‘She’s practically normal!’: Disability, gender and image in Doom Patrol
Bibliographic record
Abstract
The portrayal of disability in superhero comics has often been problematic. Frequently, disabled characters in superhero comics, when not merely marginal, are portrayed as pitiable or villainous, or, if they are disabled heroes like Daredevil or Professor Xavier of the X-Men, as examples of the super-crip, that is, given powers as compensation for their disability. An arguable exception to this tendency is Drake and Premiani’s Doom Patrol of the 1960s, especially the character of Rita Farr a.k.a Elasti-Girl. Examining this character through gender and disability theories we can see a sophisticated portrayal of marginalization as it pertains to image, spectacle and social norms. Though Rita has sometimes been left out of later iterations of the Doom Patrol on the grounds of seeming too ‘normal’, the character can be read as an exploration of how disability operates as a category of power, in a medium that has often used that category too simply. Reading the character via such concepts as Davis’s dismodernism and Wendell’s feminist disability, seeing her both as a member of this team of outcasts and as one who is frequently lured into a life in the mainstream, we can see how in Drake and Premiani’s series the categories of disability and gender interact with each other, and reflect and respond to societal expectations of power.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.016 | 0.049 |
| Scholarly communication | 0.011 | 0.009 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.006 | 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".