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Senior Honors Thesis · 2026
Method
- Constitutional Vacuum Diffusion
- Computational Text Analysis
- TF-IDF Vectorization
- OLS Regression
- Policy Diffusion Theory
Networks of Influence: Legislative Text Diffusion in State Abortion Policy After Dobbs
This thesis examines how abortion-related legislation diffused across U.S. states in the first full legislative year after Dobbs v. Jackson Women’s Health Organization (2022). Drawing on a corpus of 188 enacted bills across 46 states, it uses compu- tational text analysis—TF–IDF cosine similarity computed across 104,445 unique n-grams—together with bill-level and dyadic regression to identify the structural pre- dictors of textual convergence.
Key Findings
Three findings invert conventional expectations. First, protective coalitions, not restrictive ones, deployed standardized legislative templates most aggressively in 2023: protective bills are significantly less novel than neutral bills (β=−0.076, p= 0.022), while restrictive bills are statistically indistinguishable from the neutral baseline. Second, the highest textual convergence across state lines coexists with a near-complete absence of direct PAC contributions between coordinated legislators, indicating that diffusion operates through informational rather than financial channels. Third, at the state-pair level, shared advocacy organization co-presence (PAC Jaccard β = +0.039, p < 0.001) and shared protective coalition membership (β = +0.037, p<0.001) predict textual similarity while geographic contiguity is null (β = +0.003, p= 0.734).