A Failing Grade for Our Efforts to Make Our Civilization More Environmentally Sustainable
Bibliographic record
Abstract
In the decades to come, the authors expect growing pressures to reform current production systems to make them more compatible with the biosphere. A proactive approach to this pressure involves consideration of an alternate value chain based on a comprehensive engineering and marketing approach to recover value from end-of-life products. To estimate the potential advantages of the new value chain, the authors calculate the minimum throughput advantages and environmental advantages that can be realized from a comprehensive strategy of recovering value from end-of-life products. The efforts of corporations and other organizations to make modern ways of life more environmentally sustainable are evaluated against this benchmark in terms of activities in the area of selling services, product take back, life cycle assessment, Responsible Care, voluntary emission reduction initiatives, and engineering and management education. It is concluded that in general, these efforts make only a minor contribution toward achieving.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.010 |
| Scholarly communication | 0.015 | 0.010 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.005 | 0.012 |
| Insufficient payload (model declined to judge) | 0.027 | 0.012 |
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".