Our Madness is Invisible: Notes on Being Privileged (Non)Disabled Researchers
Bibliographic record
Abstract
This autoethnographic piece traces how two researchers continually negotiate their privileges, successes, insecurities, challenges, and (non)disabled identities in the neoliberal academy. We interrogate the co-constitution of identity of (1) a mentally disabled researcher and graduate student who researches madness in the midst of dealing with his own struggles maintaining a professional identity and repairing a fractured self; (2) a non-disabled doctoral student who has found academic success, but has had his life stalled multiple times by significant mental health challenges. We propose the concept of the privileged (non)disabled self to capture how researchers become entangled in permanent or temporal disabilities while simultaneously negotiating their accomplishments. We encourage researchers not to sideline their reflections on privilege and disability as irrelevant, but continually examine their identities in order to reveal potential avenues for emancipation.
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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 | 0.016 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.042 | 0.084 |
| Scholarly communication | 0.017 | 0.013 |
| Open science | 0.003 | 0.019 |
| Research integrity | 0.006 | 0.016 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".