The Attitude–Behavior Relationship Revisited
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
The attitude-behavior relationship is of great import to many areas of psychology. Indeed, psychologists across disciplines have published thousands of articles on the topic. The majority of this research implies that the attitude-behavior relationship is linear. However, observations from 4,101 participants on Amazon's Mechanical Turk and 321,876 online reviews demonstrate that this relationship is systematically nonlinear. Across diverse topics, measures, and contexts, as attitudes move from extremely negative to extremely positive, the corresponding shift in behavior tends to be relatively flat at first (as attitudes move from extremely to moderately negative), to steepen when attitudes cross neutral and shift from negative to positive, and to taper off again as attitudes move from moderately to extremely positive. This result can be explained on the basis of research on categorical perception. The present research suggests a fundamental pivot in how researchers construe, study, and assess the attitude-behavior relationship.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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