Changes in Public Perception of Role of Waste-to-Energy for Sustainable Waste Management of MSW
Bibliographic record
Abstract
In the last ten years, public and government perceptions of waste-to-energy have changed considerably. Most people who bothered to visit waste management facilities recognize that landfilling can only be replaced by a combination of recycling and thermal treatment with energy recovery. During the same period, the Earth Engineering Center (EEC) of Columbia University research and public information programs have concentrated on advancing all means of sustainable waste management in the U.S. and abroad. The results of EEC research are exemplified in the graphs of the Hierarchy of Waste Management and the Ladder of Sustainable Waste Management of nations; in this paper, the latter has also been used to compare the waste management status of the fifty states of the Union. This paper also describes how the European Union has directed that thermally efficient treatment of MSW is equivalent to recycling. The rapid growth of WTE in this century is exemplified by the hundreds of new WTE plants that have been built or are under construction, most with, government assistance as in the case of other essential infrastucture. The need for concerted action by concerned scientists and engineers around the world has led to the formation of the Global WTERT Council. By now there are sister organizations of EEC and WTERT in Brazil, Canada, China, France, Germany, Greece (SYNERGIA) and Japan. Others are being formed in other countries.
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 | 0.008 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".