Expected Utility, Risk, and Marketing Behavior: Theory and Evidence from the Fed Cattle Market
Bibliographic record
Abstract
The effect of carcass quality uncertainty on the structure of the slaughter cattle market is investigated. A theoretical extension of the “Theory of Factor Price Disparity” is provided. It is demonstrated that the coexistence of a risk premium wedge between marketing channel (live weight, dressed weight, and grid) pricing mechanisms, in conjunction with varying degrees of producer risk aversion or producer perception of carcass quality uncertainty, contributes to the coexistence of multiple marketing channels. It is also demonstrated that risk and risk preference provide the linkage between carcass quality uncertainty and producer marketing decisions. We demonstrate how this linkage can affect the structure of the fed cattle market and the variability in slaughter volume across marketing channels. We also confirm the linkage between value‐based production techniques that increase seller information on carcass quality and seller increased usage of grid pricing regardless of actual carcass quality. Empirical evidence is provided in support of the supposition that carcass quality uncertainty plays a role in grid market share variability.
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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 | 0.003 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".