Ecological unequal exchange: quantifying emissions of toxic chemicals embodied in the global trade of chemicals, products, and waste
Bibliographic record
Abstract
Abstract Ecologically unequal exchange arises if more developed economies (‘core’) shift the environmental burden of their consumption and capital accumulation to less developed economies (‘periphery’/‘semi-core’). Here we demonstrate that human populations in core regions can benefit from the use of products containing toxic chemicals while transferring to the periphery the risk of human and ecological exposure to emissions associated with manufacturing and waste disposal. We use a global scale substance flow analysis approach to quantify the emissions of polybrominated diphenyl ethers (PBDEs), a group of flame retardants added to consumer products, that are embodied in the trade of chemicals, products and wastes between seven world regions over the 2000–2020 time period. We find that core regions have off-loaded PBDE emissions, mostly associated with the disposal of electrical and electronic waste (e-waste), to semi-core and peripheral regions in mainland China and the Global South. In core regions this results in small emissions that mostly occur during the product use phase, whereas in peripheral regions emissions are much higher and dominated by end of life disposal. The transfer of toxic chemical emissions between core and periphery can be quantified and should be accounted for when appraising the costs and benefits of global trade relationships.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".