Telling it Like it is? Constructing accounts of settlement with immigrant and refugee women in Canada
Bibliographic record
Abstract
This article reflects on the methodology of a study of immigrant and refugee women's settlement experiences in Vancouver, Canada. It specifically takes up the ways in which the women's accounts were co‐constructed through social and political processes and relations operating at different geographical scales, but were experienced at the local scales of body, home and neighbourhood. The study consisted of in‐depth interviews with 16 immigrant and one refugee woman and their teenaged daughters. Here we focus on the mother's accounts showing how their story‐telling of life since coming to Canada was framed by multiple discourses and local material conditions. We use two case examples from the study to raise substantive issues in the research, focusing particularly on the women's talk of work and health and how these framed their understanding of ‘womanhood’ in Canada, routes to a desired ‘integration’ and their daily practices. Their quotidian life embodied their multiple identities as women, mothers, wives, workers and immigrants and the interviews were used by them to express the frustrations and hardships which were in direct contradiction to their expectations as ‘desirable’ immigrants or refugees under protection. We argue that methodological reflection is not simply an important dimension of rigour in feminist qualitative research, but is also critical to the opening up of taken‐for‐granted categories brought to the politically charged study/construction of ‘the other’. In this research the identities of study participants and researchers, in the specific space of the interview, were intricately involved in ‘telling it like it is’ for these immigrant and refugee women settling in an outer suburb of one of the three major destination cities for immigrants to Canada.
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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 | 0.007 | 0.013 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.060 | 0.036 |
| Scholarly communication | 0.014 | 0.004 |
| Open science | 0.005 | 0.015 |
| Research integrity | 0.004 | 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".