Are older adults networked individuals? Insights from East Yorkers’ network structure, relational autonomy, and digital media use
Bibliographic record
Abstract
Networked individualism is a critical concept about the transition of the societal shift from geographically bounded local groups to the contemporary network society comprised of sparse, permeable, and dynamic communication networks. An underlying assumption about networked individuals thus far in the literature is that they are at a younger age. There are fears that older adults have been left behind in this transition to networked individualism. In this study, we are the first to inquire to what extent ‒ and in what ways ‒ are older adults networked individuals. Using in-depth interviews with 41 older adults living in the East York area of Toronto, we used a combination of quantitative coding, thematic analysis, and individual profiling to analyze their social network structure, relational autonomy, and digital media use. Our findings render a rather complex and nuanced picture, showing three types of older adults along the spectrum of networked individualism: networked individuals, socially connected but not networked individuals, and socially constrained individuals. Although most participants are socially connected, those who are networked individuals actively manage and navigate multiple, diverse, and non-redundant social networks. Digital media use is neither necessary nor sufficient in qualifying a person as a networked individual as the great majority of East Yorkers ‒ even if not networked individuals ‒ integrate digital media into their everyday lives.
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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 | 0.002 | 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 | 0.004 | 0.004 |
| Scholarly communication | 0.002 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".