Governing the Sulphur Dioxide Emissions of Multinational Corporations: Putting the Breaks on the Race-to-the-Bottom
Bibliographic record
Abstract
Multinational corporations are now part of global politics. For effective governance of international environmental problems, their roles in the political process cannot be ignored. This paper will examine “race-to-the-bottom” theory and evaluate whether this race has occurred as a reaction to sulphur dioxide (SO2) regulation, resulting in a need for increased global governance surrounding environmental issues. The paper focuses on SO2 because the Trail Smelter case, which is seen as the birth case for international environmental law, recognized the harm stemming from this pollutant in 1941; scientific evidence has also linked SO2 emissions to acid rain and respiratory problems associated with smog, and advancements have been made in regulating the compound. However, despite the advancements that have been made in regulating SO2 pollution in Canada and in other developed nations, global SO2 emissions have risen. Given the academic support for the race-to-the-bottom theory, the global nature of multinationals, and transboundary harm resulting from air pollution, a new international structure is needed – one that looks at environmental problems from an issue-level, and one that includes multinational corporations in relevant decision-making processes. This topic is timely given the complex questions that surround environmental regulation of multinational corporations when dealing with air pollution. Given the state of scientific knowledge about the movement of air pollution and the harm stemming from compounds released into the air, it is imperative that this issue be examined. Specifically, the increasing importance of the regulation of greenhouse gases associated with global climate change necessitates such a study. The race-to-the-bottom associated with SO2 and the ineffectiveness of multinational regulation at the global level highlight the need to rethink future global atmospheric policy. The paper will begin with a case study on SO2 that explores the history and regulation of the compound. I will examine regulation at the international and domestic levels, and then explore how global smelting operations and SO2 emissions have shifted into the developing world. My evidence weakly indicates a shift, but does show that global emissions have not decreased despite increased regulation. I will then discuss the race-to-the-bottom theory, environmental regulation in general, and new international approaches to the problem. In conclusion, I propose that environmental regulation needs to occur at the global level and from an issue perspective. In order to be effective, this decision-making process should include various stakeholders, including multinational corporations.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".