Solidarity after Bhopal: Building a Transnational Environmental Justice Movement
Bibliographic record
Abstract
This article documents the history of the U.S.-based campaign that emerged around the ongoing Bhopal disaster, since the 2001 merger of Union Carbide Corporation (Union Carbide) and the Dow Chemical Company (Dow). Based on interviews with key organizers and former and current campaigners in the United States and in Bhopal, the article discusses how this movement has worked to keep the Bhopal disaster alive and relevant for its three target constituencies in the United States. By appealing to social and environmental justice (EJ) groups, students, and the Indian diaspora, the campaign has won small victories in India and has challenged Dow's greenwashing attempts. Members of the diaspora have been instrumental in setting in motion what scholars have called the boomerang effect through exerting pressure on the Indian government. We also see the double boomerang at work in the United States when EJ activists make strategic references to Bhopal in times of crisis. More needs to be done, however, to build a sustained transnational EJ resistance to acknowledge the ongoing impact of toxics on people and their environments.
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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 | 0.006 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.036 | 0.021 |
| Scholarly communication | 0.011 | 0.009 |
| Open science | 0.002 | 0.031 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.006 | 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".