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Record W1538345295 · doi:10.1515/9780804786768

Military Adaptation in Afghanistan

2020· book· en· W1538345295 on OpenAlexaboutno aff

Bibliographic record

VenueStanford University Press eBooks · 2020
Typebook
Languageen
FieldSocial Sciences
TopicMilitary History and Strategy
Canadian institutionsnot available
Fundersnot available
KeywordsAdaptation (eye)AeronauticsPsychologyEngineeringNeuroscience

Abstract

fetched live from OpenAlex

When NATO took charge of the International Security Assistance Force (ISAF) for Afghanistan in 2003, ISAF conceptualized its mission largely as a stabilization and reconstruction deployment. However, as the campaign has evolved and the insurgency has proved to more resistant and capable, key operational imperatives have emerged, including military support to the civilian development effort, closer partnering with Afghan security forces, and greater military restraint. All participating militaries have adapted, to varying extents, to these campaign imperatives and pressures. This book analyzes these initiatives and their outcomes by focusing on the experiences of three groups of militaries: those of Britain, Canada, Denmark, the Netherlands, and the US, which have faced the most intense operational and strategic pressures; Germany, who's troops have faced the greatest political and cultural constraints; and the Afghan National Army (ANA) and the Taliban, who have been forced to adapt to a very different sets of circumstances.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.022
Threshold uncertainty score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0060.004
Scholarly communication0.0030.001
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0110.002

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 head0.046
GPT teacher head0.232
Teacher spread0.186 · 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 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

Citations50
Published2020
Admission routes1
Has abstractyes

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Same venueStanford University Press eBooksSame topicMilitary History and StrategyFrench-language works237,207