Bibliographic record
Abstract
Unsustainable plastic production, use and mismanagement have resulted in increased plastic pollution in the environment threatening sustainability, especially in the tropics. Countries in the tropics have been disproportionally impacted by plastic pollution due to imports of plastic waste from developed countries, or because tropical Small Island Developing States have become overwhelmed by single-use plastics used widely in the tourism sector. However, plastic pollution is pervasive and is not just limited to the tropics. Plastic pollution has resulted in widespread environmental, economic and social impacts globally. Most plastics are derived from fossil fuels which contribute to climate change via greenhouse gas emissions, and plastic pollution also harms wildlife threatening biodiversity, thus placing enormous pressure on earth’s limited resources. Although downstream strategies to curb plastic pollution exist, they are infective in the face of increased upstream plastic production. Therefore, the international community has recognized that a more holistic approach is required to reduce plastic pollution. Current plastic production and waste generation are still outpacing existing plastic reduction regulations. This viewpoint shows why unsustainable global plastic production has resulted in increased global plastic pollution, including in the tropics, but also highlights how ambitious plastic pollution reduction policies can help transition towards a more sustainable plastics future.
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.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.014 | 0.002 |
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".