Bibliographic record
Abstract
In Cherie Dimaline’s 2019 novel, <italic>Empire of Wild</italic>, Elder Ajean states “You think all we have around here is good men and handsome women like me? There’s just as many bad. We gotta keep it in balance. . . Someone has to.” Ajean doesn’t position people as good or evil, but sees balance as the ultimate responsibility, especially for her family and her community. Using films and texts by Maria Campbell, Warren Cariou, Marjorie Beaucage, Dimaline, and from <italic>Stories of Our People / Lii zistwayr di la nassyon di Michif: A Métis Graphic Novel Anthology</italic>, I will situate the Rougarou as a creature who affirms the importance of Métis ways of knowing in the past and in contemporary times. The Rougarou (with variations in stories of the Cree, French-Canadian, etc.) is also a fluid creature who can be a figure of pity because they have been a bad relation. Does “all our relations” include the Rougarou?
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 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 | 0.000 | 0.000 |
| Open science | 0.001 | 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".