A call to ban non-essential microplastics used in cosmetics, festival and holiday decorations
Bibliographic record
Abstract
Abstract Festivities, holidays and celebrations are often associated with unsustainability and high environmental impact. Examples include unsustainable overconsumption and waste during Christmas, Ramadan and during the Chinese New Years celebrations among many others. Microplastics (i.e., plastic fragments 5 mm) have also become a significant environmental concern during these periods. Common non-essential festive items like glitter, confetti, balloons and other decorations along with glitter used in cosmetic products contribute to microplastic pollution, potentially causing adverse effects on ecosystems and human health. Despite overwhelming evidence of the adverse impacts of microplastics on human and environmental health, how non-essential microplastics used in cosmetics, festival and holiday decorations will be addressed within the Global Plastics Treaty remains unclear. Although the draft Global Plastics Treaty text includes non-essential plastic items such as balloons and rinse-off microbeads in cosmetics, no other decorative or aesthetic use of microplastics have been included. Whilst the inclusions of non-essential plastics are commendable, we argue that further inclusions be made for non-essential microplastics used in cosmetics, festival and holiday decorations within the Global Plastics Treaty.
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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 | 0.007 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.021 | 0.013 |
| Insufficient payload (model declined to judge) | 0.035 | 0.012 |
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".