Translanguaging and Multilingual Texts as a Resource in Superdiverse Classrooms
Bibliographic record
Abstract
This contribution draws on the preliminary results of a project that uses translanguaging and plurilingual texts during an intervention (of six months) in one primary and one lower secondary school class in Vienna. Although Viennese pupils’ linguistic repertoires are highly diverse, pupils usually barely get a chance to use their respective repertoires at school, because of a focus on highly prestigious languages, such as German or English. We assumed that pupils would positively experience the use of their plurilingual competences to gain self-efficacy. Moreover, we expected that group dynamics would improve due to the use of translanguaging. Results of the ethnographic observations and interviews we conducted with one teacher at each school at the end of the intervention are discussed in this article. They support the conclusion that school classes that are linguistically diverse benefit from intervention at the socioemotional level. However, it is crucial that teachers pay particular attention to the integration of less dominant languages. Keywords: translanguaging pedagogy, plurilingual texts, linguistic superdiversity, self-efficacy, dominant languages
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| 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 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".