“There's nothing to read here…the newspaper is <i>cho cá</i>, for the fish!”: A Young Refugee‐Background Child Brokering Languages, Literacies, and Cultures as a Caring Multiliterate Practice
Bibliographic record
Abstract
ABSTRACT This article shares stories of seven‐year‐old Anh, participating in brokering practices to support his mother at home as a caring multiliterate practice. We contextualize brokering as complex linguistic, cultural, social, and pragmatic negotiations, and emphasize the particularities and complexities of this affective labor that many children from immigrant and refugee backgrounds routinely undertake for their families and friends. Using perspectives of brokering, translanguaging, and multiliteracies, we share stories from a year‐long study and highlight Anh's capacities, care, and agency during brokering experiences. We describe how this young child supports his mother by providing kinship care for many daily tasks; ways that he guides complex cultural conversations for his mom; and also how he agentively resists brokering occasionally. Our analysis also emphasizes how intersectional inequities complicate the practice for Anh and his mother, and how he creatively communicates across languages, cultures, modes, and dominant white systemic expectations. Anh's stories highlight how an emergent bilingual's school literacies might appear to lag behind his peers while in reality he was performing complex and invisible multiliterate work at home. Valuing child brokering shifts attention to the profound capacities of young racialized children in understanding, mediating, and bridging the words, ideas, feelings, and actions of and for others. Implications center on systemic responsibilities to listen to children and family stories and recognize the significant language and literacy capacities that students demonstrate when brokering. In interpreting interactional and communicative forms with linguistic agency, affective competence, and creative problem‐solving, young children like Anh actively participate in translating cultures and navigating borders.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.017 | 0.007 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".