In search of immersion teacher educators’ knowledge base
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 Although it has long been touted as a key ingredient to successful immersion practice, no research to date has examined immersion teacher educators’ (ITEs) knowledge base as it relates to the work of content, language, and literacy integration in curriculum planning and teaching. Thus, it is difficult to know whether or not ITEs are ready and able to support the pedagogical transition toward better-integrated practice in the immersion classroom. This qualitative study set out to fill this gap in our knowledge by exploring ITEs’ understanding of the nature and role of language and literacy in the context of their discipline of expertise through the use of an analytic framework designed to examine ITEs’ knowledge base. Key findings point to the need for the elaboration of a professional development (PD) program specifically dedicated to supporting ITEs’ continuous knowledge growth, particularly when it comes to the issue of pedagogical integration.
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) | 0.004 | 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 it