Bibliographic record
Abstract
If you thought Bill C-51 was concerning, boy do we have an update for you! Bill C-59 is the Liberal government’s national security reform bill, and it covers a lot of ground. According to the University of Toronto’s Citizen Lab’s report, the potential activities allowed by Bill C-59 are “limited only by imagination”: Mass dissemination of false information, leaking foreign documents in order to influence political and legal outcomes, large-scale denial of service attacks, interference with the electricity grid… The report also warns that Bill C-59 contains a loophole which would allow the Communications Security Establishment (CSE) — the country’s spy agency focusing on electronic communications — to cause death or bodily harm, and to interfere with the “course of justice or democracy.” (*tugs collar* emoji) This follow-up to Bill C-51, the Harper government’s controversial anti-terrorism Act, is making its way through parliamentary committees, but has yet to draw similar national attention or scrutiny. But it’s not all bad. Bill C-59 also addresses institutional blindspots like lack of organizational oversight and accountability, and sheds some light onto the CSE's inner workings. Lex Gill, a researcher with Citizen Lab, says that only 3% of Canadians know what CSE is. Gill, along with fellow researchers, outlines over 50 recommendations for amendments to Bill C-59. To learn more, see their 75-page report. Lex Gill joins Jesse. — This episode of CANADALAND is brought to you by our newest sponsor PayTM.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.601 | 0.408 |
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".