Canadian Cossacks: Finding Ukraine in Fifty Years of Ukrainian-Canadian Literature in English
Bibliographic record
Abstract
Discourses of diaspora and transnationalism have begun to question previous traditional assumptions about the inevitability of ethnic assimilation by drawing attention to various kinds of hybrid identities, but I contend that, in contemporary Canadian literature, we cannot replace an outmoded model of eventual integration with an uncritical vision of ethnic persistence and hybridity. Much thinking about diasporic and ethnic identities suggests that, on the one hand, there are genuine marginalized identities worthy of inquiry and, on the other, there are symbolic ones undeserving of serious study. This dissertation focuses on the supposedly disingenuous or symbolic kinds of ethnic and diasporic identities, providing an analysis of Ukrainian-Canadian ethnic identity retention in a case study of second-, third-, and fourth-generation Canadians of Ukrainian descent who both read and write in English (not Ukrainian). Looking at Ukrainian-Canadian literature from 1954 to 2003, this dissertation argues: (1) ethnic identity affiliation does not necessarily dissipate with time; (2) ethnic identity in a hostland manifests itself as imagined ties to a homeland; and (3) lacking meaningful public and private recognition of ethnic group membership yields anxiety about subjectivity. I first argue that as multicultural policies drew attention to racial marginalization, Ukrainian-Canadian ethnic identity shifted from being an aspect of socio-economic disenfranchisement to becoming a hyphenated identity with links to Ukraine. I then suggest that in order to make that connection to Ukraine viable, writers attempt to locate Ukraine on the Canadian prairie as a substitute home-country. Such attempts give rise to various images Ukrainian-Canadian uneasiness and discomfort, primarily as authors struggle to account for First Nations’ prior presences on the landscape that they want to write as their own. Further, I analyze attempts to locate ethnic authenticity in post-independence Ukraine that also prove unsatisfactory for Ukrainian-Canadian subject formation. The many failed attempts to affix Ukrainian-Canadianness as a meaningful public and private identity give rise to unsettled and ghostly images that signal significant ethnic unease not to be overlooked in analyses of ethnic and diasporic identities. In these ways, this dissertation contributes to ongoing debates and discussions about the place of contemporary literary ethnicity in Canada.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.006 | 0.009 |
| Science and technology studies | 0.029 | 0.009 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".