Consumer Preferences in the Emerging Bison Industry
Bibliographic record
Abstract
Abstract Bison herds in western Canada have grown rapidly as producers seek to diversify their farm enterprises. Much of this growth, however, has been driven by high prices for breeding stock. Markets for bison meat have begun to emerge, and growth in these markets is essential for the long-run sustainability of the industry. However, very little information exists regarding potential bison consumers and their attitudes toward bison products. Using conjoint analysis, a survey of consumers in western Canada was used to gather information on consumer preferences for bison. Hypothetical bison products were described in terms of different levels of four attributes: price, fat content, tenderness and convenience to cook. Price emerged as the most important of the four variables; however, there was evidence that some consumers would be willing to trade off higher prices for increased tenderness and lower fat content. Cluster analysis revealed distinct consumer segments with different preference structures, pointing to potential product differentiation strategies for the bison industry.
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How this classification was reachedexpand
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 | 0.003 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".