Public awareness and perceptions of ocean plastic pollution and support for solutions in the United States
Bibliographic record
Abstract
We conducted a nationally-representative survey of United States (U.S.) adults (n=1,960) in 2021 to gather insights on the knowledge, perceptions, and concerns about threats to the ocean, with a specific focus on plastics and microplastic pollution. Responses from the U.S. adult survey group were compared to a group of highly-engaged, Ocean Conservancy members who are very attuned to ocean issues (n=882). Ocean Conservancy is a U.S.-based nonprofit environmental advocacy group working to protect the ocean from today’s greatest challenges. Plastic pollution was the primary ocean concern identified by both U.S. adults and Ocean Conservancy members, surpassing eight other threat categories including oil spills, chemical and nutrient pollution, and climate change. Broad concern was reported for both study groups about the impacts of ocean plastics on marine wildlife, with human health and coastal community impact concerns being less prominent. About half of U.S. adults and 90% of Ocean Conservancy members had heard of microplastics. Both study groups indicated widespread support for microplastic pollution prevention measures in the U.S. and believed industry to be most responsible for taking action to address it. Ocean Conservancy members were generally better informed and more concerned about plastic pollution impacts and microplastics than U.S. adults and reported significantly greater levels of personal action to reduce their plastic footprint when compared to U.S. adults. In general, U.S. adults reported a willingness to refuse single-use plastics, but less frequently brought personal food containers to restaurants for takeout, or contacted local representatives or businesses about reducing plastic waste and pollution. Overall, our survey results provide new insights about public understanding of ocean threats and plastic pollution, willingness to participate in individual plastic-reduction actions, and support for needed solutions.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".