Professional perspectives: The educational experiences of Mexican refugee claimant children in Montreal
Bibliographic record
Abstract
This thesis is based on the schooling experiences of Mexican elementary school refugee claimant children in Montreal, Quebec, Canada. It gathers perspectives from professionals who support them through the refugee determination process, including three teachers, a social worker, and an immigration lawyer. From an educational standpoint, the research questions examine the adaptation process, the cultural and linguistic barriers affecting students’ schooling experience, and the resources available to teachers. I interviewed participants at their workplace, allowing them to express their experiences of working with Mexican refugee claimant families and their children with specific reference to the children’s schooling experiences and performance in school. The research shows that refugee claimant families are subject to severe amounts of stress due to their traumatic past and uncertain future. This affects all family members; children bring this stress to school, evidently affecting their performance and general involvement at school. All respondents suggest that the children’s academic success depends on the family and the importance the family attaches to education. Teachers also believe that the lack of knowledge of the French language poses roadblocks for these children’s learning. The recommendations stemming from this research include the need to create an umbrella organisation that would provide information directly to teachers regarding this specific population and the importance of Canadian professionals building trustworthy relationships with these families. This timely research can provide information to policymakers, teachers, and other professionals involved with the refugee determination process, and future research, thus contributing to a healthier multicultural Quebec society.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| 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 | 0.005 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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".