African, Muslim refugee student teachers’ perceptions of care practices in infant and toddler field placements
Bibliographic record
Abstract
Within the context of the education-care divide in the field, numerous studies have affirmed that preschool teachers feel unprofessional when they assume a caring role yet believe that love and care are central to their work. However, immigrant/refugee teachers may experience this tensionality more acutely since their own cultural beliefs and values about caring for young children are situated outside the authoritative discourse, underpinned by western theories and practices. Framed by sociocultural-historical theory and concepts such as communities of practice, the purpose of this one-year ethnographic study was to enquire into how immigrant/refugee women studying in a Canadian early childhood college programme navigated the interstices between these discourses. Qualitative data were collected through field notes, spatial mapping, interviews, focus groups, and artefacts/documents. This article focuses on disjuncture between the cultural and religious understandings of care that five African, Muslim refugee women brought to their field placements in infant/toddler classrooms and the authoritative professional expectations, as related to mealtime practices. The findings elucidated how they interpreted care not only as a means of ensuring children’s health and well-being, but also as a means of teaching religious and cultural values.
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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 | 0.001 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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".