Exploring the potential impacts of waste disposal sites on ocean ecosystem contamination in Newfoundland: a geospatial analysis and public perception study
Bibliographic record
Abstract
This study endeavors to identify historical (closed) and currently operational landfill/waste disposal sites in Newfoundland that might be environmentally sensitive. The primary focus is to understand the potential impacts of these sites on neighboring water bodies and ocean ecosystems. Through the utilization of geospatial analysis, this study examines how waste disposal sites in Newfoundland could possibly contaminate water bodies and ocean ecosystems. Additionally, the study assesses public perceptions concerning the ecological and human health implications of waste disposal sites on the surrounding environment. Employing a geographic information system and the multiple criteria decision-making model, this study assesses the influence of waste disposal sites on nearby water bodies and the ocean. By implementing an analytical hierarchical process, a variety of environmental factors such as soil composition, topography, groundwater vulnerability index, hydrogeology, land use, and land cover are systematically ranked to determine the environmental vulnerability of each waste disposal site. The outcome is presented through a vulnerability assessment map, which categorizes dumpsites based on their level of vulnerability—high, moderate, or low. Recognizing the potential of public engagement to bolster social justice and draw attention to pertinent issues, this study integrates a diverse group of stakeholders such as community members, town councilors, mayors, landfill managers, public health experts, environmental scientists and engineers, provincial government officials, recyclers, and waste disposal service providers. Interviews were conducted with these stakeholders to gain their perspectives on the potential impacts of waste disposal sites on ocean contamination in Newfoundland. From the transcribed interview data, multiple thematic areas pertaining to present waste management practices and the environmental and health ramifications of waste disposal sites were comprehensively identified.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".