Coastal and Indigenous community access to marine resources and the ocean: A policy imperative for Canada
Bibliographic record
Abstract
Access, defined as the ability to use and benefit from available marine resources or areas of the ocean or coast, is important for the well-being and sustainability of coastal communities. In Canada, access to marine resources and ocean spaces is a significant issue for many coastal and Indigenous communities due to intensifying activity and competition in the marine environment. The general trend of loss of access has implications for these communities, and for Canadian society. In this review and policy perspective, we argue that access for coastal and Indigenous communities should be a priority consideration in all policies and decision-making processes related to fisheries and the ocean in Canada. This paper reviews how access affects the well-being of coastal communities, factors that support or undermine access, and research priorities to inform policy. Recommended actions include: ensuring access is transparently considered in all ocean-related decisions; supporting research to fill knowledge gaps on access to enable effective responses; making data accessible and including communities in decision-making that grants or restricts access to adjacent marine resources and spaces; ensuring updated laws, policies and planning processes explicitly incorporate access considerations; and, identifying and prioritizing actions to maintain and increase access. Taking action now could reverse the current trend and ensure that coastal and Indigenous communities thrive in the future. This is not just a Canadian issue. Globally, the ability of coastal and Indigenous communities to access and benefit from the marine environment should be at the forefront in all deliberations related to the oceans.
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 | 0.010 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.016 | 0.008 |
| Scholarly communication | 0.011 | 0.005 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.007 | 0.009 |
| Insufficient payload (model declined to judge) | 0.008 | 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".