Report and Analysis by Senex IGNATIEFF BUNGLE
Bibliographic record
Abstract
called “unprecedented ” by political sci-entists and “unhelpful ” and “bizarre ” by Ottawa-watchers and monarchists alike, Federal Opposition Leader Michael Ig-na tieff suggested that the Governor General’s time in office should be extend-ed. He went on to call for public involve-ment in the process of selection of her eventual successor, saying “we should have a public conversation in this coun-try about what kind of Governor General we want next.” “A cynical, destructive ploy, ” journal-ist Andrew Coyne thundered on his blog. “This is just outrageous. I cannot re-member any opposition party, ever, pol-iti cizing the appointment of a governor general. ” University of Toronto political scientist Peter Russell commented the intervention was “inappropriate, unhelp-ful and unwise... It makes it appear as if the Governor General is favored by his party and not the government and that’s the very wrong impression to create.” And an editorial in The Globe and Mail, the matinal caffeine of the chattering class, observed on May 4th that the con-sequence of Mr Ignatieff ’s action, includ-ing singling her out by race and gender, had been “to effectively and permanently compromise ” Mme Jean, making out the individual who might at any time be call-ed on to arbitrate a Con stitutional crisis
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.058 | 0.022 |
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".