<i>Colonialingualism</i>: colonial legacies, imperial mindsets, and inequitable practices in English language education
Bibliographic record
Abstract
Translanguaging and plurilingual approaches in English Language Education (ELE) have been important for envisaging more equitable language education. However, the languages implemented in translanguaging or plurilingual classrooms predominantly reflect the knowledge and belief systems of dominant, nation-state, “official”, and/or colonial languages as opposed to those of endangered and Indigenous languages. This paper contends that privileging dominant colonial knowledges, languages, and neoliberal valorizations of diversity is Colonialingualism. Colonialingualism, covertly or overtly, upholds colonial legacies, imperial mindsets, and inequitable practices. Colonial languages carry colonial legacies and can perpetuate an imperialistic and neoliberal worldview. Languages can be disembodied from place and commodified as mere “resources”, important only for economic “value” rather than cultural importance, in a “modern” global, neoliberal empire. Colonialingualism resides in the “epistemological error” in dominant western thought, characterized by linguistic imperialism and cognitive imperialism; the view that humans are superior to nature; and white (epistemological) supremacy. This “epistemological error” dominates the current mainstream western worldview, institutions, pedagogies, mindsets, and ways of languaging. Colonialingualism is subtractive and detrimental to multilingual, multicultural learners’ identities and heritages; endangered, Indigenous languages and knowledges; minoritized communities; and our environment. This paper argues that: (1) colonialingualism illustrates the “transformative limits” of translanguaging and plurilingualism; and (2) an epistemic “unlearning” of the western “epistemological error” is required to enable equitable use of all languages, languaging processes, and knowledge systems, including those Indigenous and minoritized, in ELE. The example of heritage language pedagogy in the Canadian context will demonstrate how epistemic “unlearning” while languaging can take place.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.018 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".