RACE AND MADNESS: LOCATING THE EXPERIENCES OF RACIALIZED PEOPLE WITH PSYCHIATRIC HISTORIES IN CANADA AND THE UNITED STATES
Bibliographic record
Abstract
The intersectional social construction of race and madness has significantly shaped the lived experiences of racialized people with psychiatric histories. Unfortunately, there are few studies that consider the intersections between race and madness, and fewer still that locate these intersections within the social and political contexts of colonization, Canadian and American settler states, and immigration. The primary purpose of this article is to provide a review of the literature that looks at the intersections of race and madness in Canada and the US. In particular, the author will highlight common themes that are articulated in this literature. The second goal of this article is to locate the experiences of racialized people with psychiatric histories within the socio-historical context from which they arise. The author will argue that race and madness have been mutually socially constructed in Canadian and American society. Further, the author will illustrate that psychiatric constructions of racialized people have allowed for the rationalization and justification of both historical and ongoing colonial and imperialist domination, slavery, and exclusionary immigration policies.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.052 | 0.026 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.002 | 0.004 |
| 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".