A Life Vest for Hudson Bay's Drifting Stewardship
Bibliographic record
Abstract
Hudson Bay, as the world’s second-largest inland sea, is far from insignificant. Yet, the Hudson Bay bioregion barely registers on the radar of Canadian ocean management. When it does, it almost invariably appears under a project-specific approach or within the strict parameters of jurisdictional responsibilities. However, Inuit in Sanikiluaq, from their standpoint on the Belcher Islands, see the surrounding marine environment as being largely unrelated to political boundaries and jurisdictions. From their perspective, stewardship means ensuring the sustained health of Hudson Bay and its marine life. We advocate concrete steps to bring compartmentalized governmental processes in line with this more comprehensive definition of marine environmental stewardship. A twofold course of action is needed. The first step is to make joint, complementary use of scientific and Inuit knowledge to understand the cumulative, transboundary effects on this Arctic marine ecosystem of natural and human-induced changes. Second, collaboration is greatly needed to unify the present fragmented coastal and marine governance in the eastern Canadian Arctic. We therefore propose establishing a community-based monitoring and assessment network and a cooperative, inter-jurisdictional stewardship body. Such a collaborative effort could make tangible progress toward sound, ecosystem-based, integrated management of the Hudson Bay bioregion.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.012 | 0.014 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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".