Cultural and generational factors shape Asians’ sustainable food choices: Insights from choice experiments and information nudges
Bibliographic record
Abstract
Promoting sustainable diets is crucial for mitigating global greenhouse gas emissions. We investigated the potential for large-scale dietary shifts to address the impacts of climate change on agriculture and food through surveys and choice experiments in China, Japan, and Vietnam (n = 5,089). Our findings reveal that Asian consumers are largely unwilling to deviate from current dietary habits, particularly regarding the consumption of animal proteins. This reluctance persists despite significant preferences for environmental certification as a proxy for greater sustainability in food production, as expressed by wealthier and younger respondents. Information experiments demonstrate that altruistic messaging fails to induce change, and positive information about climate impacts weakens the influence of certification. However, self-enhancement framing, particularly effective with individuals aged 60 years and above, shows promise. Our findings provide valuable insights for researchers and policymakers seeking effective strategies to encourage sustainable diets, shedding light on challenges and potential avenues for successful intervention.
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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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".