The demand for pork products in Canada: The effects of discounts
Bibliographic record
Abstract
This thesis is an investigation of the effects of discounts on the demand for pork products in Canada. A linear approximation Almost Ideal Demand System (LA/AIDS), with the Shonkwiler and Yen (1999) two-step sample selection procedure, is estimated. The first step focuses on consumer characteristics affecting the probability of purchasing pork products. The second step examines the discount and price variables associated with the quantities of pork products purchased. The results indicate that four discounts (coupons, membership discounts, price cuts, and quantity discounts) positively affect the demand for selected pork products in Canada. This study has three contributions to literature. Firstly, this study presents the consumption patterns of disaggregated pork products by exploring the effects of discounts. Secondly, this study categorizes fresh pork products based on the origin of the cuts, which is different from past studies. Finally, the price and expenditure elasticity estimates stand alone as an important contribution.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".