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Record W2978820545 · doi:10.1177/0095327x19875490

Experiences May Vary: NATO and Cultural Interoperability in Afghanistan

2019· article· en· W2978820545 on OpenAlexaffabout
Bastian Giegerich, Stéfanie von Hlatky

Bibliographic record

VenueArmed Forces & Society · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicAnthropology: Ethics, History, Culture
Canadian institutionsQueen's University
Fundersnot available
KeywordsNorth Atlantic TreatyMultinational corporationPolitical scienceInteroperabilityCoherence (philosophical gambling strategy)GermanPolitical economySociologyLawGeographyComputer sciencePolitics

Abstract

fetched live from OpenAlex

This article examines the coherence of the North Atlantic Treaty Organization’s (NATO) coordinated military strategy during the war in Afghanistan. We argue that much of this coherence can be lost when decision makers adopt multinational strategic guidance that is then interpreted by different national contingents operationally. Different strategic and military cultures across troop-contributing countries may account for observed variation in operational outcomes, but better theoretical tools are needed to examine this phenomenon. Our aim is to further scholars’ understanding of how cultural variables can affect mission outcomes. This assumed effect of strategic and military cultures is explored empirically with reference to the Canadian and German Provincial Reconstruction Teams in Afghanistan, which formed part of the NATO-led ISAF operation.

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)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.987
Threshold uncertainty score0.114

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0130.013
Scholarly communication0.0050.005
Open science0.0010.007
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.025
GPT teacher head0.341
Teacher spread0.316 · 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.

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

Citations31
Published2019
Admission routes2
Has abstractyes

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