Using Pro-Environmental Information to Modify Conservation Behavior: Paper Recycling and Reuse
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
In cases where market policy instruments (e.g., taxes and quotas) are impractical tools to induce conservation behavior, information campaigns may be a valuable option. We use a difference-in-differences strategy to estimate the effectiveness a signage campaign for inducing paper recycling and reuse behavior in computer labs. We find that the implementation of signage with pro-environment appeals increases the probability of conservation behavior (i.e., recycling or reuse) by approximately 13%, despite the fact that pre-treatment levels of paper recycling and reuse were already at approximately 85%. Our results suggest that pro-environment campaigns can be an effective conservation tool and may be an important policy instrument for policy makers to consider.
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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 | 0.000 |
| 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 | 0.002 |
| 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