Bibliographic record
Abstract
I n a characteristically whimsical essay, written on his retirement from McGill University in 1936, and intended to mark the virtues of Can ada's disconnection from European geopolitics -"not for us the angers of the Balkans, the weeping of Vienna and the tumult of Berlin" -the English-born, Canadian-raised humorist Stephen Leacock identified an idea of the North as the source of Canadian distinctiveness:To all of us here, the vast unknown country of the North, reaching away to the polar seas, supplies a peculiar mental background.I like to think that in a few short hours in a train or a car I can be in the primeval wilderness of the north, that if I like, from my summer home, an hour or two of flight will take me over the divide and down to the mournful shores of James Bay, untenanted till yesterday, now haunted with its flock of airplanes hunting gold in the wilderness.I never have gone to the James Bay; I never go to it; I never shall.But somehow I'd feel lonely without it.1
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.320 | 0.243 |
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".