Bibliographic record
Abstract
Situated within a post-Truth and Reconciliation Commission Canadian context, educators are seeking Wisdom to create space in schools for Indigenous Knowledges, perspectives, languages, and histories. An Anishinaabe scholar invites readers to make meaningful connections to knowledge from experience that centers the child within the context of an Anishinaabe summer harvest camp, a competition powwow, and a smokehouse. The storyteller takes an inward turn, exploring features of the communal learning process conducive to the learning spirit, self-evaluation, and participation in learning and teaching that matches one’s readiness and skill. The story is powerful for connecting the heart and mind, stimulating receptivity to assessment-making opportunities for teachers that are relevant to Indigenous student community teaching-learning traditions. True to the storytelling method, the stories here are meant to stimulate remembering, reflection, and a process of deep knowing. The author invites educators to think with the stories for inspiration toward personal possibilities of praxis. Positive educational transformation is set into motion as teachers connect with Indigenous peoples to honor the diversity of children, co-create a relational curriculum inclusive of family and community to embrace Indigenous Knowledge that comes from the Land, and create space to generate and transmit new knowledge through story.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.013 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 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".