Willingness-to-Pay for Fresh Brand Name Beef
Bibliographic record
Abstract
Willingness-to-pay (WTP) for hypothetical brand name fresh beef products was measured using the Becker-DeGroot-Marschak experimental auction procedure. Auctions were conducted in a field setting in and around Winnipeg, Manitoba during the summer of 2006. Four hypothetical brands were developed to individually represent local/Canadian, natural, guaranteed tender, and Angus attributes, respectively. It was found that WTP was highest, approximately $1.31 per 12 ounce steak, for branded steaks associated with the natural, guaranteed tender, and Angus attributes. It was further discovered that WTP is positively affected by preference for the brand name, frequency with which beef is consumed, and the male gender. Conversely, confidence in selecting beef tended to reduce WTP, while effects of age, education, and income were uncertain. It is concluded that the industry should explore opportunities to market higher value products both domestically and abroad if the cost of doing so does not exceed WTP premiums. Nous avons évalué, a ̀ l’aide de la procédure d’enchères expérimentales Becker-DeGroot-Marschak, la volonte ́ de payer (VdP) des consommateurs pour des produits de bœuf frais de marques hypothétiques.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".