The Effects of a Green Nudge on Municipal Solid Waste: Evidence from a Clear Bag Policy
Bibliographic record
Abstract
We explore the power of behavioral economic insights to influence the level of households' recycling and Municipal Solid Waste (MSW) by examining the effectiveness of a green nudge, the adoption of a Clear Bag Policy that was implemented in 2015 in a mid-size urban municipality in Canada. Using a Regression Discontinuity (RD) Design on universe administrative data, our analysis shows that this green nudge promoted recycling, and reduced both refuse and total MSW. While recycling increased by 15 percent, total MSW decreased by 27 percent overall between August 2015 and July 2017. Our results also demonstrate heterogeneity in response to a Clear Bag Policy across neighborhoods with varying socioeconomic indicators. Our findings suggest that green nudges can serve as effective policy instruments in devising future environment policies.
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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 | 0.000 | 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 | 0.001 |
| 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".