Food values and heterogeneous consumer responses to nanotechnology
Bibliographic record
Abstract
Abstract Agricultural applications of nanotechnology are at a relatively early stage and little is known about consumer responses to the technology. Canadian consumer responses to food nanotechnology are examined through the lens of the Food Value Scale. Data from a survey of Canadian consumers are used to evaluate the relative importance of eleven food values to food purchase decisions. We find that taste, safety, nutrition, and price are among the most important food values to Canadians, however, consumers exhibit considerable heterogeneity with respect to the priority placed on these values. A discrete choice experiment (DCE) explores the effect of food values on choice behavior. The DCE is positioned as a sliced apple product with non‐browning and antioxidant‐enhanced features introduced through the use of nanocoating or a conventional coating method. Random parameters logit (RPL) and latent class models (LCM) confirm the existence of significant preference heterogeneity. The LCM identifies three classes of consumers: “supporters,” “doubters,” and “opponents” who differ in their reaction to nanotechnology and in the relative importance placed on food values such as naturalness, novelty, and convenience. The analysis shows that food values provide additional insights into consumers’ food choices and their attitudes toward novel food technologies.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".