Am I Eligible to Register? Registration Rules, Eligibility Uncertainty, and Youth Voter Turnout
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
Abstract Is a lack of information about eligibility rules partly responsible for the particularly low youth voter turnout in U.S. elections? In a context where new voters usually have to register several weeks before Election Day and where registration rules vary by state, this article argues that there is substantial uncertainty among young Americans about their eligibility to register and vote in elections. It uses a natural experiment that leverages the as-if random assignment of a person’s 18th birthday around a state registration deadline to identify the causal effect of uncertainty about whether someone has to be 18 by the registration deadline or by Election Day to register and vote in an election on youth voter turnout. Drawing on fine-grained data from 19 U.S. state voter files, the study finds a sharp discontinuity in turnout in nine states. There are smaller or no effects in states with same day registration, a later registration deadline closer to Election Day or explicit information that 17-year-olds are eligible to register. Moreover, the effect persists over time, with people who are discouraged from voting due to eligibility uncertainty significantly less likely to vote in future elections. These findings have important implications for our understanding of youth turnout, election reforms, habit formation, and the study of citizens’ information and beliefs about electoral rules with administrative data.
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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