Evaluating Reforms in Canadian Chicken Marketing Mechanisms Using a Linear-Quadratic Inventory Model
Bibliographic record
Abstract
Marketing institutions in supply managed industries are evolving due to broad globalization pressures. The output and sales decisions of chicken processing firms under two different pricing mechanisms are modeled using a linear-quadratic inventory model. Decision rules lead to structural equations that relate output and sales to their own lagged values, lagged inventories and lagged prices and cost indicators. A Generalized Method of Moments (GMM) estimator is applied to the system of equations. The null hypotheses no adjustment costs in processing and no role for inventories in marketing are rejected. We simulate the impacts of reforming the chicken pricing mechanism, moving from producers vs. processors bargaining to a formula-based price (referred to as cost-plus"). Output in the industry is higher under the bargaining pricing system mostly because processors pay a lower price than under the cost-plus" mechanism. Simulations reveal that producers' expected profits are lower on average under the bargaining system than under cost-plus." Moreover, the cost-plus" system reduces the variability of profits.
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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 | 0.007 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".