Ageing, Social Distancing, and COVID-19 Risk: Who is more Vulnerable?
Bibliographic record
Abstract
Perceived social support represents an important predictor of healthy ageing. The global COVID-19 pandemic has dramatically changed the face of social relationships and exposed elderly as a particularly vulnerable population. Social distancing may represent a double-edged sword for older adults, protecting them against COVID-19 infection while also sacrificing personal interaction and attention at a critical time. Here, we consider the moderating role of social relationships as a potential influence on stress resilience, allostatic load, and vulnerability to infection and adverse health outcomes in the elderly population. Understanding the mechanisms how social support enhances resilience to stress and promotes mental and physical health into old age will enable new preventive strategies. Targeted social interventions may provide effective relief from the impact of COVID-19-related isolation and loneliness. In this regard, a pandemic may also offer a window of opportunity for raising awareness and mobilizing resources for new strategies that help build resilience for our ageing population and future generations.
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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 | 0.005 |
| 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 | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".