SINGLE-TIE CORE NETWORKS AMONG OLDER EUROPEANS: A POSITION OF PRECARITY AND LONELINESS?
Bibliographic record
Abstract
Abstract The problems of late-life social isolation and loneliness prompt significant concern. Individuals who have core personal networks limited to a single connection may be especially susceptible to loneliness, particularly when that connection is no longer available. The present research considers: 1) how prevalent such single-tie networks are and who is most likely to embed in them; 2) whether older adults in single-tie networks are more lonely than people with more expanded network forms; and 3) whether such networks put people at highest of loneliness in the event of network member loss. Using ego-centric network data from Waves 4 (2011) and Wave 6 (2015) of the Survey of Health, Ageing, and Retirement in Europe (SHARE), we conduct lagged dependent variable logistic regressions. Results show that a total of 28.2% of older Europeans rely on a single person as an important personal tie. Among those maintaining a single-tie network, spouses are the most common choice (62.4%), followed by a child (15.2%), a relative (8.5%), and a non-relative (13.8%). Factors significantly associated with holding different types of single-tie networks include age, gender, education, financial pressure, rural residence, participation in social activities, and grandparental roles. Child-only networks are significantly associated with greater levels of loneliness compared to multi-tie networks. Meanwhile, the loss of a partner as the only connection is associated with significantly increased loneliness, even after considering possible network additions. Future research should investigate how to better protect older adults in precarious network settings, especially during network losses.
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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".