alarm-redist / fifty-states

Redistricting analysis for all 50 U.S. states
https://alarm-redist.github.io/fifty-states/
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2010 Idaho Congressional Districts #178

Closed emmaebowe closed 1 year ago

emmaebowe commented 1 year ago

2010 Idaho Congressional Districts

Redistricting requirements

In Idaho, districts must:

  1. be contiguous (72-1506(6)).
  2. have equal populations (72-1506(3)).
  3. be geographically compact (72-1506(4), 72-1506(5)).
  4. preserve county and municipality boundaries as much as possible (72-1506(2)).
  5. not be drawn to favor party or incumbents (72-1506(8)).
  6. connect counties based on highways (72-1506(9)).

Algorithmic Constraints

We enforce a maximum population deviation of 0.5%.

Data Sources

Data for Idaho comes from the Loyala Law School (LLS) All About Redistricting project

Pre-processing Notes

No manual pre-processing decisions were necessary.

Simulation Notes

We sample 15,000 districting plans for Idaho, across 2 independent runs of the SMC algorithm. We sample using the standard algorithmic municipality constraint. No special techniques were needed to produce the sample.

Validation

validation_20230303_1412

SMC: 30,000 sampled plans of 2 districts on 922 units
`adapt_k_thresh`=0.985 • `seq_alpha`=0.5
`est_label_mult`=1 • `pop_temper`=0

Plan diversity 80% range: 0.00 to 0.69
✖ WARNING: Low plan diversity

R-hat values for summary statistics:
   pop_overlap      total_vap       plan_dev      comp_edge    comp_polsby      pop_white 
     1.0000763      1.0000477      1.0000422      1.0000343      0.9999983      1.0000142 
     pop_black       pop_hisp       pop_aian      pop_asian       pop_nhpi      pop_other 
     1.0000588      1.0000549      1.0000673      1.0000921      1.0001120      1.0001892 
       pop_two      vap_white      vap_black       vap_hisp       vap_aian      vap_asian 
     1.0001284      1.0000298      1.0000802      1.0000640      1.0000557      1.0000990 
      vap_nhpi      vap_other        vap_two pre_16_rep_tru pre_16_dem_cli pre_20_rep_tru 
     1.0000699      1.0001531      1.0000987      1.0000118      1.0000496      1.0000090 
pre_20_dem_bid uss_16_rep_cra uss_16_dem_stu uss_20_rep_ris uss_20_dem_jor gov_18_rep_lit 
     1.0000232      1.0000137      1.0000407      1.0000183      1.0000245      1.0000625 
gov_18_dem_jor atg_18_rep_was atg_18_dem_bis sos_18_rep_den sos_18_dem_hum         adv_16 
     1.0000375      1.0000434      1.0000486      1.0000658      1.0000445      1.0000465 
        adv_18         adv_20         arv_16         arv_18         arv_20  county_splits 
     1.0000458      1.0000230      1.0000021      1.0000732      1.0000155      1.0000026 
   muni_splits            ndv            nrv        ndshare          e_dvs           egap 
     0.9999667      1.0000420      1.0000373      1.0000328      1.0000320      1.0000194 

Sampling diagnostics for SMC run 1 of 2 (15,000 samples)
         Eff. samples (%) Acc. rate Log wgt. sd  Max. unique Est. k 
Split 1    14,453 (96.4%)      2.9%        0.41 9,547 (101%)      7 
Resample   13,236 (88.2%)       NA%        0.41 9,091 ( 96%)     NA 

Sampling diagnostics for SMC run 2 of 2 (15,000 samples)
         Eff. samples (%) Acc. rate Log wgt. sd  Max. unique Est. k 
Split 1    14,447 (96.3%)      3.3%        0.41 9,518 (100%)      6 
Resample   13,219 (88.1%)       NA%        0.41 9,095 ( 96%)     NA 

•  Watch out for low effective samples, very low acceptance rates (less than 1%), large
std. devs. of the log weights (more than 3 or so), and low numbers of unique plans. R-hat
values for summary statistics should be between 1 and 1.05.
• Low diversity: Check for potential bottlenecks. Increase the number of samples. Examine
the diversity plot with `hist(plans_diversity(plans), breaks=24)`. Consider weakening or
removing constraints, or increasing the population tolerance. If the accpetance rate
drops quickly in the final splits, try increasing `pop_temper` by 0.01.

Checklist

delete this line and all the tags except the reviewers you need @christopherkenny

emmaebowe commented 1 year ago

Extra validation plots for custom constraints Rplot