Hi Matthew, I hope you are in contact with the retired UK NHS statistician (ex Head of Clinical Audit) who calls himself John Dee? [See https://www.facebook.com/groups/johndeealmanac?sorting_setting=CHRONOLOGICAL] With his perceptive audits of a range of C-Vid data, his truths have been keeping us feeling more sane than we might otherwise, given unremitting MSM propaganda. I'm glad too that a reader of John's pointed to your interview with Steve Kirsch.
Facebook has banned me forever. Not with just one account but with 4 different accounts! They didn't like me showing what is wrong with the mathematics of vaccines, what is wrong with vaers, what is wrong with spike proteins. blah blah blah. So, I left. That was a year ago.
My overall impression of the FB fact checks is that they contradict reality. I seldom log in but when I do, if I see something labeled 'false' or 'partially false', I know it's probably an unwelcome truth and I then do the digging. When I bother to read their justification for their label, it's impressive how often their sources are flawed or lame. These people are utterly desperate.
My guess is that Youtube and Facebook fact-checks are done by algorithms (or AI). I'm not sure they hire a lot of people to read through posts or watch to the end of videos.
I had similar thoughts regarding the claims of Simpson's Paradox. Prior to actually decomposing the 10-59 data, the possibility that Simpson's Paradox is in play is a decent assumption but until the data is fully scrubbed one doesn't really know if SP applies or not. Sure the younger cohorts are healthier but maybe the vaxx is doing something that overwhelms that health advantage.
We crossed some inflection point awhile back where the 'fact-checkers' and their echo chamber allies have become so unmoored from reality that they're no longer capable of lying competently.
A corollary is they can't speak without beclowning themselves. And, they don't even know it.
Matthew, new subscriber thanks to a recommendation by Steve Kirsch. I’m so glad I subscribed! Between you, Steve Kirsch, Bad Cattitude, Alex Berenson, Tehno Fog, and others, my faith in humanity is bolstered significantly. When smart, thoughtful, reasoned people write the truth, more enlightenment occurs. Good luck with your move, and God Bless you and your family this Thanksgiving weekend.
From the corrected data I think I see the vaccine happy valley, then deaths from the vaccines set in, then all that were going to die did die from the shots, and the unvaxxed (I mean, how many unvaxxed actually exist in UK at this time?) start to come out with more deaths. Maybe what the shots have done is eliminate the weakest and left only the very toughest.
May I suggest Steve, that if Craig’s work does not seem a blind alley to you, that you put up a post about it on your substack?
I was alerted to the first of these videos by John Knowalittle. I don’t know who he is, but for some time I have been on an email list that he uses, and much of the information he sends out is worth paying attention to.
Jessica you threw a wetblanket over some of the first iterations of this line of investigation. These later iterations by Craig go much further and are particularly striking.
In our present circumstances it is important that we not get too distracted by noise. If this email turns out to be noise I beg your forgiveness, but at this point I think it too patently an important signal for me to delay distribution in order to do any further double-checking of my own.
The following is the backstory to my interest in this:
I became aware of Steve Kirsch’s perspective when he was with Robert Malone on the Brett Weinstein show. Jessica Rose and Mathew Crawford were collaborating with Steve, so I began following them, subscribing to both their substacks. Sometime around then I became aware of the pattern in VAERS drawn attention to by Karl Denninger at https://market-ticker.org/akcs-www?post=244109. Probably it was mentioned in some comment on one of Jessica’s, Mathew’s or Steve’s substacks.
Just before that last post of Andreas was put up, the following thread between Jessica and Tim Lundeen took place. It is here where you threw your wetblanket Jessica, and it caused me temporarily to avert my attention from this, but with Craig’s analysis my attention has returned. The thread is here,
It would be interesting to look at distribution of death/injury by days post vaccination, for both high and low-injury lots. I wonder if the distribution of AEs for low-injury lots is random (implying the vaccine was not causal), while the high-injury lots show high rates of AEs shortly after vaccination (implying causality).
Reply
Jessica RoseNov 5
AUTHOR
this isn't credible... sorry to be a wet blanket...
no it's not nefarious (one of the only things) it's just human error and humans having too much to do and not caring too much
Reply
Tim LundeenNov 6
No problem, I like to live in the real world, and we figure things out though discussion and analysis. So I appreciate your comment.
What do you see as the problems/issues that make it not credible? Their data analysis is easy to reproduce -- just download the data and attach the lot number to each event, sort by lot number. I know of three people who claim to have done this, and they all get the same answers.
Reply
Jessica RoseNov 6
AUTHOR
and therein... lies the problem :)
1Reply
Jessica RoseNov 6
AUTHOR
"it appears that they used VAERS data. they wrote an 'algorithm' to count the vax lots written in that market-ticker document but again, the problems that i described previously make claims about vax lots improbable due to sparse data.
again, i backup their assessment of the 'worst lots' for Pfizer and Moderna (almost precisely with numbers) but I don't think that it's worthy of horn-blowing due to the percentage of deaths imposed by each when calculated in the context of total deaths. 30% of all VAX_LOT fields have an "NA" (not applicable) entry and for the most part for the fields with entries, these entries are filled in 'incorrectly' (a notorious problem in VAERS which is why caution/precision must be used when using this data), and thus it is very difficult to make any claims about significant patterns.
Moderna -> vax_lot 039K20A has been associated with 86 deaths (2% of all deaths)
Pfizer _> EN6201 has been associated with 85 deaths (2.2% of all deaths)
Janssen -> 1805029 has been associated with 38 deaths (4% of all deaths)
again, one third of the death data has NO VAX LOT DATA tied to the VAERS ID.
i don't mean to be a persistent wet blanket but i don't think this floats. i would have been screaming from the rooftops to announce this finding back in ... if it did. i really did think this was going to work as a way to more precisely define why certain vax lots are more dangerous than others - i mean, defining this using analyzed VAERS data - but then i realized sparse data was an ongoing problem. to solve this problem, someone needs to go in to the source VAERS data and clean these entries up (at the filling in/vetting step) and they need to be filled in properly from the start. so there are levels of clean up that need to be achieved and probably never will be. VAERS is just problematic this way.
the really annoying thing here is that certain vax lots most definitely are more problematic with regards to SAEs than others. even if simply by contamination! but, to prove this... is another story. a difficult and ongoing one."
1Reply
Tim LundeenNov 6
Thanks, very much appreciate this explanation. I'll link to this from Karl's site.
I think we are forgetting one of the biggest problems with all this data: selection bias. In particular, I suspect that in the under 60s crowd, MOST of the deaths come from a particular group: those who are morbidly ill. The question is: are they MORE or LESS likely to get vaccinated? They might be less likely because their morbid illness makes them think they won't be able to handle the vaccine. Even if you adjust by health, the group of the "most ill" and "most likely to die" may opt out of vaccine in greater proportions. That is likely the largest portion of deaths. That's enough to skew these results to make the data basically meaningless.
Given there is no clear BENEFIT to vaccination seeing this data, I would suggest a way forward here is to fund long term clinical trials, independent of the pharma companies.
Otherwise it's gonna be the statistics wars... where everybody can gerrymander the results to fit their narrative.
Other than that, is there really any other way to avoid the problem of selection bias in deciding to get vaccinated?
Interesting that you post an image captioned "Funny thing about geting caught in a lie. Anything you ever said becomes questionable." You repeat the following lie in Chloroquine Wars Part LII: "every death in the VAERS dataset has COVID-19 as their primary symptom at the time of death."
Not a shred of truth. Repeating the lies of another liar as if they were true does not make you a truth-teller. Your entire bogus derivation of vaccine risk from case fatality rate is predicated on this lie.
You are so calm about this.
I am furious on your behalf.
You are doing such diligent work. There are many of us that appreciate you.
I wonder if anyone actually takes these professional "fact checkers" seriously.
Hi Matthew, I hope you are in contact with the retired UK NHS statistician (ex Head of Clinical Audit) who calls himself John Dee? [See https://www.facebook.com/groups/johndeealmanac?sorting_setting=CHRONOLOGICAL] With his perceptive audits of a range of C-Vid data, his truths have been keeping us feeling more sane than we might otherwise, given unremitting MSM propaganda. I'm glad too that a reader of John's pointed to your interview with Steve Kirsch.
Facebook has banned me forever. Not with just one account but with 4 different accounts! They didn't like me showing what is wrong with the mathematics of vaccines, what is wrong with vaers, what is wrong with spike proteins. blah blah blah. So, I left. That was a year ago.
My overall impression of the FB fact checks is that they contradict reality. I seldom log in but when I do, if I see something labeled 'false' or 'partially false', I know it's probably an unwelcome truth and I then do the digging. When I bother to read their justification for their label, it's impressive how often their sources are flawed or lame. These people are utterly desperate.
Facebook liked to put up fact check warnings whenever I put up figures from VAERS or the UK ONS. Sick of it so left the platform.
My guess is that Youtube and Facebook fact-checks are done by algorithms (or AI). I'm not sure they hire a lot of people to read through posts or watch to the end of videos.
I had similar thoughts regarding the claims of Simpson's Paradox. Prior to actually decomposing the 10-59 data, the possibility that Simpson's Paradox is in play is a decent assumption but until the data is fully scrubbed one doesn't really know if SP applies or not. Sure the younger cohorts are healthier but maybe the vaxx is doing something that overwhelms that health advantage.
You don't know until you know. Know what I mean?
We crossed some inflection point awhile back where the 'fact-checkers' and their echo chamber allies have become so unmoored from reality that they're no longer capable of lying competently.
A corollary is they can't speak without beclowning themselves. And, they don't even know it.
The Emperor really is naked.
Love everything you do man. Thanks for making some sense of this Topsy-turby clownworld.
Matthew, new subscriber thanks to a recommendation by Steve Kirsch. I’m so glad I subscribed! Between you, Steve Kirsch, Bad Cattitude, Alex Berenson, Tehno Fog, and others, my faith in humanity is bolstered significantly. When smart, thoughtful, reasoned people write the truth, more enlightenment occurs. Good luck with your move, and God Bless you and your family this Thanksgiving weekend.
From the corrected data I think I see the vaccine happy valley, then deaths from the vaccines set in, then all that were going to die did die from the shots, and the unvaxxed (I mean, how many unvaxxed actually exist in UK at this time?) start to come out with more deaths. Maybe what the shots have done is eliminate the weakest and left only the very toughest.
Thanks for sharing this-- the fact check makes it appear, before clicking through, that they are arguing on behalf of Alex.
Hello Jessica Rose, Mathew Crawford and Steve Kirsch,
Thanks so much for the work you and others do.
I had trouble finding emails for Jessica and Matthew, so I am posting this as a comment on your substacks. I have an email address for Steve.
I urge you to watch these two videos put out by Craig Paardekooper and give comment. They strike me as extremely important.
https://brandnewtube.com/watch/patterns-in-the-deployment-of-toxic-covid-vaccine-batches_x3LiCNOENb23dnk.html: Patterns in the Deployment of Toxic Covid Vaccine Batches
https://brandnewtube.com/watch/variation-in-the-toxicity-of-different-covid-vaccine-batches_dL2OVVSgmx9qXII.html: Variation in the Toxicity of Different Covid Vaccine Batches
May I suggest Steve, that if Craig’s work does not seem a blind alley to you, that you put up a post about it on your substack?
I was alerted to the first of these videos by John Knowalittle. I don’t know who he is, but for some time I have been on an email list that he uses, and much of the information he sends out is worth paying attention to.
Jessica you threw a wetblanket over some of the first iterations of this line of investigation. These later iterations by Craig go much further and are particularly striking.
In our present circumstances it is important that we not get too distracted by noise. If this email turns out to be noise I beg your forgiveness, but at this point I think it too patently an important signal for me to delay distribution in order to do any further double-checking of my own.
The following is the backstory to my interest in this:
I became aware of Steve Kirsch’s perspective when he was with Robert Malone on the Brett Weinstein show. Jessica Rose and Mathew Crawford were collaborating with Steve, so I began following them, subscribing to both their substacks. Sometime around then I became aware of the pattern in VAERS drawn attention to by Karl Denninger at https://market-ticker.org/akcs-www?post=244109. Probably it was mentioned in some comment on one of Jessica’s, Mathew’s or Steve’s substacks.
I also discovered these posts on The Expose:
https://theexpose.uk/2021/11/04/88-percent-covid-19-deaths-among-fully-vaccinated/
https://theexpose.uk/2021/10/31/100-percent-of-covid-19-vaccine-deaths-caused-by-just-5-percent-of-the-batches-produced/ and then Andreas Oehler’s take on the issue here: https://live2fightanotherday.substack.com/p/falling-into-place-like-dominoes: Falling into Place Like Dominoes.
Further searches turned up:
https://theexpose.uk/2021/11/01/dr-mike-yeadon-just-when-you-though-things-couldnt-get-any-worse/ https://sarahwestall.com/analysis-100-of-deaths-following-covid-19-shots-are-from-only-5-of-the-manufacturer-lots-according-to-vaers/
Andreas Oehler put up a further post here: https://live2fightanotherday.substack.com/p/exposing-the-expose-in-good-way: Exposing THE EXPOSE. Notice that the explanation put forward here by Andreas is at odds with Craig’s. There needs to be a reconciliation of the differences.
Just before that last post of Andreas was put up, the following thread between Jessica and Tim Lundeen took place. It is here where you threw your wetblanket Jessica, and it caused me temporarily to avert my attention from this, but with Craig’s analysis my attention has returned. The thread is here,
https://jessicar.substack.com/p/a-report-on-myocarditis-adverse-events/comments, as follows:
<Begin quote>
Tim LundeenNov 2
There is another safety signal, distribution of death/injury by lot number. https://market-ticker.org/akcs-www?post=244109
It would be interesting to look at distribution of death/injury by days post vaccination, for both high and low-injury lots. I wonder if the distribution of AEs for low-injury lots is random (implying the vaccine was not causal), while the high-injury lots show high rates of AEs shortly after vaccination (implying causality).
Reply
Jessica RoseNov 5
AUTHOR
this isn't credible... sorry to be a wet blanket...
2Reply
Tim LundeenNov 7
More details and thoughts on this at https://market-ticker.org/akcs-www?post=244109&page=19 scroll down to "Tourist"
Reply
Tim LundeenNov 7
Another explanation for this that makes sense: it is just suppressed reporting. https://live2fightanotherday.substack.com/p/exposing-the-expose-in-good-way
Reply
Jessica RoseNov 7
AUTHOR
no it's not nefarious (one of the only things) it's just human error and humans having too much to do and not caring too much
Reply
Tim LundeenNov 6
No problem, I like to live in the real world, and we figure things out though discussion and analysis. So I appreciate your comment.
What do you see as the problems/issues that make it not credible? Their data analysis is easy to reproduce -- just download the data and attach the lot number to each event, sort by lot number. I know of three people who claim to have done this, and they all get the same answers.
Reply
Jessica RoseNov 6
AUTHOR
and therein... lies the problem :)
1Reply
Jessica RoseNov 6
AUTHOR
"it appears that they used VAERS data. they wrote an 'algorithm' to count the vax lots written in that market-ticker document but again, the problems that i described previously make claims about vax lots improbable due to sparse data.
again, i backup their assessment of the 'worst lots' for Pfizer and Moderna (almost precisely with numbers) but I don't think that it's worthy of horn-blowing due to the percentage of deaths imposed by each when calculated in the context of total deaths. 30% of all VAX_LOT fields have an "NA" (not applicable) entry and for the most part for the fields with entries, these entries are filled in 'incorrectly' (a notorious problem in VAERS which is why caution/precision must be used when using this data), and thus it is very difficult to make any claims about significant patterns.
Moderna -> vax_lot 039K20A has been associated with 86 deaths (2% of all deaths)
Pfizer _> EN6201 has been associated with 85 deaths (2.2% of all deaths)
Janssen -> 1805029 has been associated with 38 deaths (4% of all deaths)
again, one third of the death data has NO VAX LOT DATA tied to the VAERS ID.
i don't mean to be a persistent wet blanket but i don't think this floats. i would have been screaming from the rooftops to announce this finding back in ... if it did. i really did think this was going to work as a way to more precisely define why certain vax lots are more dangerous than others - i mean, defining this using analyzed VAERS data - but then i realized sparse data was an ongoing problem. to solve this problem, someone needs to go in to the source VAERS data and clean these entries up (at the filling in/vetting step) and they need to be filled in properly from the start. so there are levels of clean up that need to be achieved and probably never will be. VAERS is just problematic this way.
the really annoying thing here is that certain vax lots most definitely are more problematic with regards to SAEs than others. even if simply by contamination! but, to prove this... is another story. a difficult and ongoing one."
1Reply
Tim LundeenNov 6
Thanks, very much appreciate this explanation. I'll link to this from Karl's site.
<End quote>
Thanks for your attention to this.
I think we are forgetting one of the biggest problems with all this data: selection bias. In particular, I suspect that in the under 60s crowd, MOST of the deaths come from a particular group: those who are morbidly ill. The question is: are they MORE or LESS likely to get vaccinated? They might be less likely because their morbid illness makes them think they won't be able to handle the vaccine. Even if you adjust by health, the group of the "most ill" and "most likely to die" may opt out of vaccine in greater proportions. That is likely the largest portion of deaths. That's enough to skew these results to make the data basically meaningless.
Given there is no clear BENEFIT to vaccination seeing this data, I would suggest a way forward here is to fund long term clinical trials, independent of the pharma companies.
Otherwise it's gonna be the statistics wars... where everybody can gerrymander the results to fit their narrative.
Other than that, is there really any other way to avoid the problem of selection bias in deciding to get vaccinated?
Interesting that you post an image captioned "Funny thing about geting caught in a lie. Anything you ever said becomes questionable." You repeat the following lie in Chloroquine Wars Part LII: "every death in the VAERS dataset has COVID-19 as their primary symptom at the time of death."
Not a shred of truth. Repeating the lies of another liar as if they were true does not make you a truth-teller. Your entire bogus derivation of vaccine risk from case fatality rate is predicated on this lie.