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Link to ETA release and pdf <a href="https://electiontruthalliance.org/clark-county%2C-nv" rel="nofollow">https://electiontruthalliance.org/clark-county%2C-nv</a>
This is of concern to the community given the apparent overlap with the technical expertise of a DOGE employee, Ethan Shaotran, and his prior work for a Musk sponsored hackathon where he created software that could spoof ballot tabulation.<p><a href="https://github.com/DevrathIyer/ballotproof/tree/master">https://github.com/DevrathIyer/ballotproof/tree/master</a><p>Apparently, Shaotran removed his name from the repo and is now listed as a private user, but it can be found in the archive of the devpost page linked from the repo: <a href="https://devpost.com/software/ballotproof-vision" rel="nofollow">https://devpost.com/software/ballotproof-vision</a><p><a href="https://web.archive.org/web/20250204131222/https://devpost.com/software/ballotproof-vision" rel="nofollow">https://web.archive.org/web/20250204131222/https://devpost.c...</a><p>Info from: <a href="https://bsky.app/profile/cartwright776.bsky.social/post/3lhr4zni7ts2z" rel="nofollow">https://bsky.app/profile/cartwright776.bsky.social/post/3lhr...</a><p>Could this be used to spoof the results, and are there artifacts that could be discovered to directly link it or rule it out?<p>Here is an image from the Election Truth Alliance analysis that shows a possible artifact: <a href="https://img1.wsimg.com/isteam/ip/9087f51c-d3bd-4002-9943-79706c6e82a3/somethingiswrong2024-04%20(3)-16ff714.png/:/cr=t:0%25,l:0%25,w:100%25,h:100%25/rs=w:1209,cg:true" rel="nofollow">https://img1.wsimg.com/isteam/ip/9087f51c-d3bd-4002-9943-797...</a><p>PDF of their analysis: <a href="https://electiontruthalliance.org/clark-county%2C-nv" rel="nofollow">https://electiontruthalliance.org/clark-county%2C-nv</a>
FWIW, there is a much more damning piece of statistical evidence in the full report produced by the Election Truth Alliance.<p>Link to the full report: <a href="https://electiontruthalliance.org/clark-county%2C-nv" rel="nofollow">https://electiontruthalliance.org/clark-county%2C-nv</a><p>At the end of the full report, there are two histograms of the vote shares earned by Harris and by Trump, respectively, overlaid by a gaussian ("normal") distribution. Election shares tend to follow gaussian distributions [1]. In Clark County, NV, the election shares have a strong discontinuity that favors Trump, but only in Early Voting results.<p>This discontinuity only appears to exist on machines that tabulated a lot of results.<p>Past elections that are suspected to have been fraudulent (a few in Russia and one in Uganda, prior to 2012) show these exact same types of discontinuities, whereas elections that are generally regarded as secure do <i>not</i> show these types of discontinuities [1].<p>Are there other potential explanations for these discontinuities? ("Russian Tails" as they are colloquially known [2].) Yes! Election Truth Alliance <i>lists them out</i> as any proper data scientist would. Furthermore, ETA lists and links their datasets, and invites anyone to use them. This is what a model data scientist <i>should</i> do.<p>It seems that they are trying to get more data from more contested areas. What will they find? I don't know, but it seems that the more this phenomenon presents itself, then some of the alternate hypotheses can be ruled out.<p>[1] <a href="https://pmc.ncbi.nlm.nih.gov/articles/PMC3478593/" rel="nofollow">https://pmc.ncbi.nlm.nih.gov/articles/PMC3478593/</a><p>[2] <a href="https://www.rferl.org/a/georgia-election-manipulation-russian-tail/33183374.html" rel="nofollow">https://www.rferl.org/a/georgia-election-manipulation-russia...</a> *[Interesting that Elon wants to get rid of Radio Free Europe. -ed]
I was able to reproduce the vote skew / batch size correlation in early voting. The average batch size for mail voting was way higher (6 machines) and election day was lower (3x machines). The fact that the vote ratio is more distributed for mail voting with way more votes per machine is what highlights incongruity for me. Stats are not always intuitive though.
Articles like this are pure chutzpah. The same side that's alleging interference in 2024 suggested that to question election irregularities in 2020 was to reject democracy itself. I don't think the authors are going to convince anyone.<p>"But there's evidence this time and there wasn't in 2020!" Well, the other side would argue the opposite. We're not going to get anywhere this way.<p>Look: <i>regardless</i> of the the extent to which these alleged voting shenanigans are real, we need to fix the system. The legitimacy of the state is at risk.<p>Just as Caesar's wife must be above reproach, our voting system must be above reproach. There are plenty of common sense things officials can take to bolster the public's faith in the system. For example, we should ban electronic voting machines. The real threat to democracy isn't election manipulation but officials who refuse to enact measures that would dispel even the appearance of manipulation.
I'm honestly not sure that their analysis passes muster. It seems that the main consideration is that Harris underperformed compared to down-ballot races and that the underperformance was ahistoric. However, the campaign was also ahistoric: she ran as a pseudo-incumbent under an unpopular presidency without as much of the name recognition incumbency usually offers. It seems extremely likely to me that this drop off in early voting numbers is indicative of an exceptionally weak campaign as opposed to widespread (consistent across all swing states) manipulation.
Newsweek article that provides more context for the Election Truth Alliance's analysis as well as other claims (and statements by Trump alluding to it)<p><a href="https://www.newsweek.com/2024-election-rigged-donald-trump-elon-musk-2019482" rel="nofollow">https://www.newsweek.com/2024-election-rigged-donald-trump-e...</a>
It is possible to reproduce one of the key claims in this post -- the "Russian tail" in the early voting tallies -- straight from the raw data hosted on the Clark County, NV website. This code can be run in a Colab notebook:<p><pre><code> # Download and extract zip file
import requests
import zipfile
import io
# Get raw data from Clark County website
zip_url = "https://elections.clarkcountynv.gov/electionresultsTV/cvr/24G/24G_CVRExport_NOV_Final_Confidential.zip"
# Download the zip file
response = requests.get(zip_url)
zip_file = zipfile.ZipFile(io.BytesIO(response.content))
# Extract to the current working directory
zip_file.extractall()
# Close the zip file
zip_file.close()
import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
# Read the actual data, skipping the first three header rows and excluding downballot races
df = pd.read_csv('/content/24G_CVRExport_NOV_Final_Confidential.csv', skiprows=3, usecols=range(21), low_memory=False)
# Find the Trump and Harris columns
trump_col = "REP"
harris_col = "DEM"
# Convert to numeric
df[trump_col] = pd.to_numeric(df[trump_col], errors='coerce')
df[harris_col] = pd.to_numeric(df[harris_col], errors='coerce')
# Filter for early voting
early_voting = df[df['CountingGroup'] == 'Early Voting']
# Group by tabulator and calculate percentages
tabulator_stats = early_voting.groupby('TabulatorNum').agg({
harris_col: 'sum',
trump_col: 'sum'
}).reset_index()
# Calculate total votes and percentages
tabulator_stats['total_votes'] = tabulator_stats[harris_col] + tabulator_stats[trump_col]
tabulator_stats['harris_pct'] = tabulator_stats[harris_col] / tabulator_stats['total_votes'] \* 100
tabulator_stats['trump_pct'] = tabulator_stats[trump_col] / tabulator_stats['total_votes'] \* 100
# Create subplots
fig, (ax1, ax2) = plt.subplots(2, 1, figsize=(10, 8))
# Plot Harris histogram
ax1.hist(tabulator_stats['harris_pct'], bins=50, edgecolor='black', color='blue', alpha=0.7)
ax1.set_title('Distribution of Harris Votes by Tabulator (Early Voting Only)')
ax1.set_xlabel('Percentage of Votes for Harris')
ax1.set_ylabel('Number of Tabulators')
# Plot Trump histogram
ax2.hist(tabulator_stats['trump_pct'], bins=50, edgecolor='black', color='red', alpha=0.7)
ax2.set_title('Distribution of Trump Votes by Tabulator (Early Voting Only)')
ax2.set_xlabel('Percentage of Votes for Trump')
ax2.set_ylabel('Number of Tabulators')
plt.tight_layout()
plt.show()
</code></pre>
This produces a figure identical (up to histogram bucketing) to the one at the end of the linked article.
I'm writing this in response to the originator of this thread @beedeebeedee[1]. I'm posting it as a top-level comment because I believe it's applicable to the overall conversation.<p>> According to the theory, in fair elections, turnout indicators typically follow a regular graphical representation that resembles a bell shape. If anomalies appear in the data -- for example, forms different from the bell shape or the bell "grows a tail" -- this indicates unfair elections.<p>There is *no* respectable statistician who would *ever* draw a conclusion from data. You could say 'may indicate evidence of unfair elections,' but it is impossible to deem whether something occurred or not with 100% certainty.<p>Now to address their "indicators."<p>> While in cities the data representation mostly follows a bell shape, in the regions it is anomalously deviated<p>All statistics is just a representation of data, it tells us nothing of logic. Logic is also based in axioms and it's important to identify what those are.<p>Here the author is saying the data is "anomalously deviated" with the axiomatic assumption that all voters must follow the same distribution, but why should this assumption be held true? It ignores other logical factors that may sway these distributions.<p>If I'm a candidate for a political position that would give a rural precinct free money, wouldn't that heavily affect that population's voting outcomes? Surely what's said in a political campaign can sway these things, yet there's nothing in the article that mentions that.<p>> According to the theory, if a number of stations emerge where one candidate -- the "beneficiary" -- is unusually high, this might indicate falsification. There's a high risk of manipulation where increased overall voter turnout is reflected only in support of the "beneficiary."<p>So the belief is that because there are 2 distributions for the number of precincts with a certain percentage of "yes" votes, that automatically "indicates falsification"? There needs to be more information than this to make a conclusion. What one holds as axioms are a matter of opinion.<p>The only way to get something useful out of a counterargument to this is for a proponent to exhaustively list all the votes they think are legitimate, and for the opponent to show the same patterns can occur there as well.<p>Similarly for a proponent to convince detractors, they'd have to show that other elections they see as legitimate *never* indicate those patterns. Otherwise this is just an opinion piece on data.<p>[1] <a href="https://news.ycombinator.com/item?id=42996898">https://news.ycombinator.com/item?id=42996898</a>
Much more honest and thorough mathematical analyzes were performed on the 2020 election, some by major academic organizations. They showed far more suspicious patterns than this. If Trump or his associates were going to "hack" the election, Clack County NV wouldn't be where they did it. That's the old Harry Reid machine. It would be conspicuous. Harris was a bad candidate. Her VP choice was worse. Her campaign skills were lacking. Democrats lost because they deserted the working class. I grew up in a union family that voted democrat. The current party no longer resembles that party. The republicans, at least under Trump, do. When Trump is gone, another Bush type could arise, and then again the middle class will be without a party. That's why Harris lost.
This is a pretty inexperienced analysis.<p>I happened to have detailed day-by-day voting and registration data for the 2024 Nevada election as it was happening. Harris losing Nevada was telegraphed in the data almost from the beginning. Forget the top line totals, the underlying structure of where and who was registering and voting in real-time made the outcome all but a foregone conclusion weeks before the actual election. Nevada was some of the easiest money on the prediction markets.<p>Much is explained by an unusually robust turnout of low-propensity voters for Trump. They often don't care about the rest of the ballot, so it skews results albeit in a predictable way. (This is also the risk for Republicans; they are unlikely to show up for mid-terms and may sit on the sidelines again in four years.)<p>Nevada has consistently clean election processes. I am only aware of a single anomaly over the last several Federal elections that was clearly inexplicable. It wasn't this election, that instance looked like a system failure rather than fraud, and it didn't change the outcome. Some other States are rife with anomalies that persist even with sophisticated analysis most cycles.<p>If I was going to pick a State to look for Federal election irregularities, Nevada would be pretty low on my list. It is easy for amateurs to fool themselves into thinking they've found election fraud when really they just don't understand what is required to find a signal that holds up under sophisticated analysis. Same thing happened in 2020.<p>I also used to live in Nevada and am pretty attuned to the local politics. There are local bellwether statistics that are traditionally pretty reliable for indicating how an election will break. Harris was upside down on these too. The tortured rationalization by Nevada election pundits like Jon Ralston to reinterpret those as "good actually" was uncritically repeated widely in the national media.