Environmental Regulations and Trade Patterns in Hazardous Waste: Facility-level Analysis
Bibliographic record
Abstract
This paper offers a fresh look at the pollution haven hypothesis (PHH) in the context of the waste management industry. Unlike previous research examining trade in waste products, the present study distinguishes between waste destined for final disposal and waste destined for recovery. Furthermore, it combines very disaggregated data with the highly flexible mixed logit model and a reliable measure of environmental policy stringency. Including all those elements in one analysis allowed for the uncovering of the dramatic differences in the reactions of waste generators to the environmental policy stringency of the destination country, depending on the treatment option their waste is slated for. Although there is no evidence confirming the PHH, a significant pollution haven effect has been found. This effect is apparent in the case of waste destined for final disposal. In contrast, facilities exporting waste for recovery are often attracted by the stringency of environmental policy.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 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".