Alone in a Crowd: Social Isolation, Place, and Connection in Later Life
Bibliographic record
Abstract
The problem of social isolation among older people has been thoroughly documented, studied, and addressed through both policy and social services, and yet persists as a major social issue. There exist several notable gaps within the scholarly literature on isolation, particularly with respect to the role(s) of place-based risk factors, the relationship(s) between exclusion and social isolation, and best practices for isolation interventions. This thesis addresses these knowledge gaps and presents both empirical and theoretical contributions resulting from a three-part investigation. These studies are presented in three distinct papers to constitute a sandwich dissertation. The first paper examines the role of neighbourhood characteristics in shaping social isolation among older people by analyzing the Canadian Longitudinal Study on Aging (CLSA) baseline data in a series of multiple regressions. Findings indicate that the selected neighbourhood characteristics account for only a small portion of the social outcome measures of interest but raise meaningful questions about the intersection of place and social connection that warrant further study. The second paper investigates both the harmful and protective aspects of places in shaping isolation risk through a qualitative study of older people informed by a place-based exclusion lens. Interview results highlight several aspects of places that contribute risk of isolation and are used to adapt the model of known isolation risk factors. The third and final paper analyzes a sample of friendly visiting programs by conducting a realist synthesis to determine how, for whom, and under what conditions friendly visiting programs are most successful. Results of the synthesis are used to build a friendly visiting program theory to be tested in future studies. Together these three papers contribute to both the applied and theoretical literature on social isolation, and can inform the development of future research, policy, and intervention strategies.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| 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".