Moving the Nation: Multiculturalism, Race, Representation, and Emotional Belonging in Canada
Bibliographic record
Abstract
This dissertation is a braided history that weaves together personal, professional, and scholarly narratives to critically examine the complex interrelationship between multiculturalism, race, representation, and emotional belonging in Canada. A one-time “Asian” refugee child from Uganda, a long-time as well as racialized and visually impaired journalist with CBC Radio (a daily site of Canadian nation-making that for too long neglected the stories of ethno-racial others), and a serious student of history, I explore what it means to live in a postcolonial context while also navigating the legacies of colonialism. I do so by working through the contested discursive formation of official multiculturalism, which was, I argue, designed not only to manage minorities, but also to manage majoritarian resistance to pluralism. Drawing on the concept of positionality, situated knowledge, and other insights from oral history, emotions history, and feminist-informed personalized scholarship, the project brings together and examines refugee narratives, oral histories, personal reflection, and some ethnographic observations as well as news reports, newspaper articles, government documents, memoirs, journalist non-fiction, and conference presentations and discussion. It also scrutinizes and contextualizes my recollections as a long-time journalist with Canada’s public broadcaster. Four case studies are analysed within broader comparative and international contexts. The scale of analysis begins with a focus on individuals, namely, the dramatically contrasting refugee narratives by which my mother and father articulated their expulsion in 1972 from Uganda and resettlement in Canada. Turning to policy and race, I revisit certain debates related to Canada’s policy of official multiculturalism through a lens sharpened by the experience of South Asians in East Africa. In addition, I assess how, as a journalist, I found official multiculturalism useful as a discursive foundation for pitching news stories about minority experiences. Finally, the examination of the Air India bombing in 1985 highlights the failure of Canadian official multiculturalism. It was a failure, I argue, not only because the state failed to protect the victims and support their families, but also because the political complexities that gave rise to the bombing are too often neglected in how the tragedy is remembered, notwithstanding the sustained, and ultimately successful, efforts by the Air India families to ensure that their losses are commemorated as Canada’s loss.
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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 | 0.002 | 0.006 |
| Science and technology studies | 0.057 | 0.017 |
| Scholarly communication | 0.011 | 0.002 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".