Well, they're being taken as proof, more precisely, that myocarditis *is* a problem for Moderna, but not for Pfizer-BioNTech. This is the European dogma. But US CDC data shows myocarditis risk to be roughly equal between Moderna and Pfizer-BioNTech. See here: https://twitter.com/EdV1694/status/1477582007270096900?s=20. Any idea about how to explain the discrepancy between this study and the raw US data?
I have a few questions for all the number specialists, table designers and statistics interpreters:
After two years of data accumulation in the context of the ''pandemic'', does it make any sense at all to extract any statement from this mountain of data? Does the result of a data evaluation still serve any truth at all?
Why do I ask? Well, in the meantime there are so many overlaps in the definition of unvaccinated and vaccinated, of recovered and diseased, to which constantly changing definitions differing from country to country are added, that there are no longer any possibilities for comparison with which any trends or conspicuous features can be uncovered. All of the data only creates a nebulous, ever-changing picture that, in its constant succession of snapshots, creates more confusion than clarity.
Does it still somehow make sense to put so much energy into data evaluation day after day, if no one is able to produce ONE clear picture from all the different evaluations that could really help us? I don't want to diminish in any way the efforts and expertise of many people who make their evaluation skills available to the general public on a daily basis, I just wonder what drives you? Do you feel that your efforts are really bearing fruit, that something good is coming out of your work for the community? Something that will expose all those who have been lying to us and leading us around by the nose for months now. Something that many would like to see happen, of course, but is always unlikely to happen - at least that's how I feel.
It seems to me that this is exactly the intention behind all the constantly changing definitions using non-standardized tests with ever questionable interpretations on their part. As if the aim is to generate as much confusion as possible in the data jungle so that the general public completely loses its orientation and at some point stops asking questions altogether.
I would be very interested in your opinion on this and I would like to thank all of you who are always putting so much energy into bringing light into the darkness, even if the darkness never really seems to go away.
I so agree with the paragraphs at the end of your post of the things that disturb you. Those are so true! And the general public is none the wiser, I wonder how many people will never know the truth....
Here are a few studies that didn't make it into the Nature limelight:
https://elcolectivodeuno.wordpress.com/2021/12/29/how-much-more-evidence-do-you-need-here-is-a-list-of-860-scientific-studies-and-reports-linking-covid-vaccines-to-hundreds-of-adverse-effects-and-deaths/
Well, they're being taken as proof, more precisely, that myocarditis *is* a problem for Moderna, but not for Pfizer-BioNTech. This is the European dogma. But US CDC data shows myocarditis risk to be roughly equal between Moderna and Pfizer-BioNTech. See here: https://twitter.com/EdV1694/status/1477582007270096900?s=20. Any idea about how to explain the discrepancy between this study and the raw US data?
Beautifully illustrated.
I have a few questions for all the number specialists, table designers and statistics interpreters:
After two years of data accumulation in the context of the ''pandemic'', does it make any sense at all to extract any statement from this mountain of data? Does the result of a data evaluation still serve any truth at all?
Why do I ask? Well, in the meantime there are so many overlaps in the definition of unvaccinated and vaccinated, of recovered and diseased, to which constantly changing definitions differing from country to country are added, that there are no longer any possibilities for comparison with which any trends or conspicuous features can be uncovered. All of the data only creates a nebulous, ever-changing picture that, in its constant succession of snapshots, creates more confusion than clarity.
Does it still somehow make sense to put so much energy into data evaluation day after day, if no one is able to produce ONE clear picture from all the different evaluations that could really help us? I don't want to diminish in any way the efforts and expertise of many people who make their evaluation skills available to the general public on a daily basis, I just wonder what drives you? Do you feel that your efforts are really bearing fruit, that something good is coming out of your work for the community? Something that will expose all those who have been lying to us and leading us around by the nose for months now. Something that many would like to see happen, of course, but is always unlikely to happen - at least that's how I feel.
It seems to me that this is exactly the intention behind all the constantly changing definitions using non-standardized tests with ever questionable interpretations on their part. As if the aim is to generate as much confusion as possible in the data jungle so that the general public completely loses its orientation and at some point stops asking questions altogether.
I would be very interested in your opinion on this and I would like to thank all of you who are always putting so much energy into bringing light into the darkness, even if the darkness never really seems to go away.
FYI: https://edv1694.substack.com/p/something-is-rotten-in-denmark-on
I so agree with the paragraphs at the end of your post of the things that disturb you. Those are so true! And the general public is none the wiser, I wonder how many people will never know the truth....