Food Carbon Labels and Purchase Decisions of Youth in the Americas: The Role of Cultural Values
Bibliographic record
Abstract
Consumer demand behavior may help make food systems more sustainable, and carbon labeling of food represents a nascent marketing tool that allows individuals to reduce their carbon footprint through their food choices. We surveyed representative samples of youth (18–24 years) from Canada (n = 397) and Argentina (n = 390) to determine the influence of cultural values on intention to use food carbon label information. Theoretical frames were an extended version of the Theory of Planned Behavior and individual-level constructs of the Hofstede’s Cultural Dimensions Theory. Structural equation modeling indicates that youth have a positive attitude toward purchasing carbon labeled food. Individualism vs. collectivism, masculinity vs. femininity, and long vs. short-term orientation indirectly influence behavioral intention, with environmental concern playing a pivotal mediating role. Findings inform green consumption theory and provide guidance for marketers and policymakers in designing effective interventions for promoting more sustainable food consumption among youth.
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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 | 0.002 | 0.003 |
| 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 | 0.000 | 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".