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Record W2012216099 · doi:10.1177/0020702015572765

But who's flying the plane? Integrating UAVs into the Canadian and Danish armed forces

2015· article· en· W2012216099 on OpenAlexaboutno aff
Gary John Schaub, Kristian Søby Kristensen

Bibliographic record

VenueInternational Journal Canada s Journal of Global Policy Analysis · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicMilitary History and Strategy
Canadian institutionsnot available
Fundersnot available
KeywordsNorth Atlantic TreatyDanishTreatyAeronauticsState (computer science)Range (aeronautics)Political scienceOperations researchEngineeringLawComputer scienceAerospace engineering

Abstract

fetched live from OpenAlex

North Atlantic Treaty Organization (NATO) members such as Canada and Denmark have transformed their military forces to better engage in expeditionary warfare. They are incorporating advanced technologies to find and strike targets precisely from great distances at little risk to themselves. The persistence of unmanned aerial vehicles (UAVs) represents the next step in modern airpower's long-range reconnaissance/precision strike complex and has transformed ground operations. Nonetheless, operational requirements in Afghanistan caught Canada and Denmark flat-footed. Ultimately, Canada effectively used UAVs while Denmark could not. Moreover, neither state has a UAV capability beyond small tactical systems (although each has plans to develop or join in the development of larger ones). The Canadian and Danish experiences suggest that ground forces are most likely to acquire and integrate small UAVs into their force structures and concepts of operation and that the air forces of small- and medium-sized Western countries will likely do so only in cooperation with others. It is here that the Canadian and Danish UAV paths may yet again cross.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.404
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.022
GPT teacher head0.316
Teacher spread0.294 · 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 teacher head, not a consensus.

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

Citations4
Published2015
Admission routes1
Has abstractyes

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