Bibliographic record
Abstract
Theory is fine, but practical experience is the heart of real learning. This chapter provides—as much as a book can—some real-life experience through seven case histories of how wastes are managed. The case histories describe a state-of-the-art materials recycling facility, five waste disposal facilities in three different countries (the United States, Canada, and Sweden), and a large mass-burn incinerator. Choosing which of the many thousands of landfills in existence to include was a difficult task. Three municipal solid waste landfills are described. The first, Fresh Kills landfill in New York City, was constructed in 1948 and represents older landfill technology. The second, a new landfill in East Carbon County, Utah, was built in 1992 and incorporates the latest engineered barriers and features of a modern landfill. The third is being developed in a large, abandoned open-pit mine in California. In addition, we discuss a landfill and treatment center for hazardous waste, located in Swan Hills, Alberta. A unique Swedish facility for disposing radioactive wastes rounds out the suite of landfill case histories; this facility takes a very innovative approach to waste disposal and is included to provide a different perspective on this topic. Materials recovery facilities (MRFs) are the vital heart of modern integrated municipal waste management systems. Without MRFs, recycling on any practical scale would not be possible; it is here that recyclable materials are collected and made ready for sale to secondary markets. One of the most innovative recycle centers in North America has recently been constructed in the city of Guelph in southern Ontario (Guelph, n,d.). It offers good insight into what can be achieved through recycling, and the equipment that is involved. The city of Guelph, with a population of 95,000, is situated about 60 kilometers west of Toronto. In the mid-1980s, the city began studying ways to reduce the amount of waste being placed in its landfill. These studies received a major impetus in 1991, when the province of Ontario developed a waste reduction plan that required municipalities to reduce the amount of garbage being placed in landfills by 50% by the year 2000. A number of pilot studies were conducted before the present approach was selected.
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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 | 0.005 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.169 | 0.031 |
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".