Diasporic playgrounds: how coming-of-age stories unsettle official multiculturalism in \nCarrianne Leung’s That Time I Loved You and Souvankham Thammavongsa’s How to \nPronounce Knife
Bibliographic record
Abstract
This thesis examines how the perspectives of children in the short story collections That \nTime I Loved You by Carrianne Leung and How to Pronounce Knife by Souvankham \nThammavongsa function to challenge government discourses on multiculturalism in so-called \nCanada. Through depictions of mental illness among immigrant and refugee families, acts of \nsecret-keeping that keep hurtful information hidden, and rejections of heteronormativity, these \ncoming-of-age stories resist attempts to assimilate migrants into an overarching storyline \nfeaturing success, gratitude, and transparency. The thesis’s introductory chapter contextualizes \nCanadian Multiculturalism, reviews pertinent scholarship in diasporic studies within English \nCanada, and considers the place of the bildungsroman genre in this field. Chapter 2 embarks on \na close analysis of the primary texts, exploring how immigrants and refugees who express \nmental illness and/or die by suicide subvert discourses that emphasize the potential prosperity \nof those who come to Canada. Chapter 3 addresses secret-keeping among the children of \nimmigrants and examines how withholding information is a radical act practiced by those who \nare meant to be legible and grateful to the nation-state. This chapter highlights literary \ntechniques such as unnamed characters and sparse language which contribute to secrecy \nwithin these texts. Subsequently, Chapter 4 discusses immigrant queerness and how it stands in \ncontrast to the linear temporalities embodied and projected by hegemonic rhetoric. The final \nchapter of this thesis offers concluding thoughts on the unique epistemologies of migrant \nchildren: how their knowledges, which reach across space and time, hold something greater \nthan the sum of their individual inheritances. Among these children is the wisdom to imagine \nmore equitable societies and futures that prioritize justice and kindness.
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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 | 0.006 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.025 | 0.030 |
| Scholarly communication | 0.014 | 0.010 |
| Open science | 0.002 | 0.013 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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.
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".