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Record W2944256076 · doi:10.25071/1913-9632.39371

Looking for Avrom Yanovsky

2019· article· en· W2944256076 on OpenAlexvenueaboutno aff
David Frank

Bibliographic record

VenueLeft History An Interdisciplinary Journal of Historical Inquiry and Debate · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsnot available
Fundersnot available
KeywordsCartoonistComicsPoliticsNewspaperCommunismPortraitOrder (exchange)PublicityComic stripMedia studiesSociologyArt historyArtVisual artsHistoryLiteratureLawPolitical science

Abstract

fetched live from OpenAlex

This is a preliminary exploration of the work of Avrom Yanovsky (1911–1979) as a cultural producer associated with the radical left in Canada. The historical sieve of cultural selection has not favoured him, but the name “Avrom,” with which he signed most of his work, is a recurring signifier in the historical memory of the Canadian left. Researchers in the field are often aware of the many political cartoons he published in Communist newspapers such as The Worker and others from the early 1930s onwards. In addition to cartoons, Yanovsky’s cultural output included portraits, sketches, illustrations, stage sets, costumes, banners, murals and other art. He invented original characters and stories for Canadian comic books and worked on animated films and documentaries. He undertook publicity and labour education projects for unions and was also prominent in the Canadian Society of Graphic Art. An exponent of Yiddish culture, he was active in the cultural life of the United Jewish People’s Order and a familiar figure at their summer camps. He was widely known for his popular “chalk talks,” which he modelled on the practice of J.W. Bengough, the politically engaged cartoonist of an earlier generation. Yanovsky shared Margaret Fairley’s views on the responsibilities of the artist-revolutionary, and his occasional writings focused on the centrality of culture in any strategy to promote radical social change.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.377
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.035
GPT teacher head0.313
Teacher spread0.277 · 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 teacher head, not a consensus.

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
Published2019
Admission routes2
Has abstractyes

Explore more

Same venueLeft History An Interdisciplinary Journal of Historical Inquiry and DebateSame topicCanadian Identity and HistoryFrench-language works237,207