Bibliographic record
Abstract
In recent years, studios like Marvel and DC have seen enormous success transforming comics into major motion pictures. At the same time, bookstores such as Barnes & Noble in the US and Indigo in Canada have made more room for comic books and graphic novels on their shelves. Yet despite the sustained popular appeal and the heightened availability of these media, Indigenous artists continue to find their work given little attention by mainstream publishers, booksellers, production houses, and academics. Nevertheless, Indigenous artists are increasingly turning to graphic narratives, with publishers like Native Realities LLC and Highwater Press carving out ever more space for Indigenous creators. In Indigenous Comics and Graphic Novels: Studies in Genre, James J. Donahue aims to interrogate and unravel the disparities of representation in the fields of comics studies and comics publishing. Donahue documents and analyzes the works of several Indigenous artists, including Theo Tso, Todd Houseman, and Arigon Starr. Through topically arranged chapters, the author explores a wide array of content produced by Indigenous creators, from superhero and science fiction comics to graphic novels and experimental narratives. While noting the importance of examining how Indigenous works are analyzed, Donahue emphasizes that the creation of artistic and critical spaces for Indigenous comics and graphic novels should be an essential concern for the comics studies field
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".