When you sing it now, just like new: First Nations poetics, voices, and representations
Bibliographic record
Abstract
Part One: ActualitiesIntroduction to Part One1. Memories and Reflections: Learning from Dane-zaa Women - Jillian Ridington 2. Hunting for Stories in Sound: Sharing Ethnographic Authority - Jillian Ridington and Robin Ridington 3. Soundman: A Guide to Field Broomfield and Stories from the Field - Jillian Ridington and Robin Ridington 4. Keynotes from the Dane-zaa: A Guide to In Doig People's Ears - Robin Ridington 5. Why Baby Why: A Guide to Howard Broomfield's Documentation of the Dane-zaa Soundscape - Jillian Ridington and Robin Ridington 6. Maintaining Dane-zaa Identity: Those Story I Remember, That's What I Live By Now - Jillian Ridington and Robin Ridington 7. Contact the People: A Guide to a Video on Dane-zaa Change and Continuity - Jillian Ridington and Robin RidingtonPart Two: Poetics and Narrative TechnologyIntroduction to Part Two8. Models of the Universe: Musings on the Language of Benjamin Lee Whorf - Robin Ridington 9. Voice, Representation, and Dialogue: The Poetics of Native American Spiritual Traditions - Robin Ridington 10. That Is How They Grab It: Celestial Discourse in Dane-zaa Music and Dance - Robin Ridington 11. Dogs, Snares, and Cartridge Belts: The Poetics of a Northern Athapaskan Narrative Technology - Robin Ridington 12. Tools in the Mind: Northern Athapaskan Ecology, Religion, and Technology - Robin RidingtonPart Three: Re-Creation in First Nations LiteraturesIntroduction to Part Three13. You Think It's a Stump but That's My Grandfather: Narratives of Transformation in Northern North America - Robin Ridington 14. Fieldwork in Courtroom 53: A Witness to Delgamuukw v. A.G. - Robin Ridington 15. Theorizing Coyote's Cannon: Sharing Stories with Thomas King - Robin Ridington 16. Happy Trails to You: Contexted Discourse and Indian Removals in Thomas King's Truth and Bright Water - Robin RidingtonEpilogue
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.006 | 0.000 |
| 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".