concessions were not made to Canada’s supply management policies in agriculture. During the renegotiation, many arguments for and against supply management in agriculture were repeated, some were updated, and some newer perspectives relating to sustainability and social responsivity were more enthusiastically discussed. Most arguments critical of supply management have been developed using economic analyses of market and industry-level impacts of supply management. On the other hand, supportive arguments are often qualitative, focus on the survival of smaller farms and generally lack empirical investigation based on application of relevant theory. This paper uses management theory to investigate the impact of supply management of management and business activities on food processing firms. We use a framework that links business activities with the broad regulatory environment to interpret evidence from a study of independent meat processors in Ontario, Canada, particularly those that processed turkey, which is a supply managed sector; and pork, which is not. Results suggest that the broad regulatory environment facing Ontario meat processors is of greater concern to managers of independent processing businesses than the specific regulatory environment of supply management. Results also suggest the value creation activities and strategies used by a business may affect how managers assess opportunities and challenges in this specific regulatory environment.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".