Spatial Distance Between Parents and Adult Children in the United States
Bibliographic record
Abstract
OBJECTIVE: This brief report presents contemporary national estimates of the spatial distance between residences of parents and adult children in the United States, including distance to one's nearest parent and/or adult child and whether one lives near all of their parents and adult children. BACKGROUND: The most recent national estimates of parent-child spatial proximity come from data for the early 1990s. Moreover, research has rarely assessed spatial clustering of all parents and adult children. METHOD: Data are from the 2013 Panel Study of Income Dynamics on residential locations of adults 25 and older and each of their parents and adult children. Two measures of spatial proximity were estimated: distance to nearest parent or adult child, and the share of adults who have all parents and/or adult children living nearby. Sociodemographic and geographic differences were examined for both measures. RESULTS: Among adults with at least one living parent or adult child, a significant majority (74.8%) had their nearest parent or adult child within 30 miles, and about one third (35.5%) had all parents and adult children living that close. Spatial proximity differed substantially among sociodemographic groups, with those who were disadvantaged more likely to have their parents or adult children nearby. In most cases, sociodemographic disparities were much higher when spatial proximity was measured by proximity to all parents and all adult children instead of to nearest parent or nearest adult child. CONCLUSION: Disparities in having all parents and/or adult children nearby may be a result of family solidarity and also may affect family solidarity. This report sets the stage for new investigations of the spatial dimension of family cohesion.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".