Canadian Consumer Preferences Regarding Gene-Edited Food Products
Bibliographic record
Abstract
Innovations in food production and processing have largely remained "behind the scenes" for decades. The current nature of social media and calls for increased transparency regarding food results in a new landscape where consumer product demands are more important than ever, but are increasingly based on limited, or incorrect, information. One area where consumer awareness is rapidly emerging is the area of gene-edited food products. This article uses a consumer survey to gather perceptions regarding food safety, gene editing and willingness to consume for three gene-edited food products. Four factors were found to strongly influence consumer perceptions: trust in the Canadian food safety system; food technology neophobia scores; knowledge of genetics; and self-knowledge of gene editing. The survey of 497 Canadians found that 15% identified as neophobics and 12% as neophilics. The majority of participants identified as neutral. When presented with various food values, participants indicated that nutrition, price, and taste were the three most important values. A participants' willingness to consume gene-edited food products strongly correlated with neophobic and neophilic preferences, with neophobics unwilling to consume and neophilics being uncertain. The only food value that strongly affects consumer willingness to consume is the environmental impact of a products' production. Canadian consumers have a moderate to high level of trust in Canada's food safety system, but this level of trust fails to carry over to food products produced through innovative technologies; however, consumers express a higher level of trust in gene-edited technology than genetically modified technology.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 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".