Trudeau's SNC-Lavelin Scandal is Hypocrisy 101
Bibliographic record
Abstract
On episode 79 of 'Unpacking the News' we explore the Big Questions: Did the Prime Minster or the PMO pressure'Jody Wilson-Raybould'to interfere with the fraud case against SNC-Lavalin? How deep is the rot of corporate cronyism in Canadian politics? And is there any truth to rumors that Justin Trudeau and Gerald Butts played in a Spin Doctors cover band while attending McGill in the early 1990s? Plus: a deeper look into Canada's opioid crisis, reflections on the 50th anniversary of a major event in the history of black liberation in Canada and the growing reality of gentrification in Montreal's Parc-Extension neighbourhood and how the residents of one of the country's poorest postal codes are fighting back. Featuring a roundtable conversation with McGill's 'The Daily' news editor Athina Khalid, Concordia's 'The Link' current affairs editor Savanna Craig and writer, comedian and activist John Hancham. This episode was recorded on February 8th and 20th, 2019.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.016 | 0.004 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.058 | 0.009 |
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".