Bibliographic record
Abstract
Note on TerminologyMany Red River Métis people in Manitoba are reclaiming the older term Michif (our endonym, the name we call ourselves), though this is not yet reflected in the literature or in common vernacular outside our communities; therefore, I use this term interchangeably with Métis (except when referring to the Michif language).I utilize the double vowel writing system and the endonyms Anishinaabe (plural: Anishinaabeg; language: Anishinaabemowin), or less frequently Ojibwe, and Nêhiyaw (plural: Nêhiyawak; language: Nêhiyawawin) rather than their exonyms (Saulteaux/Chippewa and Cree, respectively).Just as there are regional and dialectical differences within the Anishinaabe nation (i.e., Saulteaux, Ojibwe, Chippewa), these also exist within the Cree nation (i.e., Nêhiyaw or Ininiw for "Plains Cree," and Omushkeego for "Swampy Cree").Exceptions occur when I reproduce exonyms and the phonetic writing system used in texts that I discuss.The Métis participants in this study all used the term "Cree" (except for one mention of "Nêhiyawak"); therefore, I use this term when discussing participant stories and findings.Moreover, I distinguish between spirituality and religion.I believe the former more accurately describes the spiritual ways of Indigenous peoples, and the latter connotes an institutionalized approach to faith with a heavier emphasis on dogma and hierarchy.While dogma and hierarchy may be present within some Indigenous spiritual practices, they are not defining characteristics as they are within religion.
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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 | 0.006 | 0.019 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.009 |
| Science and technology studies | 0.007 | 0.005 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.116 | 0.100 |
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".