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Record W7135992493

The Impact of the Murder of Alexander Litvinenko on British Policy towards Russia

2024· dissertation· cs· W7135992493 on OpenAlexaboutno aff
Klára Fomenková

Bibliographic record

VenueDigital Repository (National Repository of Grey Literature) · 2024
Typedissertation
Languagecs
FieldSocial Sciences
TopicCanadian Policy and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsPoliticsGovernment (linguistics)BachelorPeriod (music)Face (sociological concept)Event (particle physics)Security policy
DOInot available

Abstract

fetched live from OpenAlex

The bachelor thesis titled "The Impact of the Murder of Alexander Litvinenko on British Policy towards Russia" deals with the issue of British policy towards Russia in response to the murder of Alexander Litvinenko, which significantly cooled bilateral relations. The thesis focuses on the analysis of the security and diplomatic actions of the British government and their connection with economic strategies, which is interpreted through the theoretical framework of the thesis - the theory of Canadian political scientist Kalevi Holsti. Holsti's theory, which discusses the interaction of states' security and economic measures in the face of external threats, provides a guide to understanding the shape of the British response. To illuminate the context, an overview of the British policy towards Russia prior to the event is provided, as well as a detailed account of the life and tragic death of Alexander Litvinenko. The period of around one and a half year after the murder is examined to avoid the influence of other events on British policy. Based on the secondary literature studied and the primary sources available, the outcome of this thesis is an analysis of the British government's policy towards Russia in the wake of the incident and an assessment of the unevenness of the response across different...

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)0.001
metaresearch head score (Gemma)0.008
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: Empirical
Teacher disagreement score0.660
Threshold uncertainty score0.685

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.003
Scholarly communication0.0040.001
Open science0.0000.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.007
GPT teacher head0.291
Teacher spread0.283 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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