Marine plastic debris - exploring sources & transport in coastal British Columbia
Bibliographic record
Abstract
Plastic debris, which enters the marine environment through a variety of anthropogenic sources or means and can cause harm to marine species and ecosystems, is an increasingly urgent environmental problem. This research explored the marine plastic debris problem in coastal British Columbia (BC) through the following research question: “What are the source locations and ages of marine plastic debris, specifically plastic bottles, accumulating on Triangle Island and the central BC coast, and what might be their oceanic pathways to these points of accumulation?” Sampling sites range from south to north coast of BC. I found bottles from 27 countries (156 brands), from <1-17 years old. I compared inner and outer coast locations and found there to be a significant difference (χ2 (7, N = 2798) = 20.96, p = 0.004) in source countries of bottles. I used an open-source ocean circulation model to predict travel times from source locations via ocean current patterns. For bottles where I could identify both age and source country, 53% did not comply with the ocean circulation model, indicating arrival through expedited means such as disposal overboard ships. When comparing proportion of bottles that do not comply with ocean circulation model oceanic travel times between sampling locations, I found that sampling location was not a significant influencing factor (H(5) = 1.53, p = 0.91). There was no significant difference in age distributions between domestic and international bottles (Mann-Whitney U = 4334.5, N = 503, p = 0.76). Guided by these findings, I conducted a review of existing international plastic mitigation measures, focusing on where BC stands in a global context; priorities should be plastic end-of-life disposal accountability, strengthening domestic recycling regulations and international collaboration, addressing knowledge and inequality gaps in waste management research, and minimizing, where possible, virgin plastics creation.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".