Bibliographic record
Abstract
The conspicuous absence of trauma in superhero narratives is an established trope. In Avengers #200, the character Carol Danvers (aka Ms. Marvel) was subjected to a sexual assault that was characterised as non-violent, non-traumatic and even as an act of love. Chris Claremont, who had written the Carol Danvers character years prior, objected to this treatment of the character and recontextualized Carol’s assault as rape in Avengers Annual #10. A large part of this recontextualization involved the portrayal of long-term psychological trauma in Carol’s life. This symbolic thread carries into Uncanny X-men #236, titled ‘Busting Loose’ (also by Claremont), where the superheroine Rogue temporarily loses her superpowers and is then subjected to an off-panel sexual assault. Her response is to turn her consciousness over to Ms. Marvel (whose psyche now shares Rogue’s body). The story that unfolds from there draws upon the historical symbolism of Ms. Marvel and advances the recontextualization of Carol Danvers by portraying a post-traumatic dissociation followed by a reclamation of power and agency through community and disclosure, allowing the Carol character to redress, to some degree, the problematic historical excision of trauma from superhero narratives that deal with sexual violence.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.022 | 0.015 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.011 | 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".