partisan_metrics {redist}R Documentation

Calculate gerrymandering metrics for a set of plans

Description

redist.metrics is used to compute different gerrymandering metrics for a set of maps.

Usage

partisan_metrics(map, measure, rvote, dvote, ..., .data = cur_plans())

redist.metrics(
  plans,
  measure = "DSeats",
  rvote,
  dvote,
  tau = 1,
  biasV = 0.5,
  respV = 0.5,
  bandwidth = 0.01,
  draw = 1
)

Arguments

map

a redist_map object

measure

A vector with a string for each measure desired from list "DSeats", "DVS", "EffGap", "EffGapEqPop", "TauGap", "MeanMedian", "Bias", "BiasV", "Declination", "Responsiveness", "LopsidedWins", "RankedMarginal", and "SmoothedSeat". Use "all" to get all metrics. "DSeats" and "DVS" are always computed, so it is recommended to always return those values.

rvote

A numeric vector with the Republican vote for each precinct.

dvote

A numeric vector with the Democratic vote for each precinct.

...

passed on to redist.metrics

.data

a redist_plans object

plans

A numeric vector (if only one map) or matrix with one row for each precinct and one column for each map. Required.

tau

A non-negative number for calculating Tau Gap. Only used with option "TauGap". Defaults to 1.

biasV

A value between 0 and 1 to compute bias at. Only used with option "BiasV". Defaults to 0.5.

respV

A value between 0 and 1 to compute responsiveness at. Only used with option "Responsiveness". Defaults to 0.5.

bandwidth

A value between 0 and 1 for computing responsiveness. Only used with option "Responsiveness." Defaults to 0.01.

draw

A numeric to specify draw number. Defaults to 1 if only one map provided and the column number if multiple maps given. Can also take a factor input, which will become the draw column in the output if its length matches the number of entries in plans. If the plans input is a redist_plans object, it extracts the draw identifier.

Details

This function computes specified compactness scores for a map. If there is more than one precinct specified for a map, it aggregates to the district level and computes one score.

Value

A tibble with a column for each specified measure and a column that specifies the map number.

References

Jonathan N. Katz, Gary King, and Elizabeth Rosenblatt. 2020. Theoretical Foundations and Empirical Evaluations of Partisan Fairness in District-Based Democracies. American Political Science Review, 114, 1, Pp. 164-178.

Gregory S. Warrington. 2018. "Quantifying Gerrymandering Using the Vote Distribution." Election Law Journal: Rules, Politics, and Policy. Pp. 39-57.http://doi.org/10.1089/elj.2017.0447

Samuel S.-H. Wang. 2016. "Three Tests for Practical Evaluation of Partisan Gerrymandering." Stanford Law Review, 68, Pp. 1263 - 1321.

Gregory Herschlag, Han Sung Kang, Justin Luo, Christy Vaughn Graves, Sachet Bangia, Robert Ravier & Jonathan C. Mattingly (2020) Quantifying Gerrymandering in North Carolina, Statistics and Public Policy, 7:1, 30-38, DOI: 10.1080/2330443X.2020.1796400

Examples

data(fl25)
data(fl25_enum)
plans_05 <- fl25_enum$plans[, fl25_enum$pop_dev <= 0.05]
# old: redist.metrics(plans_05, measure = "DSeats", rvote = fl25$mccain, dvote = fl25$obama)
part_dseats(plans_05, fl25, mccain, obama)


[Package redist version 4.2.0 Index]