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Record W3121588968

Bill C-59, an Act Respecting National Security Matters: What It Does and Why It Matters

2019· article· en· W3121588968 on OpenAlexaffabout
Michael Nesbitt, Leah West

Bibliographic record

VenueSSRN Electronic Journal · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Policy and Governance
Canadian institutionsCarleton UniversityUniversity of TorontoUniversity of Calgary
Fundersnot available
KeywordsNational securityOffensivePolitical scienceCivil libertiesPublic administrationLawPublic relationsSecurity serviceService (business)Computer securityInformation securityBusinessManagementPoliticsComputer scienceEconomics
DOInot available

Abstract

fetched live from OpenAlex

Forum Introduction to Special Edition of the Alberta Law Review on Bill C-59: An Act Respecting National Security Matters passed into law in June 2019. It is no exaggeration to say that this is the most wide-reaching and important update to Canada’s national security legal framework and organizational structure since at least 1984, when the Canadian Security Intelligence Service Act hived off the security and intelligence functions of the Royal Canadian Mounted Police (RCMP) to create the Canadian Security and Intelligence Service (CSIS). Among other things, the ATA 2017 created an entirely new oversight body in the form of the Intelligence Commissioner (IC), radically redesigned intelligence review, reformed and added new lines of operations for the Communications Security Establishment (CSE) including brand-new offensive and defensive cyber authorities, and made substantial changes to the breadth and scope of the information CSIS can collect. These changes will assuredly be both vital to the protection of Canadian national security and controversial with regards to the civil liberties of Canadians in the years to come.

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 imitation

Not 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.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.023
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.071
Threshold uncertainty score0.516

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.023
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0130.015
Scholarly communication0.0130.004
Open science0.0030.002
Research integrity0.0170.015
Insufficient payload (model declined to judge)0.0120.004

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.

Opus teacher head0.011
GPT teacher head0.287
Teacher spread0.276 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2019
Admission routes2
Has abstractyes

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