Role of credence and health information in determining US consumers’ willingness‐to‐pay for grass‐finished beef
Bibliographic record
Abstract
Consumer demand for forage‐ or grass‐finished beef is rapidly emerging in the US. This research uses data elicited from consumer surveys and experimental auctions to provide insight on product attributes (taste/flavour, credence and nutritional characteristics) and socio‐demographic factors that are most important in determining US consumers’ preferences and willingness to pay premiums for grass‐finished versus grain‐finished beef. Information related to beef production processes increased the probability consumers would be willing to pay a premium for grass‐fed beef. However, it appears that health‐related messages are more important drivers of willingness‐to‐pay, on average, than the absence of antibiotics and supplemental hormones and traceability. Labelling information regarding grass‐fed beef’s nutritional content and related production processes is vital for maintaining and growing premium niche markets for grass‐fed beef in the US. The relative size of the willingness to pay estimates compared to previous cost estimates suggest that the Australian beef industry may have a comparative advantage for finishing beef on forage and marketing premium grass‐fed differentiated beef products in the US market.
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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 | 0.001 | 0.000 |
| 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 | 0.001 |
| Open science | 0.000 | 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 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".