CONSUMER PURCHASE INTENTIONS FOR CERTIFIED FARM-RAISED ATLANTIC SALMON
Bibliographic record
Abstract
The occurrences of food safety incidents like polychlorinated biphenyls in farmed Atlantic salmon in Canada heightened public awareness causing significant reduction in the consumption of the product.This has induced policymakers and stakeholders to implement traceability systems as part of enhancing consumers' trust and safety in the industry.This study provides information on consumers' awareness about traceability systems of farm-raised Atlantic salmon and their willingness to pay for traceable product in the province of Newfoundland and Labrador, Canada.In this study, we used a logistic regression model to assess consumers' preferences for farm-raised Atlantic salmon.To estimate the parameters of the model, a telephone survey was carried out in fall 2018 over 200 consumers in the province.The results of the study showed that age of the respondents, education level, household size, and household consumptions were significant determinants of the Newfoundlanders and Labradoreans' willingness-to-pay a premium price for the farm-raised traceable salmon.Moreover, a shortage of public knowledge about the traceability systems was also observed in the empirical evidence.To increase the consumers' knowledge about the value of traceability system and its aspects, provincial authorities and private food companies need to take further initiatives.Providing detail labeling could be one of the suitable ways of communicating traceability to consumers.Besides, comprehensive monitoring by the competent authorities is also required to guarantee the truthfulness of traceable information and to reveal the food safety problems for enhancing the degree of consumer confidence in traceability systems. .
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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 | 0.001 | 0.002 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".