A Multilingual Child's Literacy Practices and Contrasting Identities in the Figured Worlds of French Immersion Classrooms
Bibliographic record
Abstract
In this paper, we explore the intersection of practice, identity, resources and literacy central to the New Literacy Studies and recent second language research informed by sociocultural theories of learning and language. Drawing on the construct figured worlds of literacy that describe how representations of literacy practices invoked in relation to certain people frame their social position and the construction of their identities, we discuss literacy practices and teacher discourse documented in our classroom research. We present data excerpts that illustrate how a multilingual child is variously constructed as ‘literate child’ in the figured worlds of elementary school French Immersion classrooms. In particular, we consider how her literacy practices are shaped and her identities mediated in different ways socially, materially and linguistically. We argue that the mediation of her identities in classroom literacy activities is tied to teacher expectations of her future educational progress. Finally, we suggest that partnerships between researchers, educational practitioners and policy makers aimed at documenting classroom literacy practices may highlight how interpretations of multilingual children's identities can serve to fix or change their social relations and educational paths.
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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 | 0.001 | 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 | 0.007 |
| Scholarly communication | 0.005 | 0.002 |
| 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".