Pedagogical translanguaging: Examining the credibility of unitary versus crosslinguistic translanguaging theory
Bibliographic record
Abstract
This article analyzes the credibility of two conceptions of pedagogical translanguaging theory, namely, unitary translanguaging theory (UTT) and crosslinguistic translanguaging theory (CTT). I argue that there is no difference in pedagogical implications between UTT and CTT, but there are significant differences in the way UTT and CTT pedagogies are framed theoretically. UTT claims that the bilingual’s linguistic system is unitary and undifferentiated and that languages have no cognitive or linguistic reality. Based on this claim, UTT rejects several theoretical concepts including the notion of academic language, additive (approaches to) bilingualism, the common underlying proficiency (CUP) and the pedagogical importance of teaching for transfer across languages. CTT, by contrast, affirms the legitimacy of these theoretical concepts, which are fully consistent with dynamic or heteroglossic orientations to bilingual cognitive processing. Within CTT, bilinguals actually do speak languages, involving multiple registers and fluid boundaries, and teaching for transfer across these boundaries is a prime function of pedagogical translanguaging.
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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 | 0.023 | 0.052 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.003 | 0.033 |
| Scholarly communication | 0.007 | 0.014 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.003 | 0.005 |
| 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".