The development of ballast water management in Canada: A critical analysis of the journey [graduate project].
Bibliographic record
Abstract
Non-indigenous species (NIS) and aquatic invasive species (AIS) create significant risks when introduced to foreign ecosystems. One of the many vectors facilitating the transport of NIS is ballast water, and as commercial shipping increases globally so too does the use of ballast water. Despite Canadian regulations and international guidelines put forth by the International Maritime Organization, ballast water has facilitated the introduction of several NIS to Canada. This paper seeks to analyze the development of, and identify gaps in, Canadian ballast water management, in the context of marine ecosystems. Although large-scale ballast water management in Canada began in the late 1980s, many management gaps have persevered through time, and put Canada’s coasts at risk of NIS introduction. Such management gaps include: intracoastal shipping; salinity issues associated with mid-ocean exchange and euryhaline species; vessels reporting ‘No-Ballast On Board’; lack of monitoring, and; issues surrounding political will. Additionally, ballast water regulations for the Canadian Arctic have not been thoroughly considered which represents a significant management gap, especially since the Arctic will continue to see an increase in warming and subsequently, commercial shipping in the future. Relevant case studies of ballast water-mediated introductions to marine ecosystems are also explored, including: European green crabs (Carcinus maenas) to Newfoundland; Chinese mitten crabs (Eriocheir sinensis) to the St. Lawrence River, and; copepods to the Pacific Northwest. Several recommendations for Canadian ballast water management are generated in order to protect Canada’s vulnerable marine ecosystems for generations to come.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.014 | 0.004 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| 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".