Competing narratives inhibit a circular economy for bio‐based plastic packaging: Insights from a social innovation lab study in Brazil, Canada, Poland and the UK
Bibliographic record
Abstract
Abstract Businesses are turning to bio‐based, compostable plastic packaging as a circular economy solution to global plastic pollution. However, there is a lack of proper waste management systems for collection and processing. Through an international research initiative, a social innovation lab was undertaken in Brazil, Canada, Poland and the United Kingdom to understand and address key barriers in closing the bio‐based plastic packaging loop. Based upon a qualitative data set of 100 stakeholder interviews and three phases of workshop activities in each country, a grounded model was generated to illustrate how competing views and actions are inhibiting a circular system for bio‐based plastic packaging. Key issues were the lack of end‐of‐life processing infrastructure, contamination in processing facilities and absent or ineffective regulation. A systemic approach that includes shared responsibility for infrastructure, simplified packaging design and materials and equitable regulation to reduce susceptibility to greenwashing can improve collaboration to meet circular goals.
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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 | 0.015 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.024 | 0.032 |
| Scholarly communication | 0.015 | 0.005 |
| Open science | 0.003 | 0.013 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".