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Michigan legislative district compactness

With planning for the Michigan redistricting commission underway, in class we are discussing ways of assessing compactness and partisan wasted votes along with the corresponding ‘efficiency gap’ (Stephanopoulos and McGhee 2015). A recent article by Kaufman, King, and Komisarchik (2018,  http://j.mp/2jNf1Jl ) on a survey based method to judge compactness includes an R package, “compactness” ( https://github.com/aaronrkaufman/compactness ), to calculate several traditional compactness scores along with the survey method proposed in the article. We used the package to compare compactness scores for district lines in Michigan. Here I review the results, contrasting compactness scores across Michigan State House, Senate, and U.S. House districts. In a subsequent post I will compare these scores to the partisan symmetry of the districts. The compactness package is available via devtools and github: #devtools::install_github("aaronrkaufman/compactness") library (compactness)
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Using the survey package in R to analyze the European Social Survey, part 2

Using the survey package in R to analyze the European Social Survey, part 2 Recoding the party support measure We copy paste the old labels and type the new: ess8_at<-ess8_at  %>%    mutate ( at_party_vote =   fct_recode (prtvtbat,      "Social Democratic Party SP"  =  "SP \xd6 " ,      "People's Party VP"  =  " \xd6 VP" ,      "Freedom Party FP"  =  "FP \xd6 " ,      "Alliance for the Future of Austria BZ" =  "BZ \xd6 " ,      "The Greens Gr"  =  "Gr \xfc ne" ,      "Communist Party of Austria KP"  =  "KP \xd6 " ,      "New Austria and Liberal Forum NEOS"  =  "NEOS" ,      "Pirate Party of Austria PIRAIT"  =  "Piratenpartei  \xd6 sterreich" ,      "Team Stronach for Austria"  =  "Team Frank Stronach" ,      NULL =   "Other" ,      NULL =   "Not applicable" ,