The modulation of sustainability knowledge and impulsivity traits on the consumption of foods of animal and plant origin in Italy and Turkey
Bibliographic record
Abstract
Given the environmental challenge we face globally, a transition to sustainable diets seems essential. However, the cognitive aspects underlying sustainable food consumption have received little attention to date. The aims of this cross-cultural study were: (1) to explore how impulsivity traits and individuals' knowledge of food environmental impact influence their frequency of consumption of animal- and plant-based foods; (2) to understand the modulation of individual characteristics (i.e. generation, sex, BMI, and sustainability knowledge). An online survey investigating impulsivity traits, sustainability knowledge and ratings of diverse food items was designed and administered to respondents from Italy (N = 992) and Turkey (N = 896). Results showed that Turkish respondents were higher in impulsivity and animal products consumption. Italians, instead, had greater sustainability knowledge and consumed more plant-based foods. Females in both groups reported greater knowledge of sustainability, consistent with previous findings. In terms of generations, the lowest consumption of animal products was reported by Turkish Generation Z and Italian Millennials. In conclusion, this study shed light on the interaction of psychological factors and individual characteristics with the perceived environmental impact of foods. Moreover, the adopted cross-cultural approach allowed to identify several differences in participants' responses ascribable to their different nationalities and gastronomic cultures.
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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 | 0.000 | 0.001 |
| 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) | 0.001 | 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".