Arctic Corridors and Northern Voices: Governing marine transportation in the Canadian Arctic (Ulukhaktok, Northwest Territories community report)
Bibliographic record
Abstract
Ship traffic in the Canadian Arctic nearly tripled between 1990 and 2015. Corridors have been mapped in the Arctic Ocean as part of the Low Impact Shipping Corridors Initiative co-led by Transport Canada, the Canadian Coast Guard, and Canadian Hydrographic Service. Low impact shipping corridors are the current framework for governing shipping in the Canadian Arctic. The intent of the low impact shipping corridors is to reduce the likelihood of marine incidents by providing predictable levels of service to mariners transiting the corridors. Identification of Inuit and northerners’ perspectives on the potential impacts of marine vessels on marine areas used for cultural and livelihood activities, and on community members, and the inclusion of Inuit and northerners’ voices in the development of potential management strategies for the low impact shipping corridors and Arctic marine transportation are key considerations in the current prioritization of the corridors. This report reflects opinions gathered through participatory mapping, focus group discussions, and interviews with Ulukhaktok community members who were identified by local organizations as key knowledge holders. Analyses were aimed at understanding Inuit and northerners’ perspectives on the potential impacts of marine transportation on local marine use areas and community members, and on identification of potential management strategies for the low impact shipping corridors and for Arctic marine vessels management. This report was validated by the research participants.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.005 |
| Science and technology studies | 0.012 | 0.002 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".