Perceived Traceability Costs and Benefits in the Italian Fisheries Supply Chain
Why this work is in the frame
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Bibliographic record
Abstract
The paper proposes a model in which it is hypothesized that firm characteristics influence both costs and benefits of traceability. The proposed model differentiates between aggregate measures and specific categories, as well as between expected costs and benefits on the one hand and perceived actual outcomes on the other, and is tested in a series of regression analyses based on a survey sample of 60 Italian fish processors. The findings indicate that firm characteristics are not strongly associated with any specific cost or benefit measure. However, expected overall benefits are highly significantly impacted by firm size and the number of quality management systems certified, while actual overall benefits only by firm size. Finally, the study also finds considerable discrepancies between expected and actual costs and benefits. The managerial implications of the findings are discussed.
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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 | 0.000 |
| Open science | 0.001 | 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 it