Transepistemic English language teaching for sustainable futures
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 There is a relationship between language and the environment. Languages shape worldviews, inform behaviours, and are not disconnected from local political, sociocultural, and ecological contexts. English has an enduring colonial, imperialist, and assimilationist legacy and can be easily delinked from context, culture, and place. In this article, I argue that an epistemic (un)learning of the Western ‘epistemological error’ is required to enable equitable validation of all languages and knowledge systems, including those Indigenous and minoritized, in ELT for more sustainable futures. Heritage language pedagogy (HLP), conceptualized differently from mainstream versions, and transepistemic language education in the Canadian context will illustrate how epistemic (un)learning takes place. HLP seeks to relink connections between languages and place-based knowledges. The article demonstrates how HLP and transepistemic language education enables learners and educators to engage in a decolonial and pluriversal sharing of languages, knowledges, and worlds for more equitable and sustainable ELT.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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