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Record W4327693007 · doi:10.1007/s10583-023-09526-y

Witnesses, Deniers and Bourgeois Troublemakers. The Holodomor and Ukrainian-Canadian Collaboration in Marsha Forchuk Skrypuch’s Winterkill (2022)

2023· article· en· W4327693007 on OpenAlexaboutno aff
Mateusz Świetlicki

Bibliographic record

VenueChildren s Literature in Education · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsnot available
FundersKosciuszko Foundation
KeywordsUkrainianFamineContext (archaeology)SociologyReading (process)BourgeoisieLawHistoryMedia studiesPolitical scienceLinguisticsPoliticsPhilosophy

Abstract

fetched live from OpenAlex

Abstract The article examines Marsha Forchuk Skrypuch’s Winterkill (2022), a recent Holodomor middle-grade historical novel issued by Scholastic, and showcases that Skrypuch explores the implicated position of North Americans – especially Soviet collaborators and journalists – in the context of the famine and Stalin’s collectivization. Most notably, Winterkill brings attention to the actions of Rhea Clyman, a Jewish-Canadian journalist who wrote factual articles about the situation in the Soviet Union but until the mid-2010s was largely forgotten. In the first part of the article, the author briefly introduces the historical background and points to the recent increase of Holodomor-themed Anglophone books. Then, close reading Winterkill , they argue that many characters in the novel, including the ones based on Clyman and Alice, a Ukrainian Canadian girl she met in Kharkiv in 1932, emerge as what Michael Rothberg has called “implicated subjects.” The article demonstrates that at first the foreigners in the novel are enchanted with Stalinism, accept its benefits, and their actions – directly and indirectly – contribute to the destruction of the Ukrainian countryside. Winterkill showcases both the importance of recognizing one’s implication and sharing the testimony of the Holodomor witnesses, hence keeping the memory of the famine and its victims alive.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.679
Threshold uncertainty score0.958

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.004
GPT teacher head0.254
Teacher spread0.250 · 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.

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

Citations4
Published2023
Admission routes1
Has abstractyes

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