Bibliographic record
Abstract
This paper explores how Indigenous Young Adult Literature (IYAL), offers teacher candidates (TCs) spaces for examining crucial ideas regarding Indigenous knowledge and worldviews. Using IYAL as a pedagogical approach with TCs in education programs is one step toward developing anti-oppressive education practices that work to understand marginalized peoples while also enacting pedagogies “that work against the privileging of certain groups, the normalizing of certain identities, and that make visible these processes” (Kumashiro, 2000, p. 35). By incorporating Indigenous knowledge as story (Rice, 2020), IYAL can be a tool for developing nuanced understandings of Indigenous youth, Indigenous Peoples and communities. Supporting TCs to better attend to the needs of Indigenous youth through IYAL allows for exploring the complexity of youth, identity, and culture of Indigenous Peoples. IYAL can feed the spirits of Indigenous youth in schools, a place that has historically been hostile, violent, and deadly to them. This paper explores how IYAL can further support non-Indigenous teacher candidates to develop better understandings of Indigeneity at large.
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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.006 | 0.011 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".