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Record W3010271960

Komparativní analýza bezpečnostní politiky Kanady a České republiky ve vztahu k misi ISAF - od motivace po exit

2014· dissertation· cs· W3010271960 on OpenAlexaboutno aff
Karolina Křížová

Bibliographic record

VenueDigital Repository (National Repository of Grey Literature) · 2014
Typedissertation
Languagecs
FieldSocial Sciences
TopicBorder Security and International Relations
Canadian institutionsnot available
Fundersnot available
KeywordsPolitical science
DOInot available

Abstract

fetched live from OpenAlex

This work focuses on approach of security policy toward foreign missions and interventions. I focused on the application of the theory of comparative analysis in the social sciences . The aim of this work is to analyze the development of security policies in Canada and the Czech Republic in relation to the ISAF mission in Afghanistan. Across-case comparative research metho emphasising the contrast of context separated the timeline of my work into two period: 2001-2006 and 2006-2014 . This paper examines the official positions of the Government of Canada and the Czech Republic as different context's members within the North Atlantic Treaty Organization . The data I worked with using techniques text-by-text, completed by point-by-point scheme. The idea is to demonstrate motivation of the States before joining the ISAF mission (2001) and the current reflection of the so-called exit strategy - only the Canadian ISAF mission has been terminated.. The result of this work is to understand the formation of security policy in the country from the Old continent as a new member of the NATO and long-term Alliance's member with different geographical and political environment. Different internal political developments in both countries had an influence on the shift in the priorities of the foreign.security...

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)0.002
metaresearch head score (Gemma)0.004
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 score0.979
Threshold uncertainty score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.003
Science and technology studies0.0020.003
Scholarly communication0.0060.004
Open science0.0000.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0110.000

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 head0.013
GPT teacher head0.288
Teacher spread0.275 · 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

Citations0
Published2014
Admission routes1
Has abstractyes

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