Bibliographic record
Abstract
This thesis examines the possibilities and limitations of theorizing Brown identity as an anti-racist and anti-colonial framework.By examining discursive representations of Brownness and Brown Identity in the Brown Canada Project, a community-led project of the Council of Agencies Serving South Asians, it introduces a new framework for conceptualizing the racialization, identity, and resistance of South Asians in the Greater Toronto Area.The thesis reveals three key themes: the salience of Brown identity in terms of a spirit injury that results from migration, assertion of pride in resistance, and how shared values and experiences of racism form pedagogies for education and community-building.These themes inform a theory of Brown identity and Brownness for anti-racist and anti-colonial resistance.This thesis aims to inform anti-racist and anti-colonial educational practices, political activism, and social movements.It serves as a point of generation for new lines of inquiry into Brown epistemologies, experiences, and relationships.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.057 |
| Scholarly communication | 0.007 | 0.012 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".