Bibliographic record
Abstract
Abstract The role of food traceability systems in resolving information asymmetry is explored. Three functions of traceability systems are identified: ex post reactive systems that allow the traceback of affected products in the event of a contamination problem so as to minimize social costs, ex post systems that facilitate the allocation of liability, and information systems that provide ex ante quality verification. A taxonomy of traceability systems illustrates the multidimensional nature of the information problems related to food safety and food quality. A model of ex ante quality verification and ex post traceability systems is used to demonstrate the different functions and incentives of a traceability system. Finally, examples of private sector and regulatory traceability initiatives are discussed within the context of the ex post and ex ante models developed in the paper. [EconLit citations: Q130; Q180; L150.] © 2004 Wiley Periodicals, Inc. Agribusiness 20: 397–415, 2004.
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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 | 0.019 | 0.056 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.002 | 0.011 |
| Scholarly communication | 0.010 | 0.016 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".