Sociology in Global Environmental Governance? Neoliberalism, Protectionism and the Methyl Bromide Controversy in the Montreal Protocol
Bibliographic record
Abstract
Sociological studies of global agriculture need to pay close attention to the protectionist aspects of neoliberalism at the global scale of environmental governance. With agri-food studies in the social sciences broadening interrogations of the impact of neoliberalism on agri-food systems and their alternatives, investigating global environmental governance (GEG) will help reveal its impacts on the global environment, global science/knowledge, and the potential emergence of ecologically sensible alternatives. It is argued here that as agri-food studies of neoliberalism sharpen the focus on these dimensions the widespread consequences of protectionism of US agri-industry in GEG will become better understood, and the solutions more readily identifiable. This paper illustrates how the delayed phase out of the toxic substance methyl bromide in the Montreal Protocol exemplifies the degree to which the US agri-industry may be protected at the global scale of environmental governance, thus prolonging the transition to ozone-friendly alternatives. Additionally, it is clear that protectionism has had a significant impact on the dissemination and interpretation of science/knowledge of methyl bromide and its alternatives. Revealing the role that protectionism plays more broadly in the agriculture/environmental governance interface, and its oftentimes negative impacts on science and potential alternatives, can shed light on how protectionism can be made to serve ends that are at odds with environmental protection.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.030 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.010 | 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".