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Record W4393970054 · doi:10.59848/20.1207.hv6n6

Conciliating International Defence Spending Targets and National Objectives

2020· article· en· W4393970054 on OpenAlexfundaboutno aff
Alain Veilleux

Bibliographic record

VenueHemisferio Revista del Colegio Interamericano de Defensa · 2020
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicDefense, Military, and Policy Studies
Canadian institutionsnot available
FundersCanadian Armed ForcesNorth Atlantic Treaty Organization
KeywordsPolitical scienceComputational biologyBiology

Abstract

fetched live from OpenAlex

Most NATO nations remain under pressure to increase national defence budgets, although this would be unlikely to improve significantly the Alliance response and deterrence capability. In the context of likely post-COVID 19 fiscal constraints, pressure should shift to meeting existing personnel requirements and increased participation towards more targeted and efficient contributions, along the lines of the “four-thirties” plan. While Canada has committed to increase defence spending with a view to continue to be a valued NATO partner as well as a committed international actor in uncertain times, the Canadian defence budget also balances responsibilities at home and in North America. While the larger countries will continue to assume the bulk of burden-sharing, unity, purpose and resilience of NATO will outweigh smaller country commitment to defence spending against GDP.

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)0.009
metaresearch head score (Gemma)0.024
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.032
Threshold uncertainty score0.063

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.024
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.003
Science and technology studies0.0010.001
Scholarly communication0.0080.003
Open science0.0010.003
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0060.002

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 head0.045
GPT teacher head0.263
Teacher spread0.218 · 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 designTheoretical or conceptual
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
Published2020
Admission routes2
Has abstractyes

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