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Record W7014943466

Review of <i>Leaving Shadows: Literature in English by Canada'sUkrainians</i> By Lisa Grekul

2007· article· en· W7014943466 on OpenAlexaboutno aff

Bibliographic record

VenueLincoln (University of Nebraska) · 2007
Typearticle
Languageen
FieldArts and Humanities
TopicShort Stories in Global Literature
Canadian institutionsnot available
Fundersnot available
KeywordsUkrainianImmigrationEthnic groupGovernment (linguistics)Representation (politics)Race (biology)World War IICanadian literatureLiterary criticismAmerican literature
DOInot available

Abstract

fetched live from OpenAlex

In the 1890s, when Canadian government officials first began a concerted effort to settle Canada's prairie provinces, they sent envoys to Eastern Europe, most notably to the area that is now Ukraine, to find people willing and able to accept the harsh conditions of the prairie region. Thus came the first large wave of Ukrainian immigration to Canada, followed by two others: during the Great Depression and immediately after World War Two. How has this large contingent of settlers fared in the Canadian imagination, specifically in its literature, as succeeding generations, born and raised in Canada, grapple with their dual heritage? Lisa Grekul addresses this question in clear, concrete fashion by examining the representation of Ukrainians in the work of various Canadian authors, in particular those who are descendants, as she is, of the first great wave of settlers to the prairies. In addition to scholars studying the prairies, her work is invaluable to all those interested in ethnic studies, literary or otherwise, of what Canada calls "invisible minorities," that is, those ethnic groups who are not differentiated by race from a nation's dominant culture, and are therefore more easily assimilated by (or, more negatively, disappear into) that larger culture. The book is organized thematically and chronologically into three main parts, beginning with the portrayal of Ukrainian settlers in works written by Ralph Connor, Sinclair Ross, and Margaret Laurence. Grekul includes them because, in the first half of the twentieth century, there were no fictional works written in English by the settlers themselves. The first such work, by Vera Lysenko, closes the section, providing a firm foundation for the works following, written by the generations descended from all three waves of Ukrainian immigration to Canada. The second part uses the fiction and poetry of Maara Haas, George Ryga, and Andrew Suknaski to explore the ways in w~ich the second generation both incorporates and moves away from the first one. The third section focuses on the works of Janice Kulyk Keefer and Myrna Kostash, considering the ways in which, several generations removed from the "Old Country," these writers grapple with their dual heritage. The works of less well-known and prolific writers are discussed throughout the book as well, and Grekul's citations are a thorough compendium of scholarship on the subject. In the introductory and concluding chapters, Grekul reveals the dilemma of ethnic writing from a very personal perspective, one lending poignancy to the negative conclusion she draws about the future of ethnic literature within the larger literary community. Because the Canadian arbiters of multiculturalism have made race "the locus of debate about identity," Grekul believes that literature by all "invisible minority" ethnic groups will remain marginalized and therefore "meaningless." In writing this book, she argues most persuasively for their importance to, and inclusion in, this continuing debate.

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)0.007
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: Not applicable
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.096
Threshold uncertainty score0.345

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0120.033
Science and technology studies0.0100.009
Scholarly communication0.0090.004
Open science0.0020.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0060.001

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 head0.005
GPT teacher head0.177
Teacher spread0.173 · 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
GenreReview

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
Published2007
Admission routes1
Has abstractyes

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