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>>189749Eric Graves @EricGravesKMBC - Video: “We won so fast I wasn’t even ready for the speech.”
State Sen. Ty Masterson is on to November as the Republican candidate for Kansas Governor. He just took the stage in Wichita. Live report at 10 on @kmbc.
https://x.com/EricGravesKMBC/status/2084825088634089911Ethical Skeptic @EthicalSkeptic - "The standout finding was that the single best-performing site in the entire country - the one with the lowest (and even favourable) mortality statistics - was located in Wellington Central, right in the seat of government."
Pharma and Govmt insiders whispered to get saline shots, and where to find the locations giving them.
Folleagues knew over 4 years ago that this was the case.
Quoted Post:
Liz Gunn @LizGunnNZ - Video: Barry Young: The Safest Vaccine Site in New Zealand Was Right Next to Parliament
@BarryYoungNZ explains the detailed statistical analysis he performed on the New Zealand vaccination data. Using the same tools an epidemiologist would employ - graphs, confidence intervals, Poisson scores, p-values and Standardised Mortality Rates (SMRs) - he examined both the national picture and individual vaccination sites.
While the overall data showed excess mortality, results varied sharply by location: some sites recorded significantly elevated deaths, others performed better than expected.
The standout finding was that the single best-performing site in the entire country - the one with the lowest (and even favourable) mortality statistics - was located in Wellington Central, right in the seat of government.
Barry notes that this variation suggests the doses were not uniform across New Zealand and raises the unresolved question of why the centre nearest Parliament produced such markedly different results.
A clear, data-driven examination of what site-level analysis reveals.
Transcript:
“I was thinking, well, as an epidemiologist, how would they look at this data?
What would they do? What tools would they use? How would they analyse it?
So I went through, did all the card and for it, got the nice graphs, charts, analysis, numbers, confidence intervals, Poisson scores, all the p-values, all that stuff to work out the probabilities and all the rest of it.
To work out if it was dangerous, SMRs, standardised mortality rates.
You know, one is normal.
SMR1 should be one to one mortality rate before and after the vaccine.
You’ve got the same number of people alive, same number of people alive after the vaccine.
That’s an SMR1.
If it’s SMR higher than one, you’ve got more people dying after the vaccine than should die after the vaccine.
SMR less than one, there’s more people living - Vaccines working, great.
So that’s how it works. That’s the SMR.
So anyway, I did all of that analysis and provided it for multiple sites across New Zealand. So I was doing it specifically by site.
So I’ve done the work for the whole data in general, which shows excess mortality.
But I also did it for certain sites in New Zealand, some bad ones, some not so bad, some very, very good.
Just to show that my analysis was whole and correct and valid and validated everything, because some sites I looked at, mortality was not elevated.
It was actually less than expected, which is like, OK, it proves my method works. It’s accurate.
It is picking out the bad ones, the really bad ones.
It’s also picking out some good ones as well.
But there are far fewer good ones than there are bad ones.
And the key thing to see here, I don’t think I’ve discussed this.
The key thing to realise is that the good one, the really good one, the star of the show and the whole of New Zealand, the best site was in Wellington Central itself, the seat of the government, the heart of the city.
So go figure, why did that have the best mortality statistics in the whole entire database?
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