Embodied Aging: Everyday body practices and Later Life Identities among the South Asian Indian Gujarati Diaspora in Canada
Bibliographic record
Abstract
This study explores how South Asian Indian Gujarati older adults in Canada (Greater Vancouver area) strive to maintain personal continuity, citizenship, and selfhood through everyday body management practices (exercise/yoga, medication/health supplements, skin, and hair care routines) and cultural markers such as food, sartorial choices, and community engagement. This examination, we contend, is noteworthy against the backdrop of contemporary North American academic and popular discourses of a burgeoning consumerist movement around the medicalization of bodies and anti-aging technologies. Drawing on in-depth qualitative interviews of 26 older adults, we discuss how growing old in the diaspora is marked with moral ambivalence between ‘successful aging’ and ‘aging gracefully.’ Based on an inductive thematic analysis, we identify four major themes in how the older diaspora negotiate aging and reorganise their lives through changing social relations and shifting cultural institutions. The first theme is the growing salience of both bodily and social changes in conceptualizing “old age,” and how the experiences of aging vary by gender. Specifically, while most of the female participants visualized old age in terms of a loss of physical functionality, the male participants described agedness in terms of a loss of economic and social worth. The second major theme encapsulates the acceptable coping strategies for dealing with bodily changes and the associated reconfigurations of social roles. While a fit body and functionality were regarded as foundational traits for aging well by all participants, corrective measures or anti-aging products were not espoused as the most culturally appropriate “Indian” way of growing old. The third theme highlights the apprehensions regarding growing old in a foreign country, including a foreboding anxiety of dependence and frailty in the absence of traditional familial care networks. The final theme, explores how for most participants, the notion of home evoked ambivalence in constructing their sense of belonging and identity, often expressed through everyday practices and memory-keeping. Taken together, we ultimately show how age and embodiment are inextricably linked in the experience of growing old in the diaspora.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.016 | 0.005 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| 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".