Review of <i>Greener Pastures: Decentralizing the Regulation of Agricultural Pollution</i>. By Elizabeth Brubaker
Bibliographic record
Abstract
Greener Pastures chronicles the proliferation of intensive hog production in Canada. Exploring the history of right-to-farm legislation, Elizabeth Brubaker focuses on the experiences of Manitoba, New Brunswick, and Ontario, although parallel situations may be found throughout the country. Starting with Manitoba's notorious 1976 Nuisance Act, which paved the way for similar industryshielding legislation in all other provinces, this book follows the devious evolution of laws that protect barn operators from environmental and public health liabilities, erode citizens' rights to seek relief and compensation through the judicial system, and remove decision-making powers from the communities that will be most affected. The treatise is richly illustrated with representative legal cases and their unsatisfactory outcomes, yet the accounts of pollution are comparatively restrained: even more distressing examples could be cited, there being so many from which to draw.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.009 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".