A Narrative Approach to Authorship: The Work of Evi Tampold from Her Mother/Publisher’s (and Her Own) Perspective
Bibliographic record
Abstract
Collaborative authorship in graphic medicine is examinable from a number of perspectives. One neglected approach is to look for developments in how an individual artist collaborates over the course of illustrating different graphic medicine novels. In the first, the artist collaborated with her younger self in trying to regain memories of an until then forgotten past. In the second, she worked closely with the writer to try to determine exactly what the author intended, adding a new dimension to the piece unavailable without the illustrations. In the third still to be completed work, her illustrations are based on collaboration with only the text and a few photographs, lacking direct contact with the author. How this artist’s three methods of collaboration have defined her collaborative authorship will be the focus. What is unique is this study will be undertaken from the stand point of the illustrator’s publisher, who is also her mother.
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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 | 0.009 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.016 | 0.036 |
| Scholarly communication | 0.018 | 0.013 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.003 | 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".