Architectures of raciality : racial grids and the convergences of the racial nonhuman in Canada, Singapore, and Malaysia
Bibliographic record
Abstract
This dissertation examines the emergence of racial grids, which define and organize categories of racial difference in relation to one another in a hierarchical manner, in Canada, Singapore, and Malaysia. It considers their varied approaches to embodied lived experiences of race and as belonging to a broader logic of raciality across the postcolonial world. This project focuses on three thematic points of comparison: the use of English as a mediator of racial distinction; the lasting influence of narratives of raciality that emerged during moments of inter-communal violence; and more recent recastings of these grids under forms of state-directed multiculturalism under conditions of globalization. This project examines these issues through sociopolitical theory and socio-juridical documents, as well as through Asian Canadian literature and post-Independence writing in English from Malaysia and Singapore. Drawing the work of Denise Ferreira da Silva, Frantz Fanon, Michel Foucault, and Jacques Derrida, this dissertation theorizes a figuration called the racial nonhuman in order to analyze how race organizes populations based on human types and defines them against an ideal, that is white and European, human. The racial nonhuman is engendered by historical, socio-juridical, and aesthetic discourses that render particular bodies as simultaneously within these nations and their demands for different racial types, but outside their ideal body politic. I analyze works by Fred Wah, Shirley Lim, Larissa Lai, Tan Twan Eng, and Lydia Kwa to compare how these nations have instituted and maintained their racial grids, as well as to examine how the racial nonhuman is contested and reimagined across these contexts.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".