MétaCan
Menu
Back to cohort
Record W3217528212 · doi:10.21810/jicw.v4i2.3068

National Security and Parliamentary Review Four Years On

2021· article· en· W3217528212 on OpenAlexvenueaboutno aff
David J. McGuinty

Bibliographic record

VenueThe Journal of Intelligence Conflict and Warfare · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicMilitary and Defense Studies
Canadian institutionsnot available
Fundersnot available
KeywordsPresentation (obstetrics)National securityPolitical scienceExecutive committeeExecutive directorPublic administrationLibrary scienceMedia studiesLawManagementSociologyMedicineComputer science

Abstract

fetched live from OpenAlex

On July 15, 2021, the Canadian Association for Security and Intelligence Studies (CASIS) Vancouver hosted a digital roundtable titled National Security and Parliamentary Review Four Years On: Is it Working? The presentation was conducted by the Honourable David J. McGuinty, founding chair of the National Security and Intelligence Committee of Parliamentarians (NSICOP). The presentation was followed by a question and answer period with questions from the audience and CASIS Vancouver executives, which were directed to both Mr. McGuinty and Lisa Marie Inman, Executive Director, Secretariat of NSICOP.

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)0.034
metaresearch head score (Gemma)0.070
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 score0.046
Threshold uncertainty score0.180

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0340.070
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0110.008
Science and technology studies0.0030.002
Scholarly communication0.0070.003
Open science0.0030.004
Research integrity0.0070.005
Insufficient payload (model declined to judge)0.0240.012

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 head0.070
GPT teacher head0.349
Teacher spread0.279 · 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
Published2021
Admission routes2
Has abstractyes

Explore more

Same venueThe Journal of Intelligence Conflict and WarfareSame topicMilitary and Defense StudiesFrench-language works237,207