Florida 2000 and Washington 2004

From which we obtain,

Thus, with the additional ballots required by the Florida Supreme Court—because they gave clear evidence of voter intent—the final margin was statistically insignificant at the 92 percent level. It was only by certifying the vote before the legal process was complete and these ballots were included that Harris was able to reduce that to even 85.5 percent.

In 2004 Washingtonians "decided" on a governor and were thus responsible only to themselves for the outcome. In Florida 2000 far more was at stake. With the rest of the country already decided by statistically significant margins, the national election hinged on Florida's electoral votes. Whoever won there would be the next president of the United States, so it's instructive to see if the coin toss election in Florida did justice to the will of the American people as a whole.

From the national counts given above we have,

From which we obtain,

The T-Tables I am using (LSU, 2005) do not report high enough T values to quantify the probability associated with this value. Remember however, that T is a measure of signal to noise, so the higher its value, the greater the odds of a statistically insignificant outcome. Shortly after Election Day 2000 a similar T-Test of the national vote was done by Gelobter of Rutgers University (Gelobter, 2000). Based on national vote totals as of Dec. 9, 2000 (which had a smaller spread than the final tallies reported above) he arrived at a T value of 46.833. Using a direct calculation of the corresponding probability rather than tables, he obtained a probability of only 1 chance in greater than 6.46 x 10²⁹⁵ that Gore's margin of victory was statistically insignificant. To grasp the magnitude of this figure, consider that the number of atoms in the visible universe to a radius of 15 to 20 billion light years has been estimated at roughly 10⁷⁸. Gelobter's figure is over 6 trillion, trillion, trillion, trillion, trillion times the cube of that number. Our value of T^2KN is 63 percent larger than that making the corresponding final probability many orders of magnitude lower still.

In other words, Gore won the year 2000 popular vote.   Period!

Despite all rhetoric to the contrary it's clear that both elections were a coin toss. Neither produced a final margin that came anywhere near to exceeding the dispersion in the vote gathering and counting process leaving neither candidate with a verifiable majority. However, the election process itself must also be considered. Even if the final margin was statistically insignificant, election fraud or sabotage could still be demonstrated if there was compelling evidence for the following;

• Specific activities or policy decisions that invalidated or discarded discernable ballots, or disenfranchised voters, in numbers larger than the victory margin.
• A majority vote for these ballots that favored the losing candidate by a larger margin than the one certified.

Note that this would still be a "smoking gun" even if the activities involved were not deliberate. Unintentional negligence would not constitute first degree election theft, but it would certainly pass for sabotage through incompetence or neglect to a degree that would indisputably invalidate a result. To run the full course we must now examine both elections in terms of how ballots were actually handled, how they were counted or disqualified, and whether the powers that be handled the election process in ways that stacked the deck. There were several areas where both elections presented alleged or actual disenfranchisement issues. These must now be addressed.

Machine vs. Manual Vote Counts

The Far-Right has repeatedly claimed that machine counts are more reliable than hand counts, but even a cursory examination of the evidence reveals otherwise. The voting machine technologies used in most U.S. elections fall can be grouped into 4 categories;

• Lever Machines in which the voter flips switches to indicate their selections and then pulls a manual lever to record their selections when complete. Lever machines register all chosen votes at one time and therefore do not permit overvoting.
• Punch Card Machines where the voter is given a ballot with perforated rectangles ("chads") next to each candidate's name that is punched out with a metal punch. Two variations are used in U.S. elections; DataVote machines where candidate names are listed on the ballot card, and VotoMatic machines where they are not.
• Optical Scanning Machines where the voter is given a "mark-sense" form with circles next to each candidate’s name and the choice is made by filling in the circle with a number 2 pencil. The ballot is then read by an optical scanner that detects the difference in reflectivity between the paper ballot and the pencil marks it carries.
• Direct Recording Electronic (DRE) Machines that are essentially electronic lever machines that uses either push buttons of touch screens in place of the lever. Like the lever machines they are based on, DRE's do not permit overvoting.

All are in use and most U.S. elections are conducted with a mix of all 4 (Caltech/MIT, 2001). Errors in vote taking and/or counting using these technologies will create "residual votes"--that is, no registered preference for any candidate. Residual votes fall into 3 categories; the undervotes and overvotes already discussed, and intentional abstentions by the voter. Because of the latter, the raw residual vote rate overestimates the actual impact of lost votes, so estimates of "machine effect" are best made by comparing changes in residual vote rate across different technologies, particularly before and after technology shifts in a particular region (though these have to be adjusted for the "learning curve" that results when voters and poll workers have to learn a new system). Residual vote rates for presidential elections run from 1.5 to 4 percent of all ballots cast at the county level, with the average around 2.3 percent. The corresponding average for senatorial and gubernatorial elections is 4.1 percent with a standard deviation of 3.5 percent (MIT/Caltech, 2001; Ansolabehere & Stewart, 2005). Typically, there is more intentional abstention in local elections. Studies based on exit polls and post-election surveys indicate that the intentional abstention rate is around one-half of one-percent for U.S. presidential elections. Based on this, it's likely that their unintentional residual vote rate runs from 1 to 3 percent of all ballots cast nationwide with the average around 1.8 percent. Under similar conditions gubernatorial elections show similar patterns after higher intentional residual voting is accounted for. But they may vary in how they compared to presidential elections as the residual vote rate for each may be quite different between the two for certain vote gathering technologies (Ansolabehere & Stewart, 2005).

Several studies have compared manually counted paper vote implementations with the machine vote technologies. In traditional paper votes the voter fills out a ballot by putting a pencil mark next to the candidate of choice, after which the ballots are counted by hand. These incur errors resulting from ambiguous or confusing marks by voters (Caltech/MIT, 2001). Paper votes make a good benchmark for comparing machine to manual recounts not only because they test manual counting methods, but also because they are almost certainly less accurate than manual recounts of other voting methods. Machine generated undervotes leave behind a chad, dimple, or pencil-marked oval that is generally far less confusing than hand votes that are unreadable because of illegible writing by voters. This will also be true for the clearest of problem overvotes. Results from manual recounts can vary widely compared to machine recount methods, mainly due to human factors. But with proper guidelines and bipartisan oversight these factors are greatly reduced resulting in far more accurate counts than are realized by other methods where human judgment regarding determination of voter intent is taken out of the loop.

After correction of the residual vote rate for intentional abstentions, manual paper votes have been shown to be the most accurate in presidential races, with residual vote performance improvements of up to 1.5 percent of all votes cast in presidential elections (Caltech/MIT, 2001; Ansolabehere & Stewart, 2005). Optical scan machines are almost as good, lagging anywhere from one to six-tenths of a percent behind paper votes in presidential elections (Caltech/MIT, 2001; Brady, 2001). In gubernatorial elections they rival paper ballots for accuracy though the differences are not statistically significant (Ansolabehere & Stewart, 2005). DRE machines usually (but not always) lag behind these. Punch machines are the worst, lagging behind other technologies by up to 2 percent of all ballots cast and at their best run around one percent (Caltech/MIT, 2001; Brady, 2001; Ansolabehere & Stewart, 2005).

Machine related residual vote rates are often referred to as "technology" error in that they reflect ballot spoilage directly or indirectly attributable to vote gathering equipment. They are not the same as machine reliability rates, which typically run around one miscount in every 250,000 to 1 million ballots. Technology errors include spoilage resulting from implementation and voter use as well. Machine failure rates are tested under controlled conditions usually with a small sample of test machines. These performance rates may or may not be realized in actual elections where a much larger number of machines are purchased, delivered and set up under widely varying circumstances. They may prove confusing to voters and be misused if adequate voter assistance and education are not available, a problem which was widespread in the Florida 2000 election. In practice, it's very difficult to separate actual residual vote rates due to directly and indirectly to particular technologies from those due to choice or other factors. The best estimates are generated by comparing the technologies relative to each other during periods of technology transition using regressions containing "dummy" variables that track contributions to residual vote from other variables such as demographics, county level administration changes, and vote "rolloff" (that is, where the presence or absence of other offices on a ballot affects the residual vote rate of the target office vote being measured, which can be significant) and correct for them leaving only the "raw" technology driven impact. Technology driven residual vote rates determined in this manner are referred sometimes referred to as "fixed effect" rates and are most likely to represent the actual impact of a particular technology on spoiled ballot counts (Ansolabehere & Stewart, 2005).