Bibliographic record
Abstract
During his time in Ottawa as member of Parliament for the North west Territories, Wally Firth used to carry a compass in his pocket.Every so often during a political discussion, he would take it out and stare at it.When challenged to explain what he was doing, Firth would say, "Just checking to see which way is north."That love of his northern homeland, that deep sense of the North's distinctiveness, was something Firth never failed to communicate.He understood very well that many of his southern counterparts saw the Arctic as barren and remote and empty.As Firth's campaign manager for his upset win in 1972 (he was the first Indigenous politician from the North to gain a seat in the House of Commons), I learned much from him.Firth had little formal education, but in his forty years he had lived through enormous change.In his work as a trader for the Hudson's Bay Company, as a radio "pronouncer" for the CBC, and as an organizer and pilot for the Indian-Eskimo Association of Canada, he had been a leader in many of those changes.National leaders like to drone on about "the northern identity" and "the Arctic character, " but what exactly are they talking about?Over the past several generations, communities around the circumpolar North have undergone major transformations.Northern residents have lived through the Cold War, decades of Indigenous land rights struggles, the booms and busts of resource megaprojects, environmental and social
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.614 | 0.378 |
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".