Bibliographic record
Abstract
How might those of us located within post-secondary institutions support students who have experience of the mental health system in a meaningful way? Drawing on scholarship in social movement studies and a case study in Ontario, Canada, I distinguish between the prevailing mental health and wellness offerings of educational institutions and distinct forms of grassroots organising led by and for mad-identified students. This paper reflects on my past engagement with mad student intra-university organising in Ontario. Sifting through archival materials, personal writing and correspondence, I contemplate how my involvement as a past organiser in a radical student-run peer support and advocacy group has shaped and informed my scholarship within the field of Mad Studies. Connections are made between the activist knowledge-practices fostered within mad student groups and the growth of Mad Studies in Canada. Building from social movement studies, I argue for supporting and engaging in activism alongside politicised students who are organising on campuses to confront inequitable social relations, on their own terms. Doing so requires critically unpacking white dominant hegemonic ways of thinking about what constitutes ‘mental health and wellness’ from a student perspective.
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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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.052 | 0.025 |
| Scholarly communication | 0.016 | 0.003 |
| Open science | 0.003 | 0.017 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.006 | 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".