Public Perceptions of Marine Plastic Litter: A Comparative Study Across European Countries and Seas
Bibliographic record
Abstract
Marine plastic litter (MPL) is a growing global problem and its prevention requires public engagement and behavioral change. Statistics of public perceptions of MPL are scarce and hardly comparable due to varying definitions and interpretations of the concept. This study identifies and classifies relevant components of public perceptions of MPL based on a large-scale survey across eight European countries sharing three European seas (North Sea, Baltic Sea, and the Mediterranean Sea). High levels of concern about MPL were observed throughout the EU and water pollution and plastics in oceans were consistently ranked in the top four most worrisome environmental challenges of our time. Most of the respondents (70%) reported noticing MPL, which influenced knowledge and feelings of responsibility with regards to MPL. The general public held companies and consumers most responsible for cleaning up MPL. Self-responsibility to reduce MPL varies considerably across and within countries, with the highest scores being reported in Greece and the lowest in Netherlands. Public knowledge on the recyclability of plastics was low in all countries. At the marine region level, the lowest scores for concern, perceived consequences and personal responsibility to reduce the use of plastics were reported in the North Sea region, followed by the Baltic Sea region and the highest scores were recorded in the Mediterranean Sea region. Using these results, policy implications and possible intervention strategies are discussed, to improve and increase public awareness, understanding, engagement, and sense of responsibility to change lifestyles and purchasing behavior to prevent and reduce MPL.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".