2020 Utah Congressional Districts

Redistricting requirements

In Utah, districts must, under legislation code 20A-20-302:

1. have a total population deviation of less than 1% (where total population deviation is calculated by adding together the percentage deviation of both the most populous and least populous districts from the average, or “ideal,” district)
2. not be drawn with race used as a predominant factor
3. be contiguous and reasonably compact
4. to the extent practicable
   1. preserve communities of interest
   2. follow natural, geographic, or man-made features, boundaries, or barriers
   3. preserve cores of prior districts
   4. minimize the division of municipalities and counties across multiple districts
   5. achieve boundary agreement among different types of districts
   6. prohibit the purposeful or undue favoring or disfavoring of incumbents, candidates or prospective candidates, and political parties

Algorithmic Constraints

We enforce a maximum population deviation of 0.5% (which ensures that the total population deviation as defined by Utah legislation does not exceed 1%). We constrain the number of “pseudo-county” divisions (see below for an explanation of pseudo-county). We perform cores-based simulations, thereby preserving cores of prior districts.

Data Sources

Data for Utah comes from the ALARM Project’s 2020 Redistricting Data Files. Data for the 2021 Utah Congressional adopted plans come from Utah Legislative Redistricting Committee’s MyDistricting site

Pre-processing Notes

We create pseudo-counties by splitting counties with a total population higher than the target district population into county-municipality combinations (in the end, this affects only Salt Lake County, which has a total population well above 1 million). To preserve the cores of prior districts, we merge all precincts which are more than two precincts away from a district border under the 2010 plan.

Simulation Notes

We sample 6,000 districting plans for Utah across two independent runs of the SMC algorithm. To balance county and municipality splits, we create pseudo-counties as described above.

Contents

• UT_cd_2020_stats.csv contains summary statistics on the sampled redistricting plans
• UT_cd_2020_plans.rds is a compressed redist_plans object, which contains the matrix of precinct/block assignments and may be used for further analysis.
• UT_cd_2020_map.rds is a compressed redist_map object, which contains the precinct/block shapefile and demographic data.

Both the redist_plans and redist_map object are intended to be used with the redist package.

Codebook for summary statistics

• draw: unique identifier for each sample. Non-numeric draw names are real-world plans, e.g., cd_2010 for an enacted 2010 plan.
• district: a district identifier. District numbers roughly match those in the enacted plan, but the correspondence is not perfect.
• chain: a number identifying the run of the redistricting algorithm used to produce this draw. Used for diagnostic purposes.
• pop_overlap: a number indicating the fraction of people in this plan who reside in the same-numbered district in the enacted plan.
• total_pop: the total population of each district.
• total_vap: the total voting-aged population of each district.
• pop_*, vap_*: total (voting-aged) population within racial and ethnic groups for each district. Variable codes documented here.
• plan_dev: the maximum population deviation among districts in the plan. Computed as max(abs(distr_pop - target_pop)/target_pop).
• comp_edge: compactness, as measured by the fraction of internal edges kept. Higher values indicate more compactness.
• comp_polsby: compactness, as measured by the Polsby-Popper score. Higher values indicate more compactness.
• county_splits: the number of counties which belong to more than one district.
• muni_splits: the number of Census Designated Places which belong to more than one district.
• *_##_dem_*, *_##_rep_*: vote counts for statewide Democratic and Republican candidates in a certain election. More information here.
• adv_##, arv_##: average vote counts for statewide Democratic and Republican candidates in a certain year. More information here.
• ndv, nrv: averages of the adv_## and arv_## variables across all available elections.
• ndshare: normal Democratic share, computed as ndv / (ndv + nrv)
• e_dvs: average Democratic vote share, computed as the average of the Democratic vote share when first scored under each statewide election.
• pr_dem: probability seat is represented by a Democrat; calculated as the fraction of statewide elections under which the district had a majority Democratic share.
• e_dem: expected number of Democratic seats for the plan; equivalent to summing the pr_dem values across districts
• pbias: partisan bias at 50% vote share, averaged across all available elections. Positive values indicate Republican bias.
• egap: the efficiency gap, averaged across all available elections. Positive values indicate Republican bias.