Economic sustainability of extending lay cycle in the supply-managed Canadian egg industry
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The productivity levels of the Canadian egg industry have increased over the years, including hen productivity and feed conversion efficiency. Moreover, genetic improvements combined with improved feed and light management have recently resulted in hens potentially being able to produce 500 eggs in an 80-week laying cycle. Nevertheless, most egg farms in Canada are still on a 51-week production cycle despite high hen productivity levels at culling. Lack of economic impact information, combined with the fact that egg production is under supply management in Canada and that farmers are paid their cost of production reduces the incentive to extend laying cycles despite the savings associated with lower rates of flock replacement. On the other hand, a greater percentage of large eggs is beneficial to the value chain, and the use of fewer resources per egg associated with longer laying cycles generates environmental benefits. This article analyzes the economic sustainability of extending laying cycles in Canada by combining partial budgeting analysis based on farm-level data with a non-linear mathematical programming model to assess the economic costs and benefits of extending laying cycles, while taking into consideration the policy context of supply management in Canada. The results suggest that, for hens housed in an aviary, extending the laying cycles from 51 to 64 weeks would increase profits by approximately 6% per year over a 5-year period. Our optimization model forecast that a laying cycle of 71 weeks would be economically optimal, with an average productivity of 6.7 eggs per hen per week and a cumulative mortality rate of 5.53%. This article, through an innovative methodological approach that combines partial budgeting and non-linear mathematical programming models, generates information to help the egg industry stakeholders to make informed decisions on extending laying cycles while considering the policy context of supply management in Canada.
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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 | 0.000 | 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 it