Chaos in Cuyahoga? 49,000 Votes Disappear into the Ether ...then found?

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Chaos in Cuyahoga? 49,000 Votes Disappear into the Ether

Intro

In Cuyahoga, the ballot order was rotated and evenly distributed within reason amongst the 1436 precincts. We know that ballot order in and of itself is not a significant factor in predicting the outcome of a contest if the ballot order is rotated and evenly distributed. Further, the analysis of number of precincts versus % votes awarded returns somewhat mixed results (See Appendix A - % of Votes Cast versus Graph of Number of Precincts) . However, when we examine voting locations (and their precincts) from a "uniqueness of the ballot order" perspective, there appears to be a significant relationship between the two factors. The Cuyahoga data indicates that the greater the chaos (i.e. the greater the number of ballot arrangements within a voting location), the more "one candidate" appears to benefit.

To illustrate the ballot groupings consider:

Location A has 1 precinct and thus only 1 unique ballot order combination
Location B has 3 precincts but only 1 unique ballot order combinations
Location C has 5 precincts and 3 unique ballot orders combinations
Location D has 10 precincts and 4 unique ballot orders combinations
Location E has 8 precincts and 4 unique ballot orders combinations
Location F has 7 precincts and 4 unique ballot orders combinations

Therefore location A & B belong to the same class of ballot arrangements (1); Location C belongs to class 3, and Location D, E, and F belong to class 4.

Method

Using the Copperas & Cuyahoga BOE data (excluding the absentee vote), I constructed a cross tabulation of the votes cast by the number of "unique ballot arrangements within voting location". Since there were only 5 candidate slots there is a minimum of 1 and a maximum of 5 ballot groupings in any one vote location whether there are 2 or 25 precincts voting in that same location.

Assumptions made:

1. The field (in the Copperas data file:Ref#1) Street Address is unique to one and only one location (583 distinct addresses identified)
2. Ballot order (in the Copperas data file:Ref#1) is correct.

Findings and Observations

From Graph 1, we see that in voting locations with one or more precincts but only 1 unique ballot order across precincts, Kerry picks up > 75% of the votes cast for president.



In the 2nd group of Table 1 (2 distinct ballot arrangements) Kerry's returns drop to 71%. (Note: This group includes the now infamous Cleveland 4N and 4F precincts at vote location "BENEDICTINE HIGH SCHOOL at 2900 MLK JR DR " where Peroutka picks up 215 votes and Badnarik picks up 164 votes.)

Further, as the number of ballot arrangements increases within location (i.e. the chaos), Kerry’s returns diminish significantly (the drop is > 21% in this scenario with 5 distict ballot arrangements within vote location)

A Closer look at Homogeneous Ballot Order in Voting Locations

Table 2 presents the detail data for all precincts that have homogeneous ballot order within vote location. From voting location to voting location, the ballot order may vary but within this subset the ballot order remains constant within the specific voting locations.



The first group of votes cast (in 136 precincts), is the simplest case -- vote locations that have only one precinct.

The 2nd group in the table presents the votes cast for vote locations with 2 precincts, all with the same ballot order within vote location.

In the last group in the table, 2 voting locations have been identified that have 3 precincts each, but within each vote location the order of the ballots remains the same.

Thus, Table 2 represents the scenarios where the opportunity to "shuffle the ballots" i.e. mix up the ballots either intentionally or by accident is minimized. (Ballot stuffing and machine manipulation is still a possibility in all cases).

What if?

If the homogenous data from the 182 precincts in Ballot Class 1 above represents a more accurate picture of how citizens intended to vote in Cuyahoga, then we using the percentage votes cast from that group we can recalculate that Kerry would have picked up another 49,000 votes in Cuyahoga alone had ballot mix up not been a factor.

Conclusions

Number of unique ballot arrangements within voting locations appears to be a significant predictor of vote distribution. Further study is required to determine whether other influencing factors may be involved.

References

1. Cuyahoga Precinct Results: http://copperas.com/cuyahoga/cuyahogaofficial.zip
2a. Ballot Order: http://boe.cuyahogacounty.us/boe/ballots/
2b. Precinct Results: http://boe.cuyahogacounty.us/BOE/results/history/2004/EL52.txt
2c. Vote Locations: http://boe.cuyahogacounty.us/boe/PDF/votinglocations.pdf

Appendix A