Genetically Modified Food Market Participation and Consumer Risk Perceptions: A Cross‐Country Comparison
Bibliographic record
Abstract
As developing nations look to become more competitive in world agricultural markets, genetically modified (GM) crops are one avenue of pursuit. However, fears of primary export market loss, negative media attention, and adverse government regulations often hinder GM crop implementation and increase GM food risk perceptions among domestic consumers. In this study we analyze consumer surveys of GM food purchase propensity conducted in the developing countries of Romania and China. Through the examination of marginal effects and the drivers of purchase propensity, we find that in spite of demographic and psychographic similarities, consumer willingness to purchase GM foods is quite different between the two samples. Consumer preferences are largely dependent on risk perceptions, which are high in the Romanian sample, but low in the Chinese sample. Additionally, the effect of regressors on GM purchase propensity is invariant across foods in Romania, but distinctly different across foods in China, possibly due to the stated nutritional enhancement (vitamin A) in GM rice. Comme les pays en développement cherchent à devenir plus concurrentiels sur les marchés agricoles mondiaux, les cultures génétiquement modifiées (CGM) constituent une avenue. Cependant, la crainte de perdre les principaux marchés d'exportation, l'attention médiatique négative et les règlements gouvernementaux défavorables retardent souvent l'ensemencement de CGM et augmentent la perception des risques liés aux aliments génétiquement modifiés (AGM) chez les consommateurs nationaux. Dans la présente étude, nous avons analysé des enquêtes auprès des consommateurs sur la propension à acheter des AGM dans les pays en développement, notamment la Roumanie et la Chine. En examinant les effets marginaux et les facteurs de propension à acheter, nous avons trouvé que, malgré des similarités démographiques et psychographiques, la volonté des consommateurs à acheter des AGM variait considérablement dans les deux échantillons. Les préférences des consommateurs dépendent grandement de la perception des risques, qui était élevée dans l'échantillon de la Roumanie et faible dans l'échantillon de la Chine. De plus, l'effet des variables indépendantes sur la propension à acheter des AGM était invariant pour tous les aliments en Roumanie, mais distinctement différent entre les aliments en Chine, probablement en raison de l'enrichissement nutritionnel déclaré (vitamine A) du riz génétiquement modifié.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".