Ethical Dilemmas of Trauma Representation; Considering Art Spiegelman as a Liminal Mediator
Bibliographic record
Abstract
Theodor Adorno famously proclaims that “to write poetry after Auschwitz is barbaric” (285). Undoubtedly, he does not attempt to silence narratives of the Holocaust through this oft-cited remark. With this paradox began a conversation that proceeds to this day and resulted in a paradigm that haunts all trauma narratives: “who has the right to speak or write? What are the appropriate forms for their utterance to take?” and finally, “who is speaking, to whom, on whose behalf, and in what context?” (Godard 18). An author inevitably distorts and modifies an original traumatic experience by inserting his voice into the narrative via stylistic choices, formatting, narration, etc. By default, he is thus positioned as a liminal mediator between the experiencer of the story and the reader. He must ethically avoid distortions of the subject’s story, despite such responsibility creating a difficult paradox to resolve. I consider this conflict through Art Spiegelman’s Maus volumes I and II. Maus raises the same questions of censorship, authorship, and responsibility through its subject matter of the Holocaust and its medium as a graphic novel. I focus primarily on Art, the narrator, as a mediator between Spiegelman the author, his father, mother, and the written page.
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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 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.013 | 0.095 |
| Scholarly communication | 0.020 | 0.019 |
| Open science | 0.003 | 0.011 |
| Research integrity | 0.010 | 0.009 |
| 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".