What If Polluters Cannot Pay? : The Swedish Mining Bankruptcies – Problems and Proposals
Bibliographic record
Abstract
Over the last two decades, Sweden has suffered from a number of large mining businesses going bankrupt. An example is the Blaiken mine, where Scanmining, in 2000, got a permit to mine zinc, lead, and gold. Six years later, the mining started. The company was declared bankrupt after just sixteen months. Lappland Goldminers bought the mine but did not even manage to begin mining before it was declared bankrupt. The companies have left behind large open pits and thousands of tonnes of mine waste with no plan to deal with it. Instead, water has continued to flow through the mine area, leaking high levels of zinc into a nearby lake – causing severe environmental damage. The Blaiken mine is, unfortunately, not a one-of-a-kind case. According to the Swedish Environmental Protection Agency, as many as 324 contaminated mining sites in Sweden are classified as “very high or high risk” to human health and the environment. There is an extensive set of regulations on mining, both on the EU and national level. Operators of mines shall take measures necessary to prevent environmental damage. If damage nevertheless occurs, operators are obliged to remedy it according to the Swedish Environmental Act, which, in part, is an implementation of the Environmental Liability Directive. The directive and the European Union’s environmental policy are based on the principle that the polluter should pay. However, in the vast majority of cases, such as Blaiken, there is no money left in the businesses to mitigate environmental harm and remedy environmental damage. The polluter cannot pay, which short-circuits the environmental liability system. You could say that the environment has gone bankrupt. This article aims to explore and propose solutions that ensure that the polluter can pay, even if it goes bankrupt. We will use the Swedish mining industry and its regulation, which is mainly based on EU law, as a case study. We will start by providing an environmental background to identify typical environmental actions that require funding to prevent environmental hazards and to remediate the environment in case a mining company goes bankrupt. In this section, we will also delve into the polluter pays principle to explore how the polluter can, in principle, pay, even if it goes bankrupt. Then, we will explore solutions, focusing on priority, insurance, and security. While doing that, we will dip into Norwegian, Canadian, and American regulations as well as recommendations from the World Bank and Intergovernmental Forum on Mining, Minerals, Metals and Sustainable Developments (IGF).
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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 | 0.011 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.011 | 0.018 |
| Scholarly communication | 0.030 | 0.016 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.038 | 0.020 |
| Insufficient payload (model declined to judge) | 0.012 | 0.004 |
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".