Consumers' Expectations on Transparency of Sustainable Food Chains
Bibliographic record
Abstract
The search for food products from sustainable chains has increased in the past years, motivated by consumers' interest in reducing the negative environmental, economic, and health impacts of their food choices. However, it is not yet clear whether transparency expectations of sustainable food chains influence in consumers' perception of this food products. The literature shows that there are gaps in the growth of sustainable product consumption is the transparency of production and the provision of more information to consumers. In this paper, we aimed to better understand what is the role of transparency expectations and how they influence consumers' decision to consume sustainable food products. Based on scales already validated in the literature, a theoretical model with nine hypotheses was proposed. A questionnaire was structured and empirically tested through a survey with 136 consumers of food from alternative networks. Six hypotheses were validated. Three segments of consumers target were identified from an exploratory factor analysis and cluster. Based on the results some marketing actions were suggested for the participants of alternative food networks. Other studies may validate the model proposed here.
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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 | 0.006 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".