Consumers’ food choices and the role of perceived environmental impact
Bibliographic record
Abstract
As the world population grows to a predicted 9 billion people by 2050, food availability and security should be considered, and the relationship between food production and consumers' selection of their food may influence the global agriculture system and perhaps the environment.In an altruistic sense, purchase of sustainable foods is strongly correlated with the measures of ethical self-identify, moral attitude, concern for environmental issues, and other measures of global concern.Additional analysis of values in relation to environmental purchasing and policy similarly found that intention to purchase environmentally friendly products is positively correlated with food and environmental concerns.While this ethical vision of making sustainable or organic food choices is often viewed as altruistic, it can also be viewed as an egoistic motivator, as it relates to personal identification as an ethical person.Food choice is driven by other egoistic values as well, including nutritious qualities, sensory qualities, and overall health effects of food purchases.Attitudes toward genetically modified foods, which are not organic and are viewed as non-environmentally friendly, has been correlated with decreased purchasing behavior, indicating that the tie between attitudes towards certain food production methods can predict actual purchasing.Current research examines the complex relationship between consumer knowledge and purchasing behavior relating to multiple food production methods, including organic, genetically modified, and conventional.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".