Projections of white and black older adults without living kin in the United States, 2015 to 2060
Bibliographic record
Abstract
Close kin provide many important functions as adults age, affecting health, financial well-being, and happiness. Those without kin report higher rates of loneliness and experience elevated risks of chronic illness and nursing facility placement. Historical racial differences and recent shifts in core demographic rates suggest that white and black older adults in the United States may have unequal availability of close kin and that this gap in availability will widen in the coming decades. Whereas prior work explores the changing composition and size of the childless population or those without spouses, here we consider the kinless population of older adults with no living close family members and how this burden is changing for different race and sex groups. Using demographic microsimulation and the United States Census Bureau's recent national projections of core demographic rates by race, we examine two definitions of kinlessness: those without a partner or living children, and those without a partner, children, siblings, or parents. Our results suggest dramatic growth in the size of the kinless population as well as increasing racial disparities in percentages kinless. These conclusions are driven by declines in marriage and are robust to different assumptions about the future trajectory of divorce rates or growth in nonmarital partnerships. Our findings draw attention to the potential expansion of older adult loneliness, which is increasingly considered a threat to population health, and the unequal burden kinlessness may place on black Americans.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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 | 0.001 |
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".