EVALUATION OF MANAGEMENT EFFECTIVENESS AT THE SAGUENAY–ST. LAWRENCE MARINE PARK, QUÉBEC, CANADA: A CASE STUDY
Bibliographic record
Abstract
with the support of the Commission for Environmental Cooperation (CEC) and other organizations, developed a tool to assess and monitor management effectiveness of marine protected areas (MPAs). This type of performance evaluation aims to help managers demonstrate and monitor long-term positive impacts of marine protected areas on biodiversity as well as on the well being of local human communities. The implementation of this approach has been field tested world-wide in eighteen MPAs, the majority of which are located in tropical or subtropical environments. Saguenay–St. Lawrence Marine Park is one of three high-latitude pilot sites and we wish to report on results of this management effectiveness evaluation study. The 1,138 km2 Saguenay–St. Lawrence Marine Park consists of a large estuary linked to a deep inland fjord. A strong upwelling of nutrient-rich arctic water favours a very high concentration of euphausiids, one of the basic links of the marine food chain. A resident population of endangered beluga whales as well as summer visiting minke, fin and blue whales, are major components of the ecosystem. Multiple uses of the MPA comprise, among other activities, commercial and recreational fishing, scientific research, commercial
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".