Canadian Liberals face 'Fortress Toronto' challenges
Bibliographic record
Abstract
Significance Last month’s unexpected by-election defeat in a historically strong Liberal constituency in the Toronto area indicates that few Liberal seats are now safe from a Conservative challenge. Some in the Liberal Party are now asking whether fighting the next election with a new leader might stave off a heavy loss. Impacts The party’s refusal to hold a meeting of all Liberal MPs to discuss the by-election loss will not mute disquiet in the parliamentary party. Trudeau will feel pressure at this week’s NATO summit in Washington over what many members see as Canada's poor record on defence spending. Three more by-elections are already pending after the resignations of two Liberal MPs and one NDP MP; another Liberal departure is likely.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.039 | 0.009 |
| Scholarly communication | 0.013 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.009 | 0.008 |
| Insufficient payload (model declined to judge) | 0.037 | 0.003 |
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".