Policy options to reduce consumer waste to zero: comparing product stewardship and extended producer responsibility for refrigerator waste
Bibliographic record
Abstract
Today, over-consumption, pollution and resource depletion threaten sustainability. Waste management policies frequently fail to reduce consumption, prevent pollution, conserve resources and foster sustainable products. However, waste policies are changing to focus on lifecycle impacts of products from the cradle to the grave by extending the responsibilities of stakeholders to post-consumer management. Product stewardship and extended producer responsibility are two policies in use, with radically different results when compared for one consumer product, refrigerators. North America has enacted product stewardship policies that fail to require producers to take physical or financial responsibility for recycling or for environmentally sound disposal, so that releases of ozone depleting substances routinely occur, which contribute to the expanding the ozone hole. Conversely, Europe's Waste Electrical and Electronic Equipment (WEEE) Directive requires extended producer responsibility, whereby producers collect and manage their own post-consumer waste products. WEEE has resulted in high recycling rates of greater than 85%, reduced emissions of ozone-depleting substances and other toxins, greener production methods, such as replacing greenhouse gas refrigerants with environmentally friendly hydrocarbons and more reuse of refrigerators in the EU in comparison with North America.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.041 | 0.088 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.008 | 0.014 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.015 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".