Moving from China to Canada: Occupational Transitions of Immigrant Mothers of Children with Special Needs
Bibliographic record
Abstract
Introduction: Chinese immigrants to Canada bring a set of values and beliefs that influence the way they experience the world. Some are mothers with children with special needs. These women face the difficult process of transitioning into a new culture and society along with caring for a child with special needs. Objectives: To gain an in-depth understanding of the experiences and occupations of Chinese mothers of children with special needs who have immigrated to Canada. Methods: This descriptive phenomenological study used semi-structured interviews as the principal means of collecting data from three immigrant mothers with children with special needs who were born in China or Hong Kong. Results: Three themes were identified: 1) Change in types of caregiving occupations and stressors with immigration, 2) Parenting responsibilities shape personal and family life and occupations, and 3) Occupational changes associated with caregiving and immigration influence personal and family well-being. Conclusion: Occupational choices and engagement were based on the sense of duty and responsibility to their children. Chinese immigrant mothers made significant life changes regardless of their own and their family's well-being in the interest of their children's development and quality of life.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.008 | 0.002 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".