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Record W748525432

Советско-канадские отношения и имидж СССР в Канаде в 1964-1985 гг

2014· article· ru· W748525432 on OpenAlexaboutno aff
Бортникова Екатерина Игоревна, Чернышов Юрий Георгиевич

Bibliographic record

VenueИзвестия Алтайского государственного университета · 2014
Typearticle
Languageru
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsnot available
Fundersnot available
KeywordsMemoirNewspaperHistoriographyPublic opinionPoliticsHistorySet (abstract data type)Media studiesPolitical scienceLibrary scienceArt historySociologyLawComputer science
DOInot available

Abstract

fetched live from OpenAlex

In the article the complex research of the evolution of the USSR»s image in Canada under Leonid Brezhnev, Yuri Andropov and Konstantin Chernenko against the background of Soviet Canadian relations was conducted for the first time in Russian historiography. The authors make attempt to identify the characteristics of political and economic image of the USSR, as well as the image of Soviet culture and sport that existed in Canadian public opinion. The primary sources used for the research include the whole range of the following materials: the results of opinion polls conducted by Gallup Inc. in Canada that were never brought to scientific research before, lots of text and graphic data from libraries and archives of Canada original pages of federal and regional press, photos, newspaper caricatures. Also, memoirs were of great importance as a valuable primary source for the research. The nature of the tasks set in the paper determined the use of interdisciplinary approach to the study of the phenomenon of a country image that allows investigating the problem comprehensively and using the methods of other academic disciplines along with the traditional methods of history.

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)0.001
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 score0.792
Threshold uncertainty score0.413

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0030.003
Scholarly communication0.0030.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0090.002

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 head0.007
GPT teacher head0.209
Teacher spread0.201 · 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
Published2014
Admission routes1
Has abstractyes

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Same venueИзвестия Алтайского государственного университетаSame topicCanadian Identity and HistoryFrench-language works237,207