Bibliographic record
Abstract
Nunavut, ‘our land ’ in the Inuit language, is 2,000,000 sq. km. of treeless tundras, coasts, and islands occupying one-fifth of all Canada’s land area. C. 29,000 people, 85 % of them Inuit, make up the population. Most of the non-Inuit are short-term residents, e.g., teaching and technical staff. Caribou are important food in many areas, especially the south-west mainland where great herds migrate from south to north and back annually from their winter range. No less important is the land-fast sea ice on which Inuit hunt, travel, and camp for much of the year, and the floe edge rich in food species. The seas of Nunavut include a large portion of Hudson Bay, together with many straits, gulfs, channels, and part of the north-west Atlantic. The Northwest Passage creates problems – the American navy abuses Canadian public opinion regularly by insisting on rights of passage of its ships, notably submerged nuclear submarines. Canada ‘discovered ’ Nunavut and other far northern regions and their peoples in the early 1950s (Robertson 2000), but through the Cold War 'two solitudes ' existed. One was a Northern or Arctic policy centred on future technology (especially the extraction and transport of natural resources), economics, international law, military systems and strategies, and utopian fantasies. The other was the daily North of inadequate housing, alcohol problems, social welfare, racial discrimination, and,
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 | 0.000 | 0.001 |
| Science and technology studies | 0.014 | 0.007 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".