Midlife Transition Experiences of South Asian Immigrant Women in Canada: A Qualitative Exploration
Bibliographic record
Abstract
BACKGROUND: South Asians make up a significant portion of the immigrant population in Canada, and a large portion of them are in their midlife. To improve the midlife transition of South Asian immigrant women, it is necessary to understand their lived experiences. PURPOSE: Guided by the transition theory, this study investigates the midlife experiences of South Asian immigrant women in Canada. METHODS: Twenty-two South Asian midlife, immigrant women were recruited to participate in this study from the Greater Toronto Area, Ontario, Canada. This study consisted of one asynchronous online focus group with 12 participants and ten one-on-one telephone interviews. Qualitative content analysis was guided by transition theory. RESULTS: South Asian immigrant women experienced many different transitions in their midlife in Canada. These transitions included changes in their (a) lifestyle, (b) career, (c) family, (d) physical health, (e) mental health, (f) social, (g) environment, and (h) personal development. Women actively managed their transitions using strategies such as exercise, socialization, counseling, and religion. Women expressed the need for social, community, and governmental support to facilitate their midlife transitions. CONCLUSION: To promote healthy midlife transition, governments need to create better employment policies to facilitate immigrant women settlement, transferring skills, and re-employment in Canada. In addition, health care and community services to promote physical and mental health should be emphasized.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.021 | 0.006 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.005 |
| 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".