Bibliographic record
Abstract
An exceptional showcase of interdisciplinary research, Critical Inquiries for Social Justice in Mental Health presents various critical theories, methodologies, and methods for transforming mental health research and fostering socially just mental health praxis.Marina Morrow and Lorraine Halinka Malcoe have brought together a diverse group of scholars, activists, and practitioners whose work exposes and disrupts the biomedical, neoliberal, and individualistic practices that permeate contemporary mental health research, policy, and practice.The contributors employ a variety of methodologies including intersectional, decolonizing, Mad studies, feminist, post-structural, transgender, queer, and critical realist to interrogate how power relations manifest in local to global mental health systems and their impact on people with mental distress.By privileging the voices of people with lived experiences of emotional distress and psychiatry, the collection encourages the reader to envision systems and supports designed from the bottom up, in which the people most affected have decision-making authority over their formations.Critical Inquiries for Social Justice in Mental Health demonstrates why and how theory matters for knowledge production, policy, and practice in mental health, and it creates new imaginings of decolonized and democratized mental health systems, of abundant community-centred supports, and of a world where human differences are affirmed.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.871 | 0.762 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".