Nudging and boosting reasonable use of public products: two experiments from China
Bibliographic record
Abstract
Abstract Behavioral instruments have unique advantages in certain governance contexts for the reasonable use of public products. Drawing on bounded rationality, we compare two major behavioral instruments – nudging and boosting – and experimentally test their effectiveness in promoting reasonable use of public products. We select the default option (nudging) and future orientation (boosting) as specific instruments. In Study 1, we conduct a laboratory experiment and find that (1) both the default option and future orientation reduce free electricity usage; (2) the immediate effect of the default option is greater than that of future orientation, but its delayed effect is smaller; and (3) the combination strategy is more effective than any single intervention. In Study 2, we conduct a field experiment targeting reasonable use of public toilet paper and basically replicate the results of the laboratory experiment. These findings reinforce our confidence in the effectiveness of nudging and boosting and suggest the possibility of bridging behavioral science with governance theory.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 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 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".