Determinants of Sustainable Food Consumption: A Meta-Analysis Using a Traditional and a Structura Equation Modelling Approach
Bibliographic record
Abstract
Based on a database of 16 empirical studies, this MASEM study aims to provide an overview of existing antecedents of sustainable food consumption within an integrative framework based on the TPB. Among the antecedents, Personal Norm, Attitude and Subjective Norm displayed strongest effects on Intention, followed by Beliefs, Perceived Behavioral Control and Ethical Concern, which were also within the scope of medium to large. As for the correlations of Behavior, Personal Norm, Attitude and Subjective Norm showed strongest effects, and the effects of Intention, Beliefs and Perceived Behavioral Control were also within the scope of medium to large. Results of the MASEM study indicate that both TPB and extended TPB models have statistically acceptable power in explaining the intention and behavior of sustainable food consumption, while a slight increase was made to the amount of explained variance of intention by adding Personal Norm to TPB. The results of our meta-analyses give readers an understanding of the magnitude and significance of relationships between antecedents and intention in the sustainable food consumption domain.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".