Decoding the Visual Rhetoric: Memory and Trauma in Lynda Barry’s One! Hundred! Demons!
Bibliographic record
Abstract
Memory is an important tool in Lynda Barry’s One! Hundred! Demons! (2002) as she reconnoitres in non-linear fragments the personal trauma she faced while she was growing up. Layered into nineteen disjointed chapters, Barry’s graphic narrative is an amalgamation of images, collages and photographs, often following the pattern of a scrapbook style that justifies not only the events drawn in her narrative but also the motive of visual rhetoric in comics where visual images communicate and concretize meaning. Initially published as web comics (slate.com), each chapter consists of hand-painted vignettes of multifarious themes which are directly or indirectly linked to Barry’s life, covering from her childhood to adulthood. In the backdrop of these tools, techniques of visual rhetoric the objective of this paper is to investigate the form of the graphic narrative, the visual language employed in order to explore the traumatised childhood, memory and truth-telling in comics.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.016 | 0.031 |
| Scholarly communication | 0.011 | 0.008 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 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".