Marine Protected Areas in Canada with a particular Emphasis on Newfoundland: Science, Policy, and Implementation at Multiple Institutional Levels
Bibliographic record
Abstract
The primary goal of Marine Protected Areas is to conserve and protect part or all of a marine environment through legal or other effective means. MPAs are a global phenomenon that has become part of national level ocean policy and practice in such nations as Australia, Canada, and the US. Marine protected areas depend, for their success, on the development of an informal network of local policy and practice, which varies among communities. They succeed in circumstances where national policy or legal precedent does not dissolve local policy and practice, and where national policy facilitates and can accommodate local arrangements. The collapse of fisheries in the late 20th century in Canada provided the political impetus and policy framework that increased the capacity of the federal government to accommodate local arrangements in marine waters through Canada’s Oceans Act 1996. Two Marine Protected Areas, at Eastport and Gilbert Bay, were designated in Newfoundland and Labrador in 2005 under the Oceans Act, and a third, at Leading Tickles, is in the development stage. Eastport has a research program on lobsters in place, Gilbert Bay has a program on ‘golden cod’, but no research program existed at Leading Tickles. DFO Oceans began to collect data and worked closely with community members to develop research priorities, carry out research projects and develop management programs for each MPA. The provincial government was involved as members of the MPA steering committees, and local representatives provided input. Based on the political momentum for Marine Protected Areas, the second objective of this project was to identify internationally significant science questions for research within Newfoundland and Labrador. Recent research conducted by Memorial University at the Gilbert Bay and Eastport MPAs and the Leading Tickles Area of Interest (AOI) has been a mixture of descriptive and causal science directed at local issues arising within each of the three locations (two MPAs and one AOI). Past research helped to define the scope of some of the science problems in an informal way. This report takes the next step, which is to identify questions significant to both local issues and the understanding of coastal ecosystems by the national and international science community. Sound scientific evidence is needed to identify whether the intended effects are being achieved and to document accompanying effects. The emerging practice is initial science input followed by devolution of monitoring activities to local communities, with guidance from academic scientists. The effectiveness of these scientists would be increased by national initiatives to develop the capacity to guide locally based monitoring efforts. One potential model for science guidance is that used for environmental impact assessment, where monitoring activities are designed as tests of hypotheses concerning effects stated in an impact assessment.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.010 | 0.003 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".