Tangled up with everything else: Toward new conceptions of language, teachers, and identities
Bibliographic record
Abstract
I am Canadian and currently live and work in and around Vancouver, British Columbia, but I was born and lived until my late 20s on the Canadian prairies. My fi rst teaching job was with Plains Cree children in a school in a small town in northern Alberta. My second teaching job was teaching English at night school to immigrant adults, many of whom were Chilean refugees after the 1973 coup. I think of the challenges I experienced in both positions as something like knots in entangled yarn, and I have been trying to untangle them ever since: throughout my graduate studies; my PhD dissertation about Swampy Cree-speaking students learning English in northern Ontario; my university teaching of English as an additional language teachers and of Indigenous and heritage language teachers; my research with children learning English at school; my collaborative classroom research with teachers; and most recently, the research I do with my colleague, Diane Dagenais, investigating language and literacy learning through engagement with a variety of digital technologies. Our emphasis in this recent work has not been so much on teachers, but rather on student learning, although teacher experiences are of course a logically necessary direction we will pursue in the future. In this chapter I trace how my thinking on teacher identity and language teaching has evolved along with developments in our fi eld, and with my accumulated experience working with teachers.
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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 | 0.000 | 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) | 0.015 | 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".