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Record W2061186870 · doi:10.1080/09644008.2014.916691

Lessons Learned? German Security Policy and the War in Afghanistan

2014· article· en· W2061186870 on OpenAlexaboutno aff
Arne Schröer

Bibliographic record

VenueGerman Politics · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicPolitical Conflict and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsGermanPolitical scienceEconomic historyEconomicsHistoryArchaeology

Abstract

fetched live from OpenAlex

The mission in Afghanistan revealed fundamental shortcomings, inconsistencies and contradictions of core elements of German security policy. In an effort to contribute to the debate about the factors that account for the idiosyncrasies of German security policy, the purpose of this study is to assess how far Germany learned lessons from its policy failures in Afghanistan. The study introduces a typology of learning, which is mainly based on the Advocacy Coalition Framework (ACF); delineates the German security policy belief system; and explores two prominent cases of policy failure: the deployment of the Bundeswehr and leadership of the international police training mission. Utilising different sources of data, the study confirms assumptions of the ACF about the stability of core beliefs and shows that the lack of precise policy objectives was a significant barrier to learning. Instead of clarifying Germany's strategic viewpoint, Afghanistan has further enhanced its disorientation in security policy.

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)0.005
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.044
Threshold uncertainty score0.087

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0050.007
Scholarly communication0.0050.004
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.000

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 head0.380
Teacher spread0.352 · 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

Citations12
Published2014
Admission routes1
Has abstractyes

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