From Precaution to Profit: Contemporary Challenges to Environmental Protection in the Montreal Protocol By Brian J. Gareau. Yale University Press. 2013. 384 pages. $55.00 (cloth)
Bibliographic record
Abstract
Brian Gareau's insightful From Precaution to Profit dives deep into a cavernous hole in what is widely considered to be the most successful international environmental treaty in history. Although the Montreal Protocol initiated the phasing-out of chlorofluorocarbons (CFCs) in the late 1980s, it has been less effective in curbing the use of methyl bromide (MeBr), a fumigant used for controlling pests in strawberry and tomato crops with deleterious effects on the ozone layer. According to Gareau, such ineffectiveness can be attributed to the rather dubious use of science by the agrochemical industry and the pursuit of “critical use exemptions” (CUEs) by the United States, which allow for extended use of the chemical if its elimination would generate unfair market disruptions (or, put simply, if the ban of MeBr would hurt the competitiveness of U.S. strawberry growers). However, the story is more nuanced than Big Bad Agrochemical steamrolling through the rather soft teeth of the Protocol in order to maximize profits. For Gareau, the controversy surrounding MeBr reveals a deeper challenge in the global effort to protect the environment—the countervailing pressures of neoliberalism that privilege market logics over precautionary ones and protectionist policies over global agreements.
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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 | 0.007 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.009 | 0.018 |
| Scholarly communication | 0.012 | 0.012 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.015 | 0.019 |
| Insufficient payload (model declined to judge) | 0.026 | 0.007 |
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".