Unaccompanied minors: illuminating transcultural support practices for the benefit of pedagogical intervention and teacher training
Bibliographic record
Abstract
In Québec as in France, young people who meet the administrative definition of unaccompanied minors (UAMs) are foreign minors without a legal representative in the host/settlement country. Their backgrounds and the reasons for their departure are heterogeneous (Étiemble, 2010), and in Québec, little research has focused on their lived realities, particularly concerning how schools that receive them treat their experiences. As part of an exploratory project conducted in France (Audet et al., 2024) with professionals working with UMAs as part of a transcultural reception system, three stories of practice (Desgagné, 2005) were collected. A thematic analysis by mixed coding (Mucchielli, 2009) of these stories of practice allowed us to identify five central dimensions that can benefit the process of supporting and guiding UAMs. We then discuss how these documented practices can inform the initial training and continuing education of teachers in their relationships/interventions with UMA.
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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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.015 | 0.013 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| 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".