Intergenerational Voices: Exploring South Asian Multigenerational Living
Bibliographic record
Abstract
The growing prevalence of multigenerational households presents unique opportunities and challenges for families. Cultural values, such as filial piety, play a crucial role in shaping these living arrangements, but there is limited research on the self-reported experiences of individuals within these households, particularly in South Asian communities. This thesis explores the lived experiences of South Asian families residing in multigenerational households in Canada, with a focus on how caregiving, faith, cultural transmission, and generational roles are negotiated within these shared spaces. Drawing on in-depth qualitative interviews across three generational cohorts - young adults, middle-aged adults, and older adults - this research investigates how familial responsibilities, intergenerational dynamics, and cultural values are distributed, challenged, and maintained within these households. Using a life course perspective (Hareven, 1994), the study highlights the ways in which individual transitions (e.g., caregiving, entering the workforce, aging) intersect with the family as a whole. The findings were analyzed using Braun and Clarke’s (2006) six-stage framework for thematic analysis and four key themes were identified. Participants highlighted the emotional and logistical complexities of caregiving in multigenerational homes, the dual role of faith, and the evolving expressions of identity and autonomy across generations. Findings reveal that while multigenerational living can foster emotional support and cultural continuity, it also creates challenges related to generational power dynamics, communication styles, and uneven caregiving burdens. Policy implications underscore the need for culturally sensitive support for migrant families, particularly in navigating caregiving, housing, and integration services. This research contributes to the growing literature on multigenerational living, migration, and family dynamics by offering insights into the everyday negotiations that shape shared households across generations.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.016 | 0.009 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.012 |
| Research integrity | 0.001 | 0.003 |
| 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".