Review of Jamie Benidickson’s the Culture of Flushing: A Social and Legal History of Sewage
Bibliographic record
Abstract
Rarely have legal histories peered into the latrines of the 19th and 20th century. Fortunately, the view from within Jamie Benidickson's book, 'The Culture of Flushing: A Social and Legal History of Sewage', is informative and comprehensive. A reader looking for a full examination of the social and legal history of sewage in Canada, the United States and the United Kingdom will find it in this volume. Benidickson moves through 200 years of sewage history by focusing on key developments in our attitude and treatment of sewage in major urban centers, including Toronto, New York, Chicago, and London. He chronicles the early history of neglect and the prevailing attitude of streams as 'nature’s sewers' and how water came to become an acceptable medium for disposing urban and industrial waste. With clarity and insight, Benidickson traces the major court battles, and legislation culminating in the Clean Water Act of 1972. Each step in the murky legal and cultural history of waste disposal, including the legislative attempts, the arguments made in court, the judicial opinions issued at various stages of ongoing litigation is clearly summarized. The author also puts this legal history in the larger context of environmental degradation, national legislation, and changing cultural attitudes and norms of collective responsibility.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.009 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".