Podcast - Jody Wilson-Raybould, Michael Cohen and Kim Jong Un.
Bibliographic record
Abstract
Photo: (THE CANADIAN PRESS/Adrian Wyld)The Trudeau government's worst fears came true as the former Attorney General, Jody Wilson-Raybould, spoke of continual attempts to have her to change her decision to not interfere in the SNC-Lavalin court case. Guest: Duff Conacher, Cofounder of Democracy Watch, adjunct professor at University of Ottawa.JWR was not the only person on the stand yesterday. In the U.S., Michael Cohen spoke Congress to paint a picture of Donald Trump, calling him a con-man, a racist and a cheat. How did this play out?Guest: Laura Babcock. President, PowerGroup.The summit between Trump and Kim Jong Un has been called off. What happened?Guest: Mark Haichin, PhD Candidate in International Affairs - International Conflict Management and Resolution, Norman Paterson School of International Affairs, Carleton University, Ottawa
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.680 | 0.368 |
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".