Bibliographic record
Abstract
Literature, particularly novels, serves as a platform for exploring Indigenous oral traditions—dynamic, culturally embedded knowledge systems. Novels by Indigenous authors extend oral storytelling within written narratives. This study examines how Indigenous oral traditions are preserved, transformed, and transmitted through novels from America, Canada, India, Australia, and Africa. Focusing on ten works, it explores storytelling as both a literary technique and an epistemological framework and act of cultural resistance. The selected novels include Ceremony (Leslie Marmon Silko), There There (Tommy Orange), Green Grass, Running Water (Thomas King), The Marrow Thieves (Cherie Dimaline), The Legend of Pensam (Mamang Dai), Son of the Thundercloud (Easterine Kire), Carpentaria (Alexis Wright), The Swan Book (Alexis Wright), The Palm-Wine Drinkard (Amos Tutuola), and The Healers (Ayi Kwei Armah). Using qualitative research and close reading, the study identifies oral narrative elements, affirming fiction as a vessel for Indigenous knowledge and cultural survival.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.018 | 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".