From Generation to Generation: The Role of Grandparents in the Intergenerational Transmission of (Non-)Voting
Bibliographic record
Abstract
The literature on the reproduction of political participation across generations has focused almost exclusively on parental effects. Yet, other family members may plausibly play an important role as well. This study explores the role of grandparents in the intergenerational transmission of the propensity to vote. Grandparental effects are theorized in terms of both social learning and status transmission. The analysis takes advantage of a unique dataset that links official turnout data for grandparents, parents, and adult grandchildren with demographic and socioeconomic information from administrative sources. Even controlling for a variety of status-related characteristics, grandchildren are significantly less likely to vote when their grandparents are non-voters. The association between grandparental turnout and the turnout of their adult grandchildren is only partly explained by the mediating effect of parental turnout. Having non-voting grandparents appears to reinforce the effect of having parents who do not vote and may even offset the effects of having parents who are both voters. These results suggest that it is time to take the role of grandparents seriously if we want to understand how political disadvantage is transmitted across 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 | 0.002 | 0.009 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".