Bibliographic record
Abstract
In both Marco Corona’s and Gilbert Hernandez’s comic-book biographies of Frida Kahlo, they adapt several of her self-portrait paintings into cartoon caricatures, using her art as remade, drawn visual intertext to tell her story in a new form. Along with stylistic and compositional alterations that reshape her narrative in these comic books, Corona and Hernandez also accentuate the generic shift of selections of her oeuvre from autobiographical to biographical images. This article explores the implications of this shift from a self-reflexive genre to an other-focused one. As I show, the works of Corona and Hernandez use the formal elements of the comic book to emphasise – to varying degrees – the neutralising characteristic of intertextuality and the challenges of representing a cultural icon such as Frida Kahlo. Indeed, not only do their comics tell Frida Kahlo’s story, they also critically engage with her self-portraits as visual and autobiographical devices. The three main strategies Corona and Hernandez employ to do this include blending the identities of Kahlo the artist and Kahlo the character in intertext; using frames as seams to stitch or reconfigure her body; and, frequently referencing different pop cultural icons to add significance to their narratives. Ultimately, my analyses aim to show that these comic books make explicit the power of this medium to interweave several dimensions of life storytelling.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.125 | 0.023 |
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".