A Place to Call Home: Stories of a Young Refugee-Background Child Navigating Classroom, Marginal, and Neighbourhood Places
Bibliographic record
Abstract
This article explores the experiences of Anh, a seven-year-old refugee-background child, focusing on his meaning-making and identities in place. Place-based literacies highlight how location supports children in revealing and reimagining their worlds. From a Multiliteracies perspective, I highlight places as texts—spatial, material, visual, and affective, imbued with ideologies and offering meaning through relational experiences.Using narrative inquiry, I share Anh’s stories—moving from small classroom places like his desk and the Reading Nook; to the playground and the Resource Room; to his home and neighborhood—showcasing how places reflected his ways of knowing and being. As he traverses each place, I discuss that he became increasingly more creative in his language and literacy practices, incorporated his communicative repertoires, and created belonging for himself.Anh’s journeying is interpreted as: (1) Navigating White ways of listening within classroom places; (2) Creating new worlds in marginal places; and (3) Being and becoming at home. Pedagogical implications focus on listening for brilliance as young refugee-background children navigate normative school places and creating multiliterate relational practices to support situated meaning-making.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.017 | 0.015 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.003 | 0.012 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.003 | 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".