Bibliographic record
Abstract
My discussion of Karen McBride’s Crow Winter will focus on how reconnecting with tradition and ceremony heals Hazel Ellis and helps her to come to terms with the recent loss of her father. Specifically, she heals through participating in a sweat lodge ceremony, her interactions with Nanabush and in learning about the Seven Grandfather Teachings. Her participation in the sweat lodge ceremony connects her with her spirituality. Through her interactions with traditional medicines such as tobacco and cedar, Hazel learns to open up, helping her understand that she needs to confront her feelings of grief. Through her connection with Nanabush she becomes comfortable in navigating the Spirit World. By learning about the Seven Grandfather Teachings with a focus on bravery, she is able to make a life-changing decision to protect the sacredness of the land. The novel teaches settler audiences and readers to understand the importance of land to Indigenous Peoples. Rather than look at it as property or something to be exploited, one needs to enter into a relationship with the land. Hazel makes evident that not only does land inform ways of knowing and being for Indigenous Peoples, but also that it guides people such as herself in healing journeys.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.016 | 0.014 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.007 |
| Insufficient payload (model declined to judge) | 0.008 | 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".