“Loud, Wonderful, Funny, Passionate Indigenous Voices”: An Interview on Indigenous Comics with Alina Pete (Nehiyaw)
Bibliographic record
Abstract
ABSTRACT: In this interview, I speak with Alina Pete (they/them), a Nehiyaw (Cree) comics artist, writer, and editor from the Little Pine First Nation in Saskatchewan. Alina is the creator of the Aurora-winning webcomic Weregeek (2006–2021), as well as multiple themed anthologies of Indigenous comics, most recently Indiginerds: Tales of Modern Indigenous Life (2024). This interview focuses on Alina’s process in creating these anthologies (the design, curation, organization, and unification of the disparate comics in a collection), as well as on how these anthologies evoke certain kinds of graphic Indigeneity: What kinds of Indigenous stories and knowledge lend themselves to the comics medium? What gets lost? What potential does the comics anthology hold for graphic Indigeneity and storytelling? We begin, of course, by speaking about Alina’s comics origin story, as well as themes of queerness, Indigenous futurism, anthropomorphism, and hope that permeate their illustrative work. Along the way, Alina speaks about how they unite First Nations creators to tell graphic narratives in themed, focused manners through digital crowdfunding platforms like Kickstarter and Backerkit: myths and folktales from North America; contemporary, modern Indigenous joy; post-apocalyptic hope; and more. Befitting Alina’s work, we end on a note of hope about the future of Indigenous comics: Alina tells me about the newly minted Indigenous Comic Creators Program that they helped to create in partnership with the Smithsonian’s National Museum of the American Indian.
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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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".