Barry,

Some dated information: a long way back, I was on a "blue ribbon committee" 
that included voting officials from six states in the Midwest plus several 
electronic engineers and several software engineers. The purpose was to 
evaluate voting machines and select a vendor for the six states. Dominion was 
one of the competing vendors.

None of the machines were simple scanners. All had software for tabulation, 
error correction, statistical analysis of various kinds, real-time counts, 
remote monitoring over a network, etc.

A mandate from the election officials — all machines had to have a means for 
monitoring and "correcting" results, i.e. to let election officials override 
what the machines were tabulating. This override mechanism was semi-secret, but 
like I said it was mandated by the RFP and so it was present in all the 
machines we evaluated then.

If the backdoor was used, a record of what the official did was recorded in the 
audit trail along with all other counting information.

Dominion was the only vendor that provided a way to 'turn off' the audit trail 
feature. As offered, at that time, election officials had the power to sit in 
their offices, watch the results, and "correct" them if deemed necessary, 
invisible to any subsequent audit checks.

Discrepancies between hand count and machine count were minimized because 
ballots were sorted and bundled, such that bundles, not individual ballots were 
actually counted if a recount was mandated.

The whole experience made me a non-believer in any electronic election.

All this may be quite different today — I only report what was.

davew


On Thu, Jan 28, 2021, at 8:38 AM, Barry MacKichan wrote:
> Tom, you’re a journalist, so now that I have your (virtual and asynchronous) 
> attention, I’d like to register some complaints.

> We seem to get the same data again and again, but there is critical data that 
> noone has included in what I’ve read. Two examples:

>  1. We get daily death rates and number of hospitalizations, but no 
> information about the average length of a hospital stay for a covid patient. 
> This may not seem important, but if I want to compute the probability of 
> dying from covid once you are hospitalized, I need it. It is 
> (deaths/hospitalizations)*length-of-stay — this is because one person 
> contributes 1 to the count of hospitalization for each day he is 
> hospitalized, but can contribute at most 1 to the deaths. The naive 
> calculation of the probability would be about 3% (3K/100K), but if the length 
> of stay is 5 or 6 days, the true calculations show the odds of survival are 
> the same as one round of Russian roulette.
> It’s possible that the journalists have not given us this data because the 
> data sites (covidtracking.com and Johns Hopkins) don’t have it. Good 
> opportunity for a “scoop”.

>  1. A definition of a voting machine. Based on my experience in NM and in 
> North Carolina, the only machines were scanners. I have seen one photograph 
> of a Dominion “voting machine”, and the branding on the machine said 
> “Dominion scanner.” It would be hard to corruptly modify the results from the 
> scanner, and absolutely impossible to do so in a case where the hand count 
> matches the scanner count. Fifteen years ago, there were lots of voting 
> machines that did not produce paper ballots, and these were eminently 
> hackable. But no journalist I’ve read has made any distinction between the 
> machine types (and it is possible that all modern voting machines are 
> scanners reading paper ballots. If so, tell us.)
> You are of course innocent of these lapses, but maybe you could tell some of 
> your journalist friends that they are leaving out vital information.

> Thanks for listening (if you got this far).

> —Barry

> On 27 Jan 2021, at 14:49, Tom Johnson wrote:

> 
>> NYU Professor Creates COVID-19 Dashboard to Compare Country and State Data

>> by Sabrina I. Pacifici 
>> <https://www.cloudhq-mkt9.net/mail_track/link/a9654e6b1556032541_1611776974509?uid=226430&url=https%3A%2F%2Flc3.shitrk.com%2Fr%2Fe%2FY0B3ls5OLKvTaBGYJ%3Fr%3Dhttps%3A%2F%2Fwww.bespacific.com%2Fauthor%2Fsabrina%2F>
>>  on Jan 26, 2021
>> “A new online dashboard 
>> <https://www.cloudhq-mkt9.net/mail_track/link/a9654e6b1556032541_1611776974509?uid=226430&url=https%3A%2F%2Flc3.shitrk.com%2Fr%2Fe%2FnwbGJf0b3oQtOZ9xM%3Fr%3Dhttps%3A%2F%2Fcovid.jerschow.com%2F>,
>>  created by NYU Professor Alexej Jerschow 
>> <https://www.cloudhq-mkt9.net/mail_track/link/a9654e6b1556032541_1611776974509?uid=226430&url=https%3A%2F%2Flc3.shitrk.com%2Fr%2Fe%2F60j9rsYnQRpCAGg4Q%3Fr%3Dhttps%3A%2F%2Fas.nyu.edu%2Fcontent%2Fnyu-as%2Fas%2Ffaculty%2Falexej-jerschow.html>,
>>  brings together COVID-19 data from U.S. states and countries around the 
>> world to compare cases, deaths, vaccines, and testing in a visual, 
>> user-friendly format.  The tool also integrates a range of policies 
>> governments have implemented to limit the spread of COVID-19—including 
>> school closings, stay-at-home orders, and mask mandates—in an effort to 
>> compare policy responses with COVID-19 outcomes.Jerschow, who is a professor 
>> of chemistry and typically works in the field of magnetic resonance imaging 
>> and battery research, was looking for a convenient way to compare COVID-19 
>> data from different countries and states. While the data were available from 
>> different sources, there was not a single tool that allowed him to easily 
>> analyze how different geographic areas were faring and responding to the 
>> pandemic—so, he created one…The dashboard 
>> <https://www.cloudhq-mkt9.net/mail_track/link/a9654e6b1556032541_1611776974509?uid=226430&url=https%3A%2F%2Flc3.shitrk.com%2Fr%2Fe%2FnwbGJf0b3oQtOZ9xM%3Fr%3Dhttps%3A%2F%2Fcovid.jerschow.com%2F>
>>  combines data from a series of publicly available sources. Country-wide 
>> information is downloaded from Our World in Data 
>> <https://www.cloudhq-mkt9.net/mail_track/link/a9654e6b1556032541_1611776974509?uid=226430&url=https%3A%2F%2Flc3.shitrk.com%2Fr%2Fe%2F0br9NiGe3nrF3ma6M%3Fr%3Dhttps%3A%2F%2Fourworldindata.org%2Fcoronavirus>,
>>  which sources its data from the Johns Hopkins Center for Systems Science 
>> and Engineering dashboard 
>> <https://www.cloudhq-mkt9.net/mail_track/link/a9654e6b1556032541_1611776974509?uid=226430&url=https%3A%2F%2Flc3.shitrk.com%2Fr%2Fe%2F20a9LsP2l7OTXERVM%3Fr%3Dhttps%3A%2F%2Fcoronavirus.jhu.edu%2Fmap.html>.
>>  U.S. state and territory data are obtained from covidtracking.com 
>> <https://www.cloudhq-mkt9.net/mail_track/link/a9654e6b1556032541_1611776974509?uid=226430&url=https%3A%2F%2Flc3.shitrk.com%2Fr%2Fe%2Fw3z5Jh4ZxLoiRa56B%3Fr%3Dhttps%3A%2F%2Fcovidtracking.com%2F>.
>>  The Oxford COVID-19 Government Response Tracker (OxCGRT) 
>> <https://www.cloudhq-mkt9.net/mail_track/link/a9654e6b1556032541_1611776974509?uid=226430&url=https%3A%2F%2Flc3.shitrk.com%2Fr%2Fe%2FW9OxRfQxV1nH40zGw%3Fr%3Dhttps%3A%2F%2Fwww.bsg.ox.ac.uk%2Fresearch%2Fresearch-projects%2Fcoronavirus-government-response-tracker>
>>  provides policy data…”

>> 
>> 
>> ============================================
>> Tom Johnson - t...@jtjohnson.com 
>> <https://www.cloudhq-mkt9.net/mail_track/link/a9654e6b1556032541_1611776974509?uid=226430&url=mailto%3Atom%40jtjohnson.com>
>> Institute for Analytic Journalism   --     Santa Fe, NM USA
>> 505.577.6482(c)                                    505.473.9646(h)
>> *NM Foundation for Open Government* 
>> <https://www.cloudhq-mkt9.net/mail_track/link/a9654e6b1556032541_1611776974509?uid=226430&url=https%3A%2F%2Flc3.shitrk.com%2Fr%2Fe%2F5KGR4cK49zVSrMkPr%3Fr%3Dhttp%3A%2F%2Fnmfog.org%2F>
>> *Check out It's The People's Data 
>> <https://www.cloudhq-mkt9.net/mail_track/link/a9654e6b1556032541_1611776974509?uid=226430&url=https%3A%2F%2Flc3.shitrk.com%2Fr%2Fe%2FBNmKkirZWQPirw9Pg%3Fr%3Dhttps%3A%2F%2Fwww.facebook.com%2Fpages%2FIts-The-Peoples-Data%2F1599854626919671>*
>>                  
>> ============================================
>> 
>> 

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