Monday, August 31, 2015

Kansas Election Fraud Part 5

I thought about this data far too much over the weekend.  On Friday I received data by precinct for the State of Kansas 2014 Governor's race, which had never been available before.  Here's my post on that. A reminder of where we were on this data on Friday:

  • We acquired precinct level data for all 105 counties.
    • 101 counties were in analyzable (it's a word) form.
    • 2 additional counties were parsed manually.
    • 2 other counties (Sedgwick, Shawnee), I was still working on, due to data availability issues.  
  • We validated the Clarkson's results, specifically for Johnson county.
  • We found that the remaining 101 counties have a low density of the types of precincts Clarkson analyzed (>500 voters)
Let's start with a deeper dive into Johnson County

REVISITING JOHNSON COUNTY

In Friday's post, I validated Clarkson's correlation using the new data, specifically from the Governor's race 2014, for Johnson county.  From her prior analyses, Clarkson's correlation is as follows:

Counter-intuitively, after 500 voters, precinct size correlates positively with Republican share of the vote.

The idea behind this, is that most precincts under 500 voters are rural, republican leaning districts, whereas after 500 voters, she would expect the precinct size to republican % to level out, or become more Democrat leaning, because larger precincts would be at the urban core.  I have explained the problems with this logic in several different blog posts.  Effectively, precinct creation is not a randomized process, thus many covariates, demographic and otherwise come into play.  I even  demonstrated how Clarkson's analysis dries up when we expose the data to those covariates.

But is there a move visual way to demonstrate how this works?

Turns out, yes.

Focusing on Johnson County, I highlighted all of the precincts with 500 or more voters in the 2014 Governor's election, and then went on to classify each one by larger buckets.  After 500 voters per precinct, the smallest precincts are the ones closest to the urban core, while the largest are in the outer-rural suburbs.  This map demonstrates that relationship:



Johnson County is weird though, so we don't necessarily know that the gentrified areas closest to the urban core are going to be the most liberal.  So I mapped this as well, validating that the areas closest to the urban core tend to be the most liberal, with the most conservative areas outside of the 435 loop. 

What does this mean?  It validates two things:
  • Precinct creation is not random, and the larger precincts within Johnson County do not lie closest to the "democrat" urban core, or randomly throughout the region, but instead in rural and near-urban suburbs-in direct opposition to Clarkson's hypothesis.
  • Those suburban areas (outside of the 435-loop) tend to also be more conservative.
In essence, the primary hypothesis of Clarkson's analysis is flawed, because these a priori relationships exist.

SEDGWICK COUNTY

I acquired one more county of data today, this time Sedgwick County with plenty of 500+ voter precincts.  If you're from outside of Kansas, Sedgwick County is where Wichita is located.  This county also validated Clarkson's correlation.  Here are our outputs, first graphed, then R.




I haven't found a lot of additional data on Sedgwick County yet, but will post similar to Johnson County as I find additional data.

CONCLUSION

I will keep posting on this as more data comes in, but two big takeaways from today.  
  • Sedgwick County Fits the pattern developed by Clarkson.
  • Taking a deep dive into Johnson county, we validated from my prior analysis, that, beyond 500 voters, larger precincts are actually LESS likely to be in the urban core, and more likely to be in the conservative outer suburbs.





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