From 720217eeaf5b56fbc7337056f3f663731f66970a Mon Sep 17 00:00:00 2001 From: Todd Hendricks Date: Tue, 16 Nov 2021 15:20:49 -0800 Subject: [PATCH] add descriptive text to readme to provide more context about racially polarized voting --- README.md | 10 +++++----- 1 file changed, 5 insertions(+), 5 deletions(-) diff --git a/README.md b/README.md index 14ce41a..0447de7 100644 --- a/README.md +++ b/README.md @@ -2,12 +2,12 @@ [![DOI](https://joss.theoj.org/papers/10.21105/joss.03397/status.svg)](https://doi.org/10.21105/joss.03397) -PyEI is a Python library for ecological inference. +PyEI is a Python library for ecological inference. The target audience is the analyst with an interest in the phenomenon called Racially Polarized Voting. -An important question in some voting rights and redistricting litigation in the U.S. is whether and to what degree voting is racially polarized. -In the setting of voting rights cases, the family of methods called "ecological inference" uses -observed data, pairing voting outcomes with demographic information -for each precinct in a given polity, to infer voting patterns for each demographic group. +Racially Polarized Voting is a legal concept developed through case law under the Voting Rights Act of 1965; its genesis is in the majority opinion of ***Thornburg v. Gingles (1982)***. Considered the “evidentiary linchpin” for vote dilution cases, RPV is a necessary, but not sufficient, condition that plaintiffs must satisfy for a valid claim. + +Toward that end, ecological inference uses observed data (historical election results), pairing voting outcomes with demographic information +for each precinct in a given polity, to infer voting patterns for each demographic group. PyEI brings together a variety of ecological inference methods in one place and facilitates reporting and plotting results; quantifying the uncertainty associated with results under a given model; making comparisons between methods; and bringing relevant diagnostic tools to bear on ecological inference methods.