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Record W4255126621 · doi:10.24124/2009/bpgub604

The untold story: The role of the Department of Foreign Affairs and International Trade in Canadian foreign intelligence.

2009· dissertation· en· W4255126621 on OpenAlexafffundabout
Harjit S. Virdee

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldSocial Sciences
TopicIntelligence, Security, War Strategy
Canadian institutionsRoyal Canadian Mounted PoliceLibrary and Archives Canada
FundersForeign Affairs and International Trade CanadaUniversity of Northern British Columbia
KeywordsForeign policyIntelligence analysisWork (physics)Political sciencePublic relationsInternational relationsLawEngineeringPolitics

Abstract

fetched live from OpenAlex

Of the Canadian agencies involved in intelligence work, the Department of Foreign Affairs and International Trade (DFAIT) has tended to be overlooked. In fact, DFAIT acts as a collector, analyzer and disseminator of foreign intelligence. It is actively involved in foreign intelligence collection, participates in international intelligence sharing, and contributes to the Canadian intelligence-community. This thesis explores and highlights for the first time DFAIT's involvement in foreign intelligence work, albeit selectively, over the past sixty years.

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)0.003
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.122
Threshold uncertainty score0.888

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.005
Science and technology studies0.0410.023
Scholarly communication0.0180.008
Open science0.0020.004
Research integrity0.0040.009
Insufficient payload (model declined to judge)0.0100.001

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 head0.014
GPT teacher head0.288
Teacher spread0.273 · 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 designQualitative
Domainnot available
GenreOther

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
Published2009
Admission routes3
Has abstractyes

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