Remixing images, words, and ideas: Young emergent bilinguals composing remixed countertexts as a creative, relational, and decolonizing practice
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Sharing multimodal creations of four young racialized multilingual learners from a year-long education design research project, this paper argues that remixing and repurposing are decolonizing practices through which marginalized children create countertexts. Anh, Jordan, Sarah, and Kimi – children categorized as English language learners (ELLs) in a Grade 2/3 Western Canadian classroom – expertly designed countertexts using popular and digital culture, remixed drawings, and storied responses to mentor texts and classroom activities. Framed by perspectives of multiliteracies and culturally sustaining pedagogies, these remixed countertexts highlight non-dominant perspectives and bring young children’s diverse knowledges into the official space of the classroom.Thematic and visual analysis of the children’s oral, written, and visual countertext data highlights languages and literacies as relational practices; remixing as a creative composing process for emergent bilinguals; and remixed countertexts’ potential for supporting decolonial and antiracist reimaginations of emergent bilinguals’ participation and achievement. While individual and original productions are often most valued within Western educational systems, the creative processes that accompany borrowing, copying, and remixing in countertexts can transform language, texts, and practices as they are flexibly re-purposed and re-sourced. A critical appreciation of remixed countertexts encourages educators to resist normative and narrow conceptions of literacy, consider White middle-class subtexts, challenge colonial ideas of composition, and design collaborative, decolonizing, and antiracist pedagogies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it