Environmental Change, Protest, and Havens of Environmental Degradation: Evidence from Asia
Bibliographic record
Abstract
This paper explores the relevance for the debate on “pollution havens” of two cases from the international political economy of Japan-Southeast Asia relations. It begins by suggesting that the typical focus of the pollution havens literature is too narrow, and concentrates instead on the broader question of the extent to which the environmental transformations associated with particular sectors influence their international siting patterns. The first case—the changes in Japanese FDI to Asia in the 1970s—demonstrates that Japanese firms and the Japanese state consciously attempted to relocate highly-polluting industry in order to escape anti-pollution protest in Japan. The second case—the effort to create in Asia and the Pacific an export-oriented industrial tree plantation (ITP) sector supplying regional pulp and paper markets—shows, somewhat counterintuitively, that political contestation related to the environmental problems caused by ITPs has encouraged Japanese companies to concentrate their tree planting activity not in Southeast Asia but in Australia.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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; both teacher heads agree on what is shown here.
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".