Taking Tragic Measures? Disability Studies’ Anti-Metrology and the Government of Thalidomide
Bibliographic record
Abstract
This paper interrogates the relationship between thalidomiders, the name used by victims of the drug thalidomide, and the kinds of subjectivity assumed in disability studies as an activist research enterprise. The thalidomide case presents a fundamental challenge to disability studies’ understanding of tragedy. I begin by reviewing some founding and more recent literature in disability studies. Next, I discuss the thalidomide tragedy, and how victims groups are using their existence as tragic in order to participate in the drug’s regulation and the public narratives of the drug. In the third section of this paper, I discuss three perspectives on subject formation, the Foucauldian, the Heideggerian, and Actor-Network Theory, and ask how we can make sense of this instance tragic subject-formation. I make a distinction between ‘active’ and ‘passive’ tragedy discourse, and conclude with a discussion of how disability studies might continue to talk about active tragedy.
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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 | 0.012 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.015 | 0.063 |
| Scholarly communication | 0.010 | 0.011 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.004 | 0.004 |
| 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".