The Science Framework for Implementing the Fisheries Protection Provisions of Canada's Fisheries Act
Bibliographic record
Abstract
Abstract In 2012, Canada's Fisheries Act was amended. New fisheries protection provisions provide for the sustainability and ongoing productivity of commercial, recreational, and Aboriginal fisheries. These provisions replace previous provisions that focused on fish habitats, and concerns have been expressed that the amended Act has lowered aquatic habitat protection. The science framework developed for implementation of the new provisions is based on the relationships between fisheries productivity and the response of habitats or populations to pressures, with pressures linked to specific classes of activities through pathways of effects models. The framework includes guidance on quantifying productivity, scales and types of impacts, establishing equivalence in offsetting, and managing risk. Risk of failing to achieve the intent of the fisheries protection provisions is only managed when impacts of activities have a net neutral or positive effect on fisheries productivity. This standard applies whether the evaluation of an activity is by self- or assisted assessment or a more comprehensive project evaluation. En el año 2012, el Acta Pesquera de Canadá fue enmendada. Las nuevas provisiones para la protección de pesquerías tienen como objetivo proveer sustentabilidad y productividad a las pesquerías comerciales, recreativas y nativas. Estas provisiones reemplazan varias de las anteriores que se enfocaban en el hábitat de los peces, y ahora se han suscitado ciertas preocupaciones en cuanto a que el acta enmendada reduce la protección de hábitats acuáticos. El contexto científico que se ha desarrollado para implementar las nuevas provisiones se basa en la relación entre la productividad pesquera y la respuesta de los hábitats o de las poblaciones a las presiones; presiones que a su vez se relacionan con tipos específicos de actividades mediante modelos de “rutas de efectos”. El contexto incluye guías de cómo cuantificar la productividad, tipos y escala de los impactos, establecimiento de equivalencias compensatorias y manejo del riesgo. El riesgo de que no se logren cumplir los objetivos de las provisiones de protección de las pesquerías, comienza a ser controlado sólo cuando el impacto de las actividades tiene un efecto neto neutral o positivo en la productividad pesquera. Este estándar aplica ya sea cuando la evaluación de la actividad es asistida o bien auto evaluación, o cuando se hace mediante un proyecto de evaluación más exhaustivo.
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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 | 0.084 | 0.082 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.016 | 0.009 |
| Science and technology studies | 0.015 | 0.016 |
| Scholarly communication | 0.026 | 0.007 |
| Open science | 0.009 | 0.008 |
| Research integrity | 0.019 | 0.012 |
| Insufficient payload (model declined to judge) | 0.011 | 0.003 |
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".