Amplifying Indigenous Voices: Four Indigenous Publishing Houses
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract: Existing research in the field of Indigenous children's literature is sparse but growing. A notable gap in the literature is the paucity of insight into Indigenous picturebook publishing. In preparation for a larger study of Indigenous publishing processes, in this study, we conducted a website analysis to explore the work of Indigenous publishing houses. From this data, we constructed four case studies focusing on Magabala Books (Australia), Black Bears and Blueberries Publishing (USA), Theytus Books (Canada), and Inhabit Media (Canada). Additionally, we present a close analysis of four recently published picturebooks from the publishing houses (one from each). In this article, we provide insights into the key themes underpinning the four Indigenous publishers, including a commitment to storytelling, collaboration, and education; the amplification and prioritization of Indigenous languages; the place of external funding; incorporation of Indigenous art; and the educational background of the authors and illustrators.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.012 | 0.007 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it