<i>She Shuts Her English Channel in Her Brain:</i> Racial and Linguistic Ordering during Kindergarten Practicums
Bibliographic record
Abstract
During their kindergarten placements, teacher candidates are learning to teach with young children who may be experiencing linguistic and racial hierarchies in a formal institutional setting for the first time. The purpose of this research is to understand how teacher candidates make sense of the socially constructed boundaries of language and race in their practicum placements in kindergarten classrooms. In our critically informed inquiry, we draw on translanguaging and LangCrit to understand the process of language teaching and learning in kindergarten classrooms. The three teacher candidates in this article, Yu, Fie, and Charlotte, took a required course on supporting multilingual students in the mainstream classroom as part of their requirement to become Primary/Junior (K–6) teachers and were interviewed on their experiences with multilingual children during their practicums. Four major themes were found in the data: language hierarchies during practicums, subverting language hierarchies, translanguaging with families, and racialized experiences of speaking Mandarin. Much more than other grade-level placements, kindergarten placements were spaces where the candidates witnessed communication break down, with families and children refusing to speak English.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".