Skip to content

Using alignment algorithms to measure similarity of US state bills

Notifications You must be signed in to change notification settings

desmarais-lab/text_reuse

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Measuring Policy Similarity through Bill Text Reuse

Publication: Linder F., Desmarais B., Burgess M., Giraudy E. (2018): Text as Policy: Measuring Policy Similarity Through Bill Text Reuse. Policy Studies Journal. https://onlinelibrary.wiley.com/doi/abs/10.1111/psj.12257

Abstract

The identification of substantively similar policy proposals in both proposed and adopted legislation is important to scholars of public policy diffusion and legislative politics. Conventional, manual, approaches are prohibitively costly in constructing datasets that accurately represent policymaking across policy domains, jurisdictions, or time. We propose the use of text-sequencing algorithms, applied to legislative text, to identify bills that introduce similar policy proposals. We present three ground truth tests, applied to a corpus of 500,000 bills from US-state legislatures. First, we show that bills introduced by ideologically similar sponsors are more likely to exhibit a high degree of text reuse. Second, we show that bills classified by the National Conference of State Legislatures as covering the same policies exhibit a high degree of text re-use. Third, we show that rates of text reuse across state borders correlate with the diffusion networks recently introduced by Desmarais, Harden and Boehmke (2015).

Replication

See the makefile for concrete replication steps. The original data is available here: https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi%3A10.7910%2FDVN%2FCZ25GF

About

Using alignment algorithms to measure similarity of US state bills

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published