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Record W2081916369 · doi:10.1177/0020702013493756

Explaining Canada’s practices of burden-sharing in the International Security Assistance Force (ISAF) through its norm of “external responsibility”

2013· article· en· W2081916369 on OpenAlexaffabout
Benjamin Zyla

Bibliographic record

VenueInternational Journal Canada s Journal of Global Policy Analysis · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicMilitary and Defense Studies
Canadian institutionsUniversity of OttawaGlobal Affairs CanadaInternational Development Research Centre
Fundersnot available
KeywordsNorm (philosophy)Political scienceContext (archaeology)Promotion (chess)Foreign policyBest practiceResponsibility to protectPublic administrationInternational securityPublic relationsPoliticsInternational lawLaw

Abstract

fetched live from OpenAlex

While Canadian burden-sharing practices within NATO in the 1990s are well documented, the data in the literature raise two central questions: (1) was the practice of Canadian burden-sharing a one-time event, or was it part of a larger pattern of practices? and (2) what factors motivated Canada to shoulder the burden to the extent that it did? This article studies the extent of Canada’s burden-sharing practices in the context of the International Security Assistance Force (ISAF) mission in Afghanistan. The article makes two arguments: first, Canada’s commitment to NATO continued to be strong post-9/11; second, Canada’s practices of sharing Atlantic burdens can be explained by its adherence to the norm of “external responsibility,” which guided its foreign policy by appealing to Canada’s humanitarian responsibilities to contribute at an extraordinary level to the promotion and maintenance of international peace and security.

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)0.004
metaresearch head score (Gemma)0.011
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.157
Threshold uncertainty score0.978

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0250.014
Scholarly communication0.0060.002
Open science0.0010.003
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0030.000

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 head0.028
GPT teacher head0.363
Teacher spread0.334 · 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
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

Citations9
Published2013
Admission routes2
Has abstractyes

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