<i>Becoming Wolf</i> and other stories: using Indigenist arts-based methodologies to explore urban Indigenous coming of age
Bibliographic record
Abstract
Arts-based methodologies are increasingly being used in community-based research to explore and communicate issues of importance to Indigenous communities. Situating research in an Indigenist framework ensures that relational accountability—foundational to Indigenous ways of knowing and doing—is threaded throughout all stages of a research project. In this article, the authors describe how using Indigenist arts-based methodologies helped to develop critical knowledge sharing tools about urban Indigenous coming of age for youth living in foster care. The article describes how wisdoms gathered at a knowledge holder’s dinner and two youth workshops were used to develop the story Becoming Wolf, which was later adapted to a watercolour infographic and a graphic novel. We hope that this article shows our support for socially transformative and allied research and contributes to discourses about knowledge co-creation and mobilization.
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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 | 0.008 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 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".