Identity in Resettlement: Perspectives of Female Refugee Lone Parents from Africa
Bibliographic record
Abstract
The purpose of the current study was to explore how the identities of women from Africa who are resettled in Canada as refugee lone parents might be influenced by the resettlement experience. There is extensive research on resettlement outcomes for newcomers (Frank, 2013; Guo, 2013; Painter, 2014; Schwartz et al., 2010), including those resettled as refugees (George, 2012; Huijts, et al, 2012; Teixiera & Dias, 2018), but not much is known about what happens to individuals' identity as they settle in the new countries. Given this, I explored identity change in the context of resettlement for this specific class of refugees, by asking the question: How do refugee single mothers from Africa make sense of how their identities have changed or remained the same in the context of settling in Canada? In conducting this study, I was guided by a qualitative research method, Interpretative Phenomenological Analysis (IPA; Smith, Larkin, and Flowers; 2009). Using purposive and snowball sampling, I recruited nine women living in two major urban centres in Alberta, who met criteria for participation. I conducted audio-taped, in-depth, semi-structured interviews with each, in either Kiswahili or English. I translated and transcribed the ones in Kiswahili to English and transcribed the ones in English verbatim. Following this, I analyzed the data according to IPA procedures (Smith et al, 2009). Through this process, I created five super-ordinate themes related to identities that remained the same; that had been lost; that were acquired in resettlement; that might change in the future; and that others might use to describe this population. The findings are explained and discussed in the context of relevant literature. Strengths and limitations of the study are considered as well as implications of the findings for research, policy, and the practice of counselling with this population.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.021 | 0.013 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 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".