The NGO Project XXII: CTCL in NJ
Liberty and Prosperity 1776
Introduction
Question: Is CTCL misrepresenting the information on the IRS Form 990 stating that the PURPOSE of the grants were to help support the SAFE administration of public elections during the Covid-19 pandemic?
Answer: It appears so given the results of both aggregate, state and county by county analysis as we will see below. It appears this is a quantifiable democrat ballot harvesting operation.
Background
This is Part XXII in The NGO Project series which examines the role NGOs had in determinative outcomes in the 2020 Presidential Election. In prior articles, I focused on the effect CTCL had on AZ, CO, CT, GA, IA, ME, ME, MI, NC, NH, NM, NY, OH, PA, RI, TX, UT, VT, VA and WI.
This article will solely focus on CTCL in New Jersey (NJ).
Calculation Basis
The calculation basis was previously explained in detail here. In this article, I do make one adjustment and that is to calculate the 2020DIFF factor by weighted average rather than arithmetic average.
Analysis
CTCL made 24 grants to ALL 21 counties in NJ.
Therefore, I cannot compare CTCL counties to NonCTCL counties in NJ. A simpler approach will be used for this analysis.
All 4,564,616 votes cast were impacted by CTCL because every county received grants.
The total amount of grants to NJ was ~ $20,418,892 and the value of individual grants ranged from ~ $67,000 to $3,203,500.
$12.5MM of the grants (61%) were focused in 5 counties of Bergen, Burlington, Camden, Essex and Passaic. These counties account for ~ 35% of all votes in NJ. To put it another way, 61% of the grant money was distributed to 35% of the cast votes.
The $/vote spent by CTCL in all counties range from $0.98/vote to $14.28/vote (all parties).
Passaic County received the most grant money and has the highest $/vote total….hmmm.
The average 2016 D/R ratio is 1.40. The average 2020 D/R ratio is 1.43 indicating no significant shift.
2020DIFF Calculated with Weighted Average
For this analysis, I used a slightly different way to calculate the 2020DIFF using a weighted average based on total votes in a county. This is what it looks like.
w = Total County Vote / Total State Vote
a = D/R2020 - D/R2016 (for CTCL Counties)
a' = a * w (per county)
2020DIFF = sum(a'1:a'n)
This method in theory permits a better correlation for D vote harvesting because it is weighted for counties with higher vote totals.
As stated above, my typical model does not work for NJ because all counties received grants.
Therefore, if you just calculate the weighted average of 2020DIFF for all counties, you end up with 0% factor. This is strange, what might this be attributed too?
Because I am using a weighted average AND the counties of Essex, Hudson and Passaic show a significant -2020DIFF, the effective D contribution averages out to be negative. Therefore no D harvesting factor can be calculated for NJ.
The arithmetic average of 2020DIFF is 2% however, FYI.
These are the 5 counties with the heaviest shift to D’s. If I lived in NJ, I would dig into these at a minimum.
My conclusions are the following.
Either CTCL spending actually helped Republicans in terms of creating -2020DIFF values for the state…..
Or despite CTCL spending Republican turned out in greater ratios but it didn’t matter do the prevalence of fraud in heavy D counties.
You decide.
Conclusion
CTCL issued ~$20.5MM in grants in NJ but apparently R’s turned out in heavier ratios anyway. NJ requires further digging.
References
CTCL IRS Form 990 (revised form from Jan 2022 used)
Telegram - https://t.me/electiondataanalyzer
Truth - @ElectionDataAnalyzer
The math here is simple, try this on your own. It is a model to look for trends, not an exact science.