We need to keep our reporting clean if we want to be the internet site of record.
This is why we need sources. This is why GP should be labeled TABLOID. This is why we don’t just run around with bullshit infowars “it’s a sting op!”, this is why we don’t habbening every 5 seconds.
WE ARE ALLOWED NO MISTAKES.
If you hype something up here and it’s wrong (crowder the other day) it longer term hurts us.
Fakenews can lie their assets off all day long. We get no slack.
Doing some rough math, there were 3,612,258 registered births in the US in 1980, so about 9896 per day. I'm not sure the average voting age, and am too lazy to try to be more precise about average number of people with the same birthday.
The next question is around the number of people who share the same first, middle, and last name. I've met people with the same first-and-last name, but never first-middle-and-last, unless we assume both don't have middle-names.
In this case we're dealing with an even smaller population than the entire us population, just 2 states.
I'm too lazy and lack the data (on same name) to calculate precise numbers, but I'd be a little surprised if you could find 1000 matches that were different people.
Not true. A first/middle/last and DoB match is almost always a dead ringer for a match even if you're dealing with John Smiths.
EDIT: Sorry, to explain further, let's say you have an ordinary day in America. Roughly 10,700 people are born.
Nearly 50/50 male/female, and luckily we haven't moved to androgynous names only yet so most are uniquely one direction or the other. Let's give a little leeway for overlap and say a pool of 6,000 (half plus 10ish%)
So of the roughly 6,000 same-sexed + SNL-Pat-named people born on a given day, what are the odds they have the same first, middle, and last name? Obviously the pool is going to narrow given more unique names.
Even looking at a John Smith or a James Franklin or a Jane Goodman, the odds of there being another John Smith or James Franklin or Jane Goodman in the same rough geographical area (remember, PA and WI areas only here) with the same middle initial (of the 26 letters about 16-18 are commonly used) is very small.
Without getting further into the weeds with the birthday paradox (50% chance of 2 people in a room of 23 having the same birthday) and other metrics, I would be absolutely shocked if the list of 130k above contains any more than 10k that are legitimately different people. I would wager any handful you pick you're probably going to be looking at the same person every time and very rarely finding records that are different people.
It must have, because he is saying over 130k. It's one thing if you get a few hundred hits. That could be dismissed. However, if you're into the thousands with FULL name and DOB being exact, that's NOT a coincidence.
Also, if that matches and they are all registered voters, AND all voted for Biden... that's basically statistically IMPOSSIBLE to happen naturally.
In Oregon, all you need to log in to your account to request absentee ballots is first, middle, and last name, along with DOB. They use that as log in credentials, so it's not that common to have THOUSANDS of people share those same details.
Not necessarily, but of 130k matches I'd put literally all of the money in my bank account on at least 100k being the same people, or positive matches.
I just did a search across 3.6 million PA residents, grouping by first name, mi, last name, and dob and got 30K pairs. They seem to have different addresses. This dataset (unlike ones I used to work with) is supposed to be heavily processed to remove duplicates.
Only .8% but a big number because the denominator is so large. Dunno the cause, could still be bad data I suppose.
Michigan and Pennsylvania is what he says. We need to keep our reporting clean if we want to be the internet site of record.
Good catch. Very eloquently said, as well.
This is why we need sources. This is why GP should be labeled TABLOID. This is why we don’t just run around with bullshit infowars “it’s a sting op!”, this is why we don’t habbening every 5 seconds.
WE ARE ALLOWED NO MISTAKES.
If you hype something up here and it’s wrong (crowder the other day) it longer term hurts us.
Fakenews can lie their assets off all day long. We get no slack.
What did Crowder get wrong? I watch him all the time seems like he had legit evidence?
His entire claim what that the columns for in Detroit absentee all said zero, but they always do, and other people here explained that isn’t unusual.
That still didn't explain the ridiculous numbers tho right?
Don’t know. I have trouble figuring out what data is public all available and what isn’t.
I do patient matching as part of my job.
First + middle + last + dob is enough to get you over literally every matching threshold in our system.
This is big.
Hello fellow data jockey
Yeah, some of those might be legitimately different people, but ...
There are definitely some in there, but likely less than 5% are different people.
Much less than 5%, more like 0.5% if even that.
This guy fucks
Doing some rough math, there were 3,612,258 registered births in the US in 1980, so about 9896 per day. I'm not sure the average voting age, and am too lazy to try to be more precise about average number of people with the same birthday.
https://www.cdc.gov/nchs/data/statab/natfinal2003.annvol1_01.pdf
The next question is around the number of people who share the same first, middle, and last name. I've met people with the same first-and-last name, but never first-middle-and-last, unless we assume both don't have middle-names.
In this case we're dealing with an even smaller population than the entire us population, just 2 states.
I'm too lazy and lack the data (on same name) to calculate precise numbers, but I'd be a little surprised if you could find 1000 matches that were different people.
That was my guess too! Lol. I wrote that in a different response
I have the PA data is the MI data out their? I want to look into this.
I have 100s of screenshots of liberals gloating about their imaginary new president. I am going to have so much fun when Trump is inaugurated.
Link
Huh?
Is this the nail in the coffin?
I am sure one can find 10 million bogus Biden voters (as Sydney Powell claimed) if one combs through all 50 states for duplicated voters.
And I wouldn't be surprised that most if not all of them voted Dem.
Someone is probably writing a movie script for this 2020 election fraud of the century now!
aaaand its been blocked.
Amazing news! (Thanks for giving the time stamp!)
You don't even have the correct states. Smh
I've worked with demographic detail-based matching a lot and those 4 pieces of info are not great criteria for finding distinct records.
If the name is unusual them maybe.
Not true. A first/middle/last and DoB match is almost always a dead ringer for a match even if you're dealing with John Smiths.
EDIT: Sorry, to explain further, let's say you have an ordinary day in America. Roughly 10,700 people are born.
Nearly 50/50 male/female, and luckily we haven't moved to androgynous names only yet so most are uniquely one direction or the other. Let's give a little leeway for overlap and say a pool of 6,000 (half plus 10ish%)
So of the roughly 6,000 same-sexed + SNL-Pat-named people born on a given day, what are the odds they have the same first, middle, and last name? Obviously the pool is going to narrow given more unique names.
Even looking at a John Smith or a James Franklin or a Jane Goodman, the odds of there being another John Smith or James Franklin or Jane Goodman in the same rough geographical area (remember, PA and WI areas only here) with the same middle initial (of the 26 letters about 16-18 are commonly used) is very small.
Without getting further into the weeds with the birthday paradox (50% chance of 2 people in a room of 23 having the same birthday) and other metrics, I would be absolutely shocked if the list of 130k above contains any more than 10k that are legitimately different people. I would wager any handful you pick you're probably going to be looking at the same person every time and very rarely finding records that are different people.
Then my datasets must have been garbage.
It must have, because he is saying over 130k. It's one thing if you get a few hundred hits. That could be dismissed. However, if you're into the thousands with FULL name and DOB being exact, that's NOT a coincidence.
Also, if that matches and they are all registered voters, AND all voted for Biden... that's basically statistically IMPOSSIBLE to happen naturally.
In Oregon, all you need to log in to your account to request absentee ballots is first, middle, and last name, along with DOB. They use that as log in credentials, so it's not that common to have THOUSANDS of people share those same details.
Not necessarily, but of 130k matches I'd put literally all of the money in my bank account on at least 100k being the same people, or positive matches.
That's being very, very generous.
I just did a search across 3.6 million PA residents, grouping by first name, mi, last name, and dob and got 30K pairs. They seem to have different addresses. This dataset (unlike ones I used to work with) is supposed to be heavily processed to remove duplicates.
Only .8% but a big number because the denominator is so large. Dunno the cause, could still be bad data I suppose.