Bibliographic record
Abstract
Canada's oceans offer important economic, socio-cultural and recreational opportunities that have shaped the country's history and identity. However, this growth is resulting in increased pressure through congestion, environmental degradation and ecosystem imbalances, which threaten the basis for future sustainable growth and in many areas, the biodiversity and ecological integrity of marine ecosystems are being threatened. The increased activity on, in and below our oceans is also manifesting conflicting usage issues that are not only shaping public and therefore policy agendas but is also leading to critical policy pressures that are demanding integration and multi-dimensional rationalization. In Canada there is a multitude of policies, regulations and legislation that bear on the management and development of ocean resources. There are those that direct and control fisheries and other harvesting activities; policies that regulate marine transportation; policies and regulations that direct seabed and subsurface exploration; laws and regulations for recreational use and a plethora of other policies that impact on our ocean resources. This paper examines the evolution of ocean policy in Canada, and describes a mosaic of mostly vertically oriented policies that is shared by other maritime nations and explores recent developments in the ocean policy forum.
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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.015 |
| Science and technology studies | 0.014 | 0.004 |
| Scholarly communication | 0.009 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".