Le Gout Qui Reste: Cultural Identity and Belonging in Ook Chung's <i>Kimchi</i>
Bibliographic record
Abstract
The emphasis placed on the questioning of identity in Québécois society since the Quiet Revolution of the mid-twentieth century continues to this day. Whereas this search for a specifically Québécois identity was originally cast in terms of an Anglophone/Francophone divide, the influx of migrants from around the world to the province since the 1970s has rendered such a simplistic, binary discourse impossible. The population of Québéc in general and of Montréal in particular is now multicultural; visible minorities now constitute twenty-six percent of the Montréal populace. While most migrants in Québéc are able to find a niche in Montréal in which they feel they belong, be it within a community of their fellow countrymen or the province's society at large, others are unable to feel a part of the society of their adopted land. One such migrant is Kim, the narrator of Ook Chung's Kimchi. Born in Japan to Korean parents and raised in Québec, he does not feel completely connected to any of these three countries. In this thesis, I explore the means by which he systematically deconstructs traditional defining factors of identity (race, language, ethnicity). Although he accepts that race, language and ethnicity have a bearing on one's sense of self, particularly in the form of cultural identity, he rejects the argument that they are in themselves sufficient to offer a sense of belonging. I argue that he focuses instead on the creation of community between individuals, irrespective of these factors.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.025 | 0.023 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.005 |
| 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".