Beyond Affect and Cognition: Identification of the Informational Bases of Food Attitudes<sup>1</sup>
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Two studies were conducted to identify the informational bases of food attitudes. Study 1 was an exploratory study in which participants indicated the importance of food characteristics and emotional reactions for determining their attitudes toward a variety of foods. On the basis of a series of exploratory factor analyses, 5 informational bases of food attitudes were identified: positive affect, negative affect, specific sensory qualities, abstract cognitive qualities, and general sensory qualities. A second confirmatory study corroborated the appropriateness of this 5‐factor structure. Furthermore, the food‐specific attitude structure model was found to have better fit than a more traditional attitude structure model. The implications of these findings for attitude theory, understanding eating behavior, and changing food selection are discussed.
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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 | 0.000 | 0.000 |
| 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) | 0.000 | 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 it