Inequality and Social Ties: Evidence from 15 U.S. Data Sets
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
What is the relationship between inequality and social ties? Do personal networks, group memberships, and connections to social resources help level the playing field, or do they reinforce economic disparities? We examine two core empirical issues: the degree of inequality in social ties and their consolidation with income. Using 142,000 person-wave observations from 15 high-quality U.S. data sets, we measure the quantity and quality of social ties and examine their distribution. Our findings show that (1) the Gini coefficient for social ties often exceeds that of income and (2) social ties are concentrated among those with the highest incomes. We introduce an overall inequality–consolidation curve, demonstrating that social ties generally reinforce economic inequality. However, we identify one key exception: there is no class gradient in the use of social ties for job search. These findings contribute to debates about the role of social ties in perpetuating or mitigating inequality.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.007 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it