Sociodemographic drivers of waste management behaviors and public perceptions of environmental contaminants in coastal communities of Newfoundland, Canada
Bibliographic record
Abstract
This study investigates waste management behaviors and public awareness of persistent organic pollutants (POPs) like PBDEs and PFAS in coastal communities of Newfoundland, Canada. Protecting these unique environments requires responsible waste disposal practices. Using an integrated theoretical framework combining the Theory of Planned Behavior (TPB), the Value-Belief-Norm (VBN) theory, and the Norm Activation Model (NAM), we conducted a mixed-methods study employing a pretested survey with open- and closed-ended questions. Although a larger sample was planned, 86 adult residents completed the survey. Our analysis revealed significant differences in waste management behaviors across community types (cities, big towns, and small towns). For example, cities showed higher engagement in e-waste recycling (82%) compared to smaller towns (68%), while smaller towns were more consistent in composting (78% vs. 50% in cities) and hazardous waste disposal (χ 2 = 33.97, p = 0.0021). Higher education and income levels were positively correlated with increased recycling and proper waste disposal. However, despite a general awareness of environmental issues, knowledge of specific environmental contaminants was limited (45% for PBDEs, 33% for PFAS). These findings highlight the urgent need for targeted public education campaigns and improved waste management services tailored to the unique needs of diverse coastal communities. This study provides valuable insights for policymakers and environmental managers, emphasizing the importance of targeted interventions to promote sustainable practices and protect fragile coastal ecosystems. • Socioeconomic disparities and age influence coastal waste practices. • Limited awareness of specific chemicals despite general environmental concern. • Community-specific strategies improve waste management effectiveness. • Tailored interventions enhance waste management in coastal areas.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".