2010 Washington Congressional Districts

[Aneetej]

2010 Washington Congressional Districts

Redistricting requirements

In Washington, districts must according to HCR 4409 (https://apps.leg.wa.gov/billsummary/?BillNumber=4409&Year=2011&Initiative=false):

1. be contiguous
2. have equal populations
3. be geographically compact
4. preserve county and municipality boundaries as much as possible

Interpretation of requirements

We enforce a maximum population deviation of 0.5%. We also used ferry routes in order to create districts linking precincts that are offshore.

Data Sources

Data for Washington comes from the ALARM Project's 2020 Redistricting Data Files.

Pre-processing Notes

As described above, the adjacency graph was modified by hand to reflect Washington's contiguity requirements. The full list of these changes can be found in the '01_prep_WA_cd_2010.R' file.

Simulation Notes

We sample 13,000 districting plans for Washington using the SMC algorithm and thinned the samples down to 5,000. To comply with the federal VRA and to respect communities of interest, we add a weak VRA constraint targeting one majority-minority district (currently WA-09). To balance county and municipality splits, we create pseudocounties for use in the county constraint, which leads to fewer municipality splits than using a county constraint. Note that King County, Pierce County, and Snohomish County must all be split due to their large populations, although within the counties, we avoid splitting any municipality.

Validation

SMC: 5,000 sampled plans of 10 districts on 6,966 units
`adapt_k_thresh`=0.985 • `seq_alpha`=0.5
`est_label_mult`=1 • `pop_temper`=0

Plan diversity 80% range: 0.46 to 0.75

R-hat values for summary statistics:
   pop_overlap      total_vap       plan_dev      comp_edge    comp_polsby      pop_white      pop_black       pop_hisp       pop_aian 
      1.001646       1.001990       1.047810       1.000324       1.016263       1.007529       1.010500       1.003960       1.018536 
     pop_asian       pop_nhpi      pop_other        pop_two      vap_white      vap_black       vap_hisp       vap_aian      vap_asian 
      1.016474       1.029484       1.000878       1.031311       1.017548       1.009942       1.002920       1.018697       1.016003 
      vap_nhpi      vap_other        vap_two pre_16_dem_cli pre_16_rep_tru pre_20_dem_bid pre_20_rep_tru uss_16_dem_mur uss_16_rep_van 
      1.029103       1.000622       1.023141       1.006931       1.001036       1.007730       1.000398       1.011018       1.002541 
uss_18_dem_can uss_18_rep_hut gov_16_dem_ins gov_16_rep_bry gov_20_dem_ins gov_20_rep_cul atg_16_dem_fer atg_16_rep_tru atg_20_dem_fer 
      1.014578       1.000803       1.017507       1.002236       1.005800       1.000463       1.010223       1.002179       1.011421 
atg_20_rep_lar sos_16_dem_pod sos_16_rep_wym sos_20_dem_tar sos_20_rep_wym         adv_16         adv_18         adv_20         arv_16 
      1.000299       1.018101       1.001819       1.017244       1.001672       1.010871       1.014578       1.011348       1.001800 
        arv_18         arv_20  county_splits    muni_splits            ndv            nrv        ndshare          e_dvs         pr_dem 
      1.000803       1.000182       1.012592       1.000323       1.010621       1.000878       1.003832       1.003847       1.010574 
         e_dem          pbias           egap 
      1.003377       1.005177       1.002774 

Sampling diagnostics for SMC run 1 of 2 (6,500 samples)
         Eff. samples (%) Acc. rate Log wgt. sd  Max. unique Est. k 
Split 1     5,577 (85.8%)     12.2%        0.80 4,127 (100%)     16 
Split 2     5,438 (83.7%)     19.2%        0.83 3,953 ( 96%)      9 
Split 3     5,405 (83.1%)     22.0%        0.83 3,850 ( 94%)      7 
Split 4     5,139 (79.1%)     26.1%        0.83 3,820 ( 93%)      5 
Split 5     5,257 (80.9%)     27.4%        0.82 3,822 ( 93%)      4 
Split 6     5,304 (81.6%)     29.1%        0.81 3,773 ( 92%)      3 
Split 7     5,253 (80.8%)     15.6%        0.81 3,734 ( 91%)      6 
Split 8     5,095 (78.4%)     17.1%        0.85 3,529 ( 86%)      4 
Split 9     4,924 (75.7%)      7.0%        0.87 3,091 ( 75%)      3 
Resample    1,550 (23.9%)       NA%        1.00 3,983 ( 97%)     NA 

Sampling diagnostics for SMC run 2 of 2 (6,500 samples)
         Eff. samples (%) Acc. rate Log wgt. sd  Max. unique Est. k 
Split 1     5,576 (85.8%)     13.7%        0.80 4,120 (100%)     14 
Split 2     5,353 (82.4%)     19.3%        0.86 3,932 ( 96%)      9 
Split 3     5,428 (83.5%)     24.2%        0.82 3,897 ( 95%)      6 
Split 4     5,405 (83.2%)     12.8%        0.80 3,875 ( 94%)     11 
Split 5     5,242 (80.6%)     17.6%        0.81 3,834 ( 93%)      7 
Split 6     5,313 (81.7%)     24.1%        0.79 3,825 ( 93%)      4 
Split 7     5,246 (80.7%)     24.8%        0.81 3,748 ( 91%)      3 
Split 8     5,192 (79.9%)     18.6%        0.82 3,602 ( 88%)      3 
Split 9     5,333 (82.0%)      7.7%        0.78 3,106 ( 76%)      2 
Resample    2,846 (43.8%)       NA%        0.93 4,253 (104%)     NA 

Checklist

• [x] I have followed the instructions
• [x] I have updated the tracker
• [x] All TODO lines from the template code have been removed
• [ ] I have merged in the master branch and then recalculated summary statistics
• [x] I have run enforce_style() to format my code
• [x] The documentation copied above is up-to-date
• [x] There are no data files in this pull request
• [x] None of the file output paths (for the redist_map and redist_plans objects, and summary statistics) have been edited

@CoryMcCartan