Signaling sustainability: Do Canadian consumers prefer broad or narrow food sustainability labels?
Bibliographic record
Abstract
Abstract Sustainability labeling has been increasingly integrated into many food product labels in response to consumer interest in purchasing sustainably produced food. While a product label may contain the phrase “sustainably produced”, little additional information is available to consumers regarding how sustainability has been enhanced, or the dimensions of sustainability encompassed by the label. Using data from a survey of 1416 Canadian consumers, we examine consumer perceptions of sustainability and preferences for broad versus narrow sustainability claims across several contexts, including the dimensions of sustainability and the scope of a sustainability standard with respect to compliance criteria, product coverage, and geographical coverage. We find low levels of consumer knowledge and understanding of sustainability labeling, heterogeneity with respect to which dimension of sustainability appeals to different types of consumers, and a general preference for broad over narrowly defined sustainability labels, particularly with respect to the scope of criteria encompassed by the label. Our findings suggest some confusion as to what constitutes sustainability in the context of agri‐food, but that broader, more encompassing labels are likely to gain more traction with consumers.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".