Bibliographic record
Abstract
This dissertation explores constructions of psychiatry as accurate, effective, and necessary by tracing supposedly objective psychiatric facts to their subjective roots. I focus on post-WWII Montreal, where the discursive shift from “mental hygiene” into “mental health” signified a new era of psychiatric alignment with science and medicine in order to question the ostensible and self-proclaimed certainty of psychiatric philosophy and practice. I explore the purposeful association of psychiatry with medicine, foregrounding the ways that a totalizing ideology (Arendt, 1951) was used to buttress psychiatric expansion while simultaneously abstracting individuals into groups and types of mental health problems. By constructing the subjective opinions of professionals as objective reality, the facticity of psychiatry is rooted in eugenics hierarchies that are mobilized towards creating a particular version of desirable citizens. Using archival data from the National Committee for Mental Hygiene (Canada) and related organizations, I read expert-centered accounts against the grain, tracing ideologies, logical leaps, constructions of facticity, and overarchingly, tracing objective facts to their subjective situatedness. Focusing on the ways that undescribed and abstracted behaviours were used to funnel many individuals into a few problem-types, I show how constructions of contemporary mental health ideology are bound to social context. Specifically, I point to a psychiatric totalitarianism where all human suffering and problems become interpreted through a psychiatric lens and judged against problematic ideals of desirable citizens that bear direct overlap with eugenic ideals. This limited and limiting version of ‘the human’ rules Western social and economic hierarchies, defining both normalcy and abnormality as grounded in eugenic-based gradations that favour a white supremacist, patriarchal, and capitalist view of mental health. As such, the ideology propagated by psychiatry becomes increasingly further removed from people’s experiences of distress, defining each citizen as either participating and helping with Canada’s “mental health crisis” or else as being part of the problem and becoming categorized through the problem groups and types taxonomized within psychiatry. In this way, I show how psychiatric hegemony represents a medicalized approach to human suffering and problems that works to depoliticize distress and stunt social justice-informed change.
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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 | 0.010 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.009 |
| Science and technology studies | 0.053 | 0.032 |
| Scholarly communication | 0.015 | 0.004 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.003 | 0.008 |
| 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".