« J’avais peur, mais maintenant, c’est chez moi » : parcours de femmes réfugiées en situation monoparentale à Montréal
Bibliographic record
Abstract
Research Framework: The number of displaced people in the world now stands at 82.4 million. The UN Refugee Agency (UNHCR) remains critical of the low quotas granted to refugees in Canada and since 2018 one of its recommendations has been to prioritize vulnerable populations, in particular single women with children, who are at the heart of this research. In the context of forced migration, being a single mother often rhymes with precarity, instability and socio-economic inequalities, which have all been dramatically multiplied with the pandemic. Objectives: The objective is to examine the strategies these women put into place to anchor themselves in Quebec society, and to face the daily challenges in their lives. Methodology: The article is based on data collected through semi-structured interviews with Montreal-based single refugee mothers. Results: These mothers find themselves juggling between tumultuous emotions, daily challenges, and familial responsibilities. Their journeys illustrate the ways in which resilience and agency intersect in the management of family dynamics as well as in settlement experiences. Conclusions: Family transformations and the challenges of forced migration push refugee mothers to rebuild not only their home, but also their individuality as women and mothers, which challenges the often-reductive perspectives on motherhood and resilience. Contribution: The results presented allow to nuance the concepts of resilience and agency while highlighting their ambivalence and their complexity. They also reveal the ways refugee mothers rebuild their lives after experiencing forced migration.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 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) | 0.005 | 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".