Age-Related Patterns in Social Networks among European Americans and African Americans: Implications for Socioemotional Selectivity across the Life Span
Bibliographic record
Abstract
Socioemotional selectivity theory contends that as people become increasingly aware of limitations on future time, they are increasingly motivated to be more selective in their choice of social partners, favoring emotionally meaningful relationships over peripheral ones. The theory hypothesizes that because age is negatively associated with time left in life, the social networks of older people contain fewer peripheral social partners than those of their younger counterparts. This study tested the hypothesis among African Americans and European Americans, two ethnic groups whose social structural resources differ. Findings confirm the hypothesis. Across a wide age range (18 to 94 years old) and among both ethnic groups, older people report as many emotionally close social partners but fewer peripheral social partners in their networks as compared to their younger counterparts. Moreover, a greater percentage of very close social partners in social networks is related to lower levels of happiness among the young age group, but not among the older age groups. Implications of findings for adaptive social functioning across the life span are discussed.
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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 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".