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It’s too early to just accept this as fact. It may be true, and may not. It may be true but didn’t swing the election. What’s absolutely true though is that the race shouldn’t have been close enough to even make a Republican win remotely believable.
The Democrats made it close by putting wealthy interests ahead of voters to the highest degree they thought they could get away with. Dance long enough on the Cliff’s edge and eventually you fall in - or maybe you get pushed. Not a lot of difference ultimately.
Well, . . . IF it’s true, it very definitely did swing the election - that being the entire point of it.
The perceived platform of the Democrats notwithstanding.
This appears to be the larger body working on it:
https://thecommoncoalition.com/report/
If every aspect of what’s being alleged is entirely true, then yes. The thing is, it’s a huge collection of different allegations that range from probable to unhinged. They aren’t all going to be 100% true.
The fact that they spend so much time in their video on Trump saying they don’t need votes is a big red flag to me. They put so much effort into priming people to believe that I don’t think they have quite convinced themselves.
All of these allegations combined actually pale in comparison with the impact of media consolidation and establishment manipulation of coverage. Our primary process is an absolute travesty that can be trivially manipulated on the whim of the establishment to get whatever outcome they desire.
Which parts read as unhinged to you?
Agreed on the media part, but that’s a very old conspiracy.
I hate to use the word “conspiracy” on it - first because it implies that it’s a “conspiracy theory” when most of it happens in plain sight, and second because it’s less of a cabal and more just a bunch of rich folks with common interests acting in common ways.
Jumping right from claiming that Trump over-performing (compared to down-ticket races) more in swing states than other states leads straight to the conclusion that a “vote changing algorithm” must be responsible for the difference is a big one. There are other perfectly plausible explanations. For instance, maybe anti-establishment sentiment is part of what makes a purple state purple, and anti-establishment Trump voters are more likely to split their ticket. The analysis offered is incredibly shallow, and seems to rely entirely on statistical analysis without considering sociological context. I’m also curious why a group so competent as to be able to pull this off wouldn’t have tipped votes in down-ticket races as well.
On the other hand, a lot of the voter suppression claims are very plausible, and some are even obviously true. It’s almost not revelatory at all to say that Republicans use voter suppression to win races. Specifics of particular instances are worth questioning, but Republicans have been doing it in the open for decades, and it has definitely blown up in the time since the court gutted the voting rights act.
There is also the general over-reliance on a single expert, who is apparently “the leading U.S. expert in election forensics”. Looking at his citations, that title is not justified by his academic career. What I see is some mild success early on, and a decade+ drift towards irrelevance. I see a career that could maybe benefit from a prominent association with a media frenzy over a stolen US election.
Oh just conspiracy in “two or more parties working together towards a harmful act” sort of thing. Doesn’t have to be secret.
The part about a particular number of votes being needed to trigger the algorithm is an interesting part of it. In that reply to the second substack post he explains why Elmo’s 20 million investment in the Wisconsin supreme court runoff didn’t pay out for him, and it was about volume of votes.
There’s also this graphic which is interesting.
I haven’t read up on the expert academic but having a stalled career doesn’t discount anything for me if so. The numbers and facts should speak for themselves anyway.
I don’t find that graph very interesting at all. First it’s kind of annoying that they don’t say what they mean by drop-off before presenting the chart. Later in the document they group drop-off and mail-in, so I presume they mean ballots in drop boxes. But then, I have no idea how the percentage of votes cast by drop-off could be a negative number. They also assert that the 2016 example represents “human voting” and the 2024 does not with no explanation of any kind. Isn’t it possible that COVID had some lingering impact on how people cast their votes? The whole thing is a mess, which makes me think that they don’t really want people to understand it.
No, they absolutely should not. Not at this stage anyways. It’s nothing but conceit for you to think you can figure this out from the data yourself. At this stage, it’s up to the experts who have access to all the data and the knowledge of how to interpret it. Not one expert, but a lot of experts. At some point the issues and challenges would become better defined, and matters of opinion would start to separate from matters of fact. That is when average people would be able to judge what constitutes cheating and what constitutes playing the game.
There are plenty of people and organizations with resources, motivation, and interest in uncovering such a conspiracy. None of them are ringing the alarm bells. Were this a real controversy, it wouldn’t be just some lone cobbled together group putting it forward.
It should, especially when the arguments put forward depend so much on expert opinion and there is only one expert being put forward. True is true, no mater who says it, but a complicated issues like this needs experts to add context that non-experts might not even consider. For instance, the sociological aspects I mentioned (makeup of purple states / covid impact on voter patterns) and others I didn’t or wouldn’t think of. Even just statistics themselves have a whole lot of nuance that can lead to crazy results if not handled correctly. Humans are terrible at understanding statistics at this scale.and complexity.
So look at the variance in the 2016 vote and the much more regular pattern in the 2024 vote. And yes drop-off, or mail-in ballot versus voting-at-the-polling-station votes.
I read it like: 10 drop off votes vs 10 polling station votes = 0% difference.
20 drop off votes vs 10 polling station votes = -10%
10 drop off voted vs 20 polling station votes = 10%
Each county has one blue line and one red line. In 2016, some of the counties show both lines positive (few drop offs) and some both lines negative (largely drop offs). In 2024, no county had more drop offs than polling station votes, and of the drop offs they were overwhelmingly trump even in areas that were overwhelmingly blue in 2016.
I think that’s interesting.
We’ll just have to disagree on that then. I’m not saying I’m an expert, I’m saying the known vote counts in the following examples are all we need to know to warrant a further look:
You might say “there are no numbers in there” and on that we would agree. Those numbers would not be esoteric symbol-strewn formulas, they’d be, like “5%”. And having them in front of us would be interesting to see without the need for a historian, a COBOL developer, and a Druid.
The key says “total vote” not polling-station votes, but sure.
Total in-person votes amounted to about 6% of the total vote. All of the numbers should be massively negative by your interpretation. If you lump mail-in and drop-off votes together, then you get just under a million votes compared to 1.5 million drop-off votes. The results of your interpretation should still skew mostly negative, but the chart is mostly positive. You have made assumptions about the charts that are not in the description and that make the chart obviously wrong.
Again I say, the whole thing is a mess, which makes me think that they don’t really want people to understand it.
Well, the fact that we had an election warrants a further look. I’m just saying that it should be looked at by people who won’t make obvious mistakes like you just did. At some point we play a role
Tell me you know nothing about statistical modeling without telling me you know nothing about statistical modeling. If you were to take any large random list of numbers, you could find all sorts of patterns that aren’t there. Any experience at large statistics at all would have red flags flying any time someone picks out a very particular view when presenting data - especially if they obscure how exactly that view was obtained. Why 2016 and not 2020 or 2012? Why only Ohio? Why present the data this way and not some other way? Why make the key so confusing?
I’m not saying that there isn’t something here, but the information this organization is presenting doesn’t support that conclusion at all. If anything, it calls attention to how much obfuscation it takes to even make the case.