Squeezed In: The Intersecting Paradoxes of Care for Immigrant Informal Caregivers
Bibliographic record
Abstract
While the feasibility of maintaining informal care for older adults is a growing concern for many Canadians, support is not the same for everyone. The situation for immigrants is even more precarious because of their unique social locations. They find themselves squeezed into a system that neither reflects their realities nor addresses their needs. This thesis argues that, due to their multiple marginalities as gendered and racialized newcomers, immigrant informal caregivers lack needed resources in caring for aging family, friends, and neighbours. It also argues that mainstream home care and long-term care providers face challenges in caring for older immigrants because health care provision for older adults was not developed to advance immigrant interests. To develop this argument in an empirically grounded way, I use a theoretical framework combining feminist theories of care work and intersectionality theories in order to analyze a series of semi-structured interviews with informal immigrant and Canadian-born caregivers, as well as management and staff in home care and four long-term care facilities in Southern Ontario. \n \nThe results show that immigrant informal caregivers in Southern Ontario face challenges in accessing supports, services, and resources because of the gendered nature of care work and their immigrant social locations. My research indicates that many immigrant informal caregivers experience a burden as a result of taking on the caregiver role, often squeezed between the expectations of care from their home countries and the demands of caregiving in a Canadian context. Moreover, when informal care can no longer be provided by immigrant informal caregivers in the home, a host of systemic barriers restrict access to, and accommodation in, long-term care facilities. The dissertation concludes by demonstrating how proposed improvements in the delivery of long term care facilities are contingent on formal service providers being respectful, reflective, and responsive to the diversities among immigrants (‘inclusion’), rather than fitting them into existing mainstream programs (‘integration’). In doing so, this dissertation adds to the sociology of care by reinforcing a multidimensional approach for accommodating complex diversities in ways that are workable, necessary and inclusive.
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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 | 0.011 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.039 | 0.044 |
| Scholarly communication | 0.014 | 0.009 |
| Open science | 0.003 | 0.018 |
| Research integrity | 0.003 | 0.005 |
| 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".