Bibliographic record
Abstract
The Canadian general election of 2008 was not as much a victory for the governing party as it was a defeat for the opposition leader. The Conservative minority government of Stephen Harper elected January 23, 2006 was remarkably resilient; it was the longest uninterrupted minority government in Canadian history. This owed in no small part to the election of Stephane Dion as leader of the Liberal Party at the end of 2006. Dion is widely believed to have been elected because he was the second choice of most of the delegates. He spent most of his brief leadership fighting his adversaries within the party and had little time to prepare a strategy for taking down Harper. This was the opposite of what had occurred during the previous minority government of the Liberals under Paul Martin. From its election on June 28, 2004 until its defeat on November 28, 2005, Martin was ruthlessly shadowed by an official opposition under Harper that doggedly pursued the defeat of the government. On the other hand, Harper actively solicited the defeat of his government, which never happened. Harper was boxed in by a pledge of fixed election dates, which precluded an election before October 2009 without an awkward act of reneging on Harper's part. By the end of August 2008, Harper was apparently more eager to defeat Dion at the polls than he was reluctant to renege on his fixed election dates pledge, and the election was called for October 14.
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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 | 0.008 | 0.049 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.010 |
| Science and technology studies | 0.018 | 0.004 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.013 | 0.001 |
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".