Canada's voluntary ARET program: Limited success despite industry cosponsorship
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
Abstract The Accelerated Reduction/Elimination of Toxins (ARET) Challenge was a voluntary program initiated in 1994 by the Government of Canada. Unlike the U.S. 33/50 Program, ARET involved industry partners in negotiation and cosponsorship of the program, with the intention that early involvement would yield stronger commitment to voluntary reductions. We review the program's self‐reported success in delivering emissions reductions. For 17 ARET substances that were also covered by Canada's National Pollutant Release Inventory, we employ treatment effects regressions to control for self‐selection bias. We find evidence that ARET accelerated emission reductions in five cases, slowed reductions in two cases, and had no discernible effect in ten cases. Industry cosponsorship apparently did not have the intended effect and instead resulted in program features such as data confidentiality that significantly undermined the program's credibility. © 2007 by the Association for Public Policy Analysis and Management
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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 | 0.001 | 0.001 |
| 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