Legitimizing Plurilingual and Pluricultural Identities: Designing an Arts-Infused Cultural-Historical Activity System
Bibliographic record
Abstract
Widespread monolingual practices have often overlooked the plurilingual and pluricultural skills of superdiverse children – skills such as their ability to draw on linguistic and cultural competencies – in both formal and informal educational settings. However, arts-based multimodal activities can help reveal children’s “invisible” linguistic and cultural assets while simultaneously fostering language and literacy development. This paper presents a design-based study that integrated arts-based tools, plurilingualism, and communities of practice in the implementation of a 16-week after-school program for superdiverse children in Western Canada by using a cultural-historical activity theory (CHAT) lens. Multiple interviews were conducted with 32 students (grades 2–5) in the program, and 222 arts-based artifacts along with 69 field note entries were collected through weekly observations. Visual and thematic analyses of the data revealed that many children embraced plurilingualism, took pride in their transnational and religious identities, and expressed motivation to become language teachers and cultural brokers. Despite these successes, resistance to plurilingualism, limitations in the available tools, and tensions within the program’s power structure persisted. The findings highlight the potential of design-based research and CHAT and offer important implications for integrating arts-based, plurilingual, and multimodal designs into literacy activities that can challenge persistent monolingual practices in schools.
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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 | 0.008 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.010 | 0.028 |
| Scholarly communication | 0.010 | 0.004 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.001 | 0.001 |
| 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".