Issues in production, recycling and international trade: analysing the Chinese plastic sector using an optimal life cycle (OLC) model
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
There have been increasing pressures by governments and NGOs to restrict international trade in secondary material waste in the conviction that imports of these goods are in reality a disguise for waste dumping by the exporting country. Moreover, cheap imports of secondary material waste tend to crowd out the local recovery system leading to a domestic waste disposal problem. Alternatively, proponents of trade argue that a ban on secondary material waste leads to an inefficient use of resources resulting inevitably in higher economic and environmental costs, both in developed and developing countries. In this paper we set out to investigate if free trade in secondary material waste can support economic development and simultaneously reduce environmental degradation in a developing country and the conditions necessary for the trade to be permitted. In this study we focus on the trade in waste plastics in China. A life cycle model is formulated within an optimization framework and solved by non-linear programming methods. Preliminary results suggest that trade in waste plastics is both economically and environmentally advantageous but under a number of stringent conditions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 it