Syrian refugee women in Winnipeg: their lives and experiences with resettlement
Bibliographic record
Abstract
The assumption that war related migration and resettlement are primarily characterized by a life of harsh realities with negative outcomes has guided the development of much research and many newcomer support programs. The purpose of this qualitative study is to use semi-structured individual interviews to examine and document how three Syrian refugee women, SRW, experience war, displacement, and resettlement and its impact on their psychological well-being. The goal is to give voice to under-represented SRW, gaining a deeper understanding of how they adjust to a new environment as refugees. This study has explored the main research question: What is it like to be a Syrian refugee woman in Winnipeg? An interpretative analysis revealed five super ordinate themes; The Matriarch - existential reality as an opportunity for growth, hopes and dreams about ‘the good life’, transition through adaptation and renewal, women as healers, and life satisfaction. The data indicated a strength-based approach to settlement as the participants navigated their way through language barriers, grief and loss, and adapting to a new life with courage and resiliency. The implications for future research and counselling training and practice are evidenced by the data of this study. The voices of SRW need to be honoured and heard with compassion and empathy for their struggles while respecting the strength and inner resolve they implement to overcome such struggles to move forward in their new lives. Future researchers and counsellors would do well to be educated in the positive outcomes of refugee settlement, displayed so gracefully within this study.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.009 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| 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".