Progress, challenges, and trajectories for indigenous language content-based instruction in the United States and Canada
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Indigenous language content-based instruction in the United States and Canada is primarily known as Indigenous language medium or Indigenous language immersion (ILI) education. In spite of huge barriers, it has grown over the past decade. Programs have emerged from concerns about language loss and a desire for language revitalization. Language revitalization takes several generations since it seeks an outcome where the Indigenous language is primary with high, but secondary, proficiency in the nationally dominant language. To establish a trajectory to reach such an outcome, the majority of schooling until high school graduation should be through the Indigenous language. Indigenous language medium schooling also seeks to produce sufficient mastery of academics and English for access to English medium higher education. Where a sufficiently strong model has been implemented, as in Hawaiʻi, those results are beginning to be produced. At present, the models being implemented elsewhere in the two countries are at varying stages of development, with minimal government support.
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.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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 it