Oceans and human health—navigating changes on Canada’s coasts
Bibliographic record
Abstract
Ocean conditions can affect human health in a variety of ways that are often overlooked and unappreciated. Oceans adjacent to Canada are affected by many anthropogenic stressors, with implications for human health and well-being. Climate change further escalates these pressures and can expose coastal populations to unique health hazards and distressing conditions. However, current research efforts, education or training curriculums, and policies in Canada critically lack explicit consideration of these ocean–public health linkages. The objective of this paper is to present multiple disciplinary perspectives from academics and health practitioners to inform the development of future directions for research, capacity development, and policy and practice at the interface of oceans and human health in Canada. We synthesize major ocean and human health linkages in Canada, and identify climate-sensitive drivers of change, drawing attention to unique considerations in Canada. To support effective, sustained, and equitable collaborations at the nexus of oceans and human health, we recommend the need for progress in three critical areas: ( i) holistic worldviews and perspectives, ( ii) capacity development, and ( iii) structural supports. Canada can play a key role in supporting the global community in addressing the health challenges of climate and ocean changes.
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".