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Record W4287679065

NEW OPPONENT’S FACE_CARICATURES ABOUT USSR IN CANADIAN POLITICAL DISCOURSE (1945-1953)

2020· article· en· W4287679065 on OpenAlexaboutno aff
Tkachenko Vadym Oleksiiovych

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsnot available
Fundersnot available
KeywordsFace (sociological concept)PoliticsAdversaryPolitical scienceMedia studiesSociologyLinguisticsComputer sciencePhilosophyLawComputer security
DOInot available

Abstract

fetched live from OpenAlex

The end of the World War Two had marked a significant change in the foreign relations balance, especially in the role and the number of the major powers which included for that moment USSR and USA which led to the Cold War start. It is questionable and scientifically interesting to reveal how the Canadian attitude to the later-Stalinist Soviet Union had changed from mostly allied to mostly hostile. Using the visual history approach among with the discourse studies, the author studied how this relation change had occurred using the caricatures as the primary sources. The article concludes that the change in the attitude was slow and was speeded by first Cold War conflicts and tensions which all were reflected, especially like the Korean War. The author also connects these transformations with the internal changes like the Gouzenko Affair and the change of leadership. In the same time, it is stated that negative connotation and portraying of the USSR as an aggressor were done without trying to humiliate the Soviet State, viewing the Cold War as a result not only of the East aggressive policies, but also of the West

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)0.003
metaresearch head score (Gemma)0.006
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.180
Threshold uncertainty score0.951

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.006
Science and technology studies0.0380.018
Scholarly communication0.0140.003
Open science0.0020.003
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0090.000

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 head0.221
GPT teacher head0.540
Teacher spread0.319 · 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
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueDOAJ (DOAJ: Directory of Open Access Journals)→Same topicCanadian Identity and History→French-language works237,207→