The Influence of Descriptive Social Norm Information on Sustainable Transportation Behavior
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
A month-long field experiment evaluated the impact of descriptive social norm information on self-reported reduction of private vehicle use. Following a baseline week, participants were asked to reduce their vehicle use by 25% and were randomly assigned to a control condition or to a low or high social norm condition in which they received information that either under- or over-reported others’ successful efforts to switch to sustainable transportation. Results indicated a significant linear trend, such that messages highlighting more prevalent descriptive social norms increased sustainable transportation behavior (relative to private vehicle use) for commuting, but not non-commuting, purposes. Participants in the high social norm condition decreased their commuting-related private vehicle use by approximately five times, compared with baseline. Car-use message campaigns can reduce private vehicle use by highlighting descriptive norms about others’ sustainable transportation efforts, but these messages appear to be most effective for commuting behavior.
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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