First, you can't really weigh between doctor and self-reporting in the way you're suggesting. Doctor reports aren't that useful because they're reporting pretty much everything that happens within a time frame after the vaccine, which is by definition going to include most, if not all, garbage data that is unrelated to the vaccine. Self-reporting, on the other hand, carries almost no empirical data, and does not even confirm that the self-reported diagnosis is medically sound.
where you assume roughly 5% of the data is worthless...
See, almost everything you say is logical, except this part.
Let's define "worthless" in this case as "a medical symptom that occurred after the vaccine, but was not related to the vaccine." Would that be accurate? It's worthless data for your data set.
Now, why are you "assuming" that only 5% of that data is "worthless"?
Why can I not assume that 90% of the data is "worthless"? 99%? 100%?
Because that is absolutely, completely, unequivocally possible with VAERS. It may even be the case. Because VAERS does not verify a single report sent to it.
Let me be absolutely clear: if literally every single case submitted to VAERS right was completely unrelated to the vaccine, and the vaccine was completely safe, VAERS would look no different, and you would not be able to point to a difference in the VAERS data.
You assume only 5% of the data is worthless. Why? Why do you assume the data sent to VAERS would be accurately reporting vaccine injury?
VAERS does not claim this to be true. Nobody claims this to be true. In fact, it would be completely insane for any self-reporting system that is tracking millions and millions of individual people to have a 95% accuracy rate in reporting. That'd be ludicrous.
Can you empirically justify your assumption that only 5% of the data is worthless? That's a pretty important assumption to your argument, because if I instead assume that 99.99% of the data is worthless, instead of 5%, then your argument falls apart.
Contrary to your beliefs, I don’t cower in the face of claimed expertise.
You have NOT established which data sets are redundant. You have no way of establishing which data is worthless and which is not, because that is not contained in VAERS data, because they do not collect it. You are making an assumption about how much data useful, but you have no way of confirming even a single case via VAERS data.
I am not junking my data by establishing a 99% junk baseline. I’m doing that based on established studies showing vaccine reactions being far less than 1% and extrapolating from that. Reminder: just because you download VAERS data does not mean you have a means of verifying any single number as a vaccine injury.
I am not predetermining the value. I am seeing how many vaccine reactions happen in sample populations, and extrapolating. That’s what scientists do. VAERS is not a sample population because not a single entry has been proven to be related to a vaccine injury, as stated by VAERS.
Data doesn’t have to be a false report to be wrong. If someone submits a VAERS report that they have a migraine, that doesn’t mean vaccines cause migraines. It means that person did exactly what VAERS asked them to do. And that person was wrong, and their migraine had nothing to do with the vaccine. But VAERS is happy.
Most bad data is not false reports. It’s people who are wrong, but doing what they’re supposed to do and reporting anyway. And it’s doctors who are reporting absolutely everything, because they have to, not because they think the vaccine has anything to do with it.
Again, it is entirely possible that VAERS has less than ten reports in it reflecting actual vaccine damage, and it’s also possible that not a single fraudulent report is included. Just millions of wrong ones.
I have no idea why you think a control doesn’t exist if everyone is vaccinated. Of course it does. We know how prevalent myocarditis is in people before the COVID vaccine. That was our control. We also know what our rate is in our vaccinated population. That’s our experiment. Nobody needs a control and experimental group to run simultaneously. People existed and got sick before the vaccine. We don’t need unvaccinated people to track how things change after vaccination, obviously.
One of my graduate degrees is in information science. It's time to stop talking down to me like I have no idea what you're trying to say.
You are not "sampling" a population through VAERS data, because you cannot confirm literally anything about the VAERS population. Samples must be verifiable, and VAERS submissions are not verified.
Law of large numbers states that the larger the number, the more represented the outlier cases.
Which means that you are correct that IF the vaccine is capable of causing damage, then it will be represented in a large enough sample.
What you haven't established, and cannot establish, is what percentage of that sample population will represent outliers.
It may take a hundred million cases to even find a single vaccine injury. It'll be represented in a large population, but it'll still be a vanishingly small risk.
I can give you a bag of 1,000 coins, and you might feel pretty good about the representation of coins in there. Is there a good chance there's a gold dollar? Sure. A fifty-cent piece? Sure. They're rare, but they might be there.
But what about a buffalo penny? What about a misprinted quarter? Just because I have a large population of coins doesn't mean I have any reason to assume these very rare coins are present in the population. I can't make many assumptions about how many there are.
If I have 100,000 coins, or 100,000,000 coins, then I have a better chance of finding a very rare coin, but it'll still be a very small number of them compared to the total number of coins.
You're looking at VAERS data and assuming that if people are submitting, then at least SOME must have a legitimate vaccine injury.
This is incorrect.
There is no reason to believe this outside of the fact that you ALREADY believe that the vaccine causes injury. You are permitting that conclusion to taint how you are evaluating your data and guide your assumptions.
You assume the vaccine is hurting people and it's being covered up, therefore, 95% of the VAERS reports must be legitimate, despite what the actual verified data suggests.
But there is no reason to assume only 5% of the data is garbage. None. Nothing empirical you can provide. The law of large numbers only states that existing outliers will be represented in a large enough sample, not that you can make any assumptions about the proportion of the outliers to the total population based on that data alone.
First, you can't really weigh between doctor and self-reporting in the way you're suggesting. Doctor reports aren't that useful because they're reporting pretty much everything that happens within a time frame after the vaccine, which is by definition going to include most, if not all, garbage data that is unrelated to the vaccine. Self-reporting, on the other hand, carries almost no empirical data, and does not even confirm that the self-reported diagnosis is medically sound.
See, almost everything you say is logical, except this part.
Let's define "worthless" in this case as "a medical symptom that occurred after the vaccine, but was not related to the vaccine." Would that be accurate? It's worthless data for your data set.
Now, why are you "assuming" that only 5% of that data is "worthless"?
Why can I not assume that 90% of the data is "worthless"? 99%? 100%?
Because that is absolutely, completely, unequivocally possible with VAERS. It may even be the case. Because VAERS does not verify a single report sent to it.
Let me be absolutely clear: if literally every single case submitted to VAERS right was completely unrelated to the vaccine, and the vaccine was completely safe, VAERS would look no different, and you would not be able to point to a difference in the VAERS data.
You assume only 5% of the data is worthless. Why? Why do you assume the data sent to VAERS would be accurately reporting vaccine injury?
VAERS does not claim this to be true. Nobody claims this to be true. In fact, it would be completely insane for any self-reporting system that is tracking millions and millions of individual people to have a 95% accuracy rate in reporting. That'd be ludicrous.
Can you empirically justify your assumption that only 5% of the data is worthless? That's a pretty important assumption to your argument, because if I instead assume that 99.99% of the data is worthless, instead of 5%, then your argument falls apart.
I so enjoyed reading this chain, thank you 😊
Quickly.
Contrary to your beliefs, I don’t cower in the face of claimed expertise.
You have NOT established which data sets are redundant. You have no way of establishing which data is worthless and which is not, because that is not contained in VAERS data, because they do not collect it. You are making an assumption about how much data useful, but you have no way of confirming even a single case via VAERS data.
I am not junking my data by establishing a 99% junk baseline. I’m doing that based on established studies showing vaccine reactions being far less than 1% and extrapolating from that. Reminder: just because you download VAERS data does not mean you have a means of verifying any single number as a vaccine injury.
I am not predetermining the value. I am seeing how many vaccine reactions happen in sample populations, and extrapolating. That’s what scientists do. VAERS is not a sample population because not a single entry has been proven to be related to a vaccine injury, as stated by VAERS.
Data doesn’t have to be a false report to be wrong. If someone submits a VAERS report that they have a migraine, that doesn’t mean vaccines cause migraines. It means that person did exactly what VAERS asked them to do. And that person was wrong, and their migraine had nothing to do with the vaccine. But VAERS is happy.
Most bad data is not false reports. It’s people who are wrong, but doing what they’re supposed to do and reporting anyway. And it’s doctors who are reporting absolutely everything, because they have to, not because they think the vaccine has anything to do with it.
Again, it is entirely possible that VAERS has less than ten reports in it reflecting actual vaccine damage, and it’s also possible that not a single fraudulent report is included. Just millions of wrong ones.
One of my graduate degrees is in information science. It's time to stop talking down to me like I have no idea what you're trying to say.
You are not "sampling" a population through VAERS data, because you cannot confirm literally anything about the VAERS population. Samples must be verifiable, and VAERS submissions are not verified.
Law of large numbers states that the larger the number, the more represented the outlier cases.
Which means that you are correct that IF the vaccine is capable of causing damage, then it will be represented in a large enough sample.
What you haven't established, and cannot establish, is what percentage of that sample population will represent outliers.
It may take a hundred million cases to even find a single vaccine injury. It'll be represented in a large population, but it'll still be a vanishingly small risk.
I can give you a bag of 1,000 coins, and you might feel pretty good about the representation of coins in there. Is there a good chance there's a gold dollar? Sure. A fifty-cent piece? Sure. They're rare, but they might be there.
But what about a buffalo penny? What about a misprinted quarter? Just because I have a large population of coins doesn't mean I have any reason to assume these very rare coins are present in the population. I can't make many assumptions about how many there are.
If I have 100,000 coins, or 100,000,000 coins, then I have a better chance of finding a very rare coin, but it'll still be a very small number of them compared to the total number of coins.
You're looking at VAERS data and assuming that if people are submitting, then at least SOME must have a legitimate vaccine injury.
This is incorrect.
There is no reason to believe this outside of the fact that you ALREADY believe that the vaccine causes injury. You are permitting that conclusion to taint how you are evaluating your data and guide your assumptions.
You assume the vaccine is hurting people and it's being covered up, therefore, 95% of the VAERS reports must be legitimate, despite what the actual verified data suggests.
But there is no reason to assume only 5% of the data is garbage. None. Nothing empirical you can provide. The law of large numbers only states that existing outliers will be represented in a large enough sample, not that you can make any assumptions about the proportion of the outliers to the total population based on that data alone.