Coastal and Ocean Management in Canada: Progress or Paralysis?
Bibliographic record
Abstract
Canada's experience with coastal and ocean management, which can be traced back over thirty years, is defined by short periods of intense and promising announcements separated by much longer periods of neglect. The Oceans Action Plan of 2005 promised real action to implement the Oceans Act of 1997, with the use of Large Ocean Management Areas that could provide a uniquely Canadian approach to integrated coastal and ocean management. In 2008, the Coastal Zone Canada conference reviewed the status of Canada's progress toward coastal and ocean management and found it wanting. The 2010 Coastal Zone Canada conference sounded a clarion call for urgent action to address the serious degradation of the world's oceans and coasts, being caused by over-exploitation of resources, pollution, and the impacts of climate change. This article analyzes the highs and lows of Canada's approach to ocean and coastal management, and concludes that despite a comprehensive and innovative federal legislative framework, and after the high hopes of the Oceans Action Plan, the picture has again slipped back to one of relatively little progress toward fulfilling the promise of the Canada Oceans Act.
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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.007 |
| Science and technology studies | 0.014 | 0.011 |
| Scholarly communication | 0.010 | 0.004 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".