The Madwoman in the Academy, or, Revealing the Invisible Straightjacket: Theorizing and Teaching Saneism and Sane Privilege
Bibliographic record
Abstract
In this paper, I suggest that one way to bring mad perspectives and discussions about saneism/mentalism--systemic discrimination against people who have been diagnosed as, or are perceived to be "mentally ill"--into higher eduction is to situate them within existing curricula across disciplines. One of the ways curricula can be modified is by adapting existing theoretical frameworks from other interdisciplinary fields to mad issues and contexts. As an example of this adaptation, I turn Peggy McIntosh's article "White Privilege: Unpacking the Invisible Knapsack" (1988), a staple of undergraduate humanities curricula, into a teaching tool for showing not only the ways in which "sane" people--those who have never been psychiatrized or perceived as "mentally ill"--have access to privileges that mad people do not, but also the ways in which saneism/mentalism intersects with other forms of oppression such as racism, sexism, classism, heterosexism and ableism. Keywords: saneism, mentalism, mad studies, privilege, feminism, intersectionality, pedagogy
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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 | 0.007 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.013 | 0.098 |
| Scholarly communication | 0.010 | 0.014 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.002 | 0.006 |
| 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".