Solitude in context: On the role of culture, immigration, and acculturation in the experience of time to oneself
Bibliographic record
Abstract
Older adults spend much time in solitude (without social interaction), putting them at risk of loneliness, especially if aging outside their country of origin (e.g., Chinese immigrants to Canada). Yet, cultural contextual factors that may reduce loneliness in moments of solitude are poorly understood. This study sought to disentangle the roles of culture, immigration, and acculturation in solitude-loneliness associations across two countries. Community-dwelling adults aged 51-85 in Vancouver (N = 58 East Asian, N = 37 European/North American) and in Hong Kong (N = 56 East/Southeast Asian) completed approximately 30 ecological momentary assessments over 10 days on their current affect and social situations. Participants in Vancouver spent more time in solitude, desired solitude more, and felt less lonely overall than those in Hong Kong. Multilevel models revealed that moments of solitude felt lonelier than moments spent in social interaction, but only for individuals less acculturated to their host culture or not concurrently desiring solitude. Associations held regardless of host culture, cultural heritage, or immigration status. Findings suggest that solitude need not feel lonely if it happens by choice and if individuals feel connected with their host culture, for both immigrant older adults and those aging in their birth country.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 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".