I'm not looking at the data wrong. There are only (about) 300 unique batch numbers, once you remove typos.(Prove me wrong.)
Due to that fact alone, you can't have an analysis that says there are 200 'safe' batches for every 'toxic' batch. (It would mean you either have one or two 'toxic' batches.)
Look at the data that comes from your search...
I'm currently looking at a region around Jun 2021, and (genuine) batch number '042A21A'. That batch number is represented dozens and dozens of ways in the database.
Each of the **'A'**s are sometimes represented as a '4' or an '8' or an 'H' (the first is a 'looks like' error, the second two are a 'sounds like' error.)
Each of the **'2'**s are sometimes changed to a 'Z'.
Sometimes people put a dash (or space or hashtag) between '042A' and '21A'. Sometimes in other places.
Sometimes some of the numbers or letters are simply left off.
Therefore, you could see "042A214", "042A -21A", "042AZ1A", "042A218", "042-A21A", "#042A21A", "042421A", "042A21H", and so on - which are all the same batch.
When you figure out how many ways this ONE batch number is represented in the database, it staggers the imagination. And each one of these 'false' batch numbers is assumed (by the video) to be a 'safe batch' because it only links to one adverse event.
The database is hopelessly 'unclean'. If you (or someone else) has a carefully cleaned version, please let me know. Without removing the 'fake' batch numbers, you cannot run an analysis.
In the search you provided, the 'largest batches' that I saw was one called 'Unknown' with 1,782 cases - and another called 'NONE' with 4,669 cases.
The truth is that (if you look at only the real batches), most have a serious ('toxic') number of links - AND you are still missing all the links that are 'lost' because they are 'spread out' among all the typos. And then, you still can't compare batch to batch unless you know that the batches are all the same size - and the CDC specifically refuses to release that data to the public.
Why are you making your argument about typos when I already said there are obvious typos? Straw-man much?
I specifically trimmed a search to make all of that obvious AND provided a way to verify WITH the manufacturer the validity of the batch # WHICH WAS TO DEAL WITH THE ARGUMENT YOU JUST MADE AGAIN IN DETAIL.
Focusing / highlighting only UNKNOW batches is just intellectually dishonest as that's not what I'm pointing to.
I spend 4 hours a day, 5 days a week in VAERS data. I know it's full of typos and I know how to look at the data and generate very tailored and specific reports.
What we can clearly see though, despite that, is REAL batches with X numbers of issues and REAL batches with XXX of issues. for J&J alone. THAT is what I was pointing to.
We can also put missing series numbers into the J&J page and see they are valid batches and hypothesize those may be saline or something neutral.
I am not offerring straw men. I see a genuine danger of having people think "Oh, there's such a really small chance that I can get a bad batch, so why not take it? I can keep my job, etc..."
The message (of 'mostly benign batches') will make no difference to those of us who will never take it, but there are those 'on the fence' who are at risk. A video like this might 'please' us, but it puts others in danger.
Nobody should take this vax.
If you are a numbers guy (like me, a programmer), you know that you can't judge how toxic a batch is unless you know both the numerator and the denominator. 'How many bad events in this batch' divided by 'how big the batch is'.
You might call this another straw man, but I don't see anywhere, in any data set, how we know the size of each batch (how much was manufactured in the batch, and how much was destroyed in the field due to expiration, etc). Pfizer and Moderna aren't telling us, and the CDC (who admits that they know) won't disclose it to the general public.
If Batch1 has 5000 bad events in VAERS, and Batch2 has only 500 - it is not valid to say that Batch2 is 'safer' unless you know the relative sizes of the batches (the denominators). What if Batch1 was 20 times as large as Batch2? Then Batch1 would actually be the safer batch - even with 10 times the events. Simple math.
Now if you know the size of each batch, of each manufacturer, and how much of each batch was actually used (not expired or discarded), please let me know how you know. I would love to have more info.
Incidentally, I made a post over a month ago that described this exact concept (doses are mostly benign/saline, with a 'fine tweaking' to produce desired results) - so I agree that they are doing this. It's just that this data does not prove it.
Post: "If they give SALINE to almost everyone (the first time around), they still get ALL of their EVIL BENEFITS. Here's how..."
I'm not looking at the data wrong. There are only (about) 300 unique batch numbers, once you remove typos. (Prove me wrong.)
Due to that fact alone, you can't have an analysis that says there are 200 'safe' batches for every 'toxic' batch. (It would mean you either have one or two 'toxic' batches.)
Look at the data that comes from your search...
I'm currently looking at a region around Jun 2021, and (genuine) batch number '042A21A'. That batch number is represented dozens and dozens of ways in the database.
Each of the **'A'**s are sometimes represented as a '4' or an '8' or an 'H' (the first is a 'looks like' error, the second two are a 'sounds like' error.)
Each of the **'2'**s are sometimes changed to a 'Z'.
Sometimes people put a dash (or space or hashtag) between '042A' and '21A'. Sometimes in other places.
Sometimes some of the numbers or letters are simply left off.
Therefore, you could see "042A214", "042A -21A", "042AZ1A", "042A218", "042-A21A", "#042A21A", "042421A", "042A21H", and so on - which are all the same batch.
When you figure out how many ways this ONE batch number is represented in the database, it staggers the imagination. And each one of these 'false' batch numbers is assumed (by the video) to be a 'safe batch' because it only links to one adverse event.
The database is hopelessly 'unclean'. If you (or someone else) has a carefully cleaned version, please let me know. Without removing the 'fake' batch numbers, you cannot run an analysis.
In the search you provided, the 'largest batches' that I saw was one called 'Unknown' with 1,782 cases - and another called 'NONE' with 4,669 cases.
The truth is that (if you look at only the real batches), most have a serious ('toxic') number of links - AND you are still missing all the links that are 'lost' because they are 'spread out' among all the typos. And then, you still can't compare batch to batch unless you know that the batches are all the same size - and the CDC specifically refuses to release that data to the public.
Why are you making your argument about typos when I already said there are obvious typos? Straw-man much?
I specifically trimmed a search to make all of that obvious AND provided a way to verify WITH the manufacturer the validity of the batch # WHICH WAS TO DEAL WITH THE ARGUMENT YOU JUST MADE AGAIN IN DETAIL.
Focusing / highlighting only UNKNOW batches is just intellectually dishonest as that's not what I'm pointing to.
I spend 4 hours a day, 5 days a week in VAERS data. I know it's full of typos and I know how to look at the data and generate very tailored and specific reports.
What we can clearly see though, despite that, is REAL batches with X numbers of issues and REAL batches with XXX of issues. for J&J alone. THAT is what I was pointing to.
We can also put missing series numbers into the J&J page and see they are valid batches and hypothesize those may be saline or something neutral.
Ok, simple question....
How are there '1 in 200' batches that are toxic --- if there are only (about) 300 unique batch numbers?
Another straw-man? Come on dude. Did you miss what I said originally or are you just caught up in your own argument so much that you missed it?
My position "While it's not 10% (currently but they can change that) there are obviously deadly batch's and it's easy to see."
Let me explain myself ---
I am not offerring straw men. I see a genuine danger of having people think "Oh, there's such a really small chance that I can get a bad batch, so why not take it? I can keep my job, etc..."
The message (of 'mostly benign batches') will make no difference to those of us who will never take it, but there are those 'on the fence' who are at risk. A video like this might 'please' us, but it puts others in danger.
Nobody should take this vax.
If you are a numbers guy (like me, a programmer), you know that you can't judge how toxic a batch is unless you know both the numerator and the denominator. 'How many bad events in this batch' divided by 'how big the batch is'.
You might call this another straw man, but I don't see anywhere, in any data set, how we know the size of each batch (how much was manufactured in the batch, and how much was destroyed in the field due to expiration, etc). Pfizer and Moderna aren't telling us, and the CDC (who admits that they know) won't disclose it to the general public.
If Batch1 has 5000 bad events in VAERS, and Batch2 has only 500 - it is not valid to say that Batch2 is 'safer' unless you know the relative sizes of the batches (the denominators). What if Batch1 was 20 times as large as Batch2? Then Batch1 would actually be the safer batch - even with 10 times the events. Simple math.
Now if you know the size of each batch, of each manufacturer, and how much of each batch was actually used (not expired or discarded), please let me know how you know. I would love to have more info.
Incidentally, I made a post over a month ago that described this exact concept (doses are mostly benign/saline, with a 'fine tweaking' to produce desired results) - so I agree that they are doing this. It's just that this data does not prove it.
Post: "If they give SALINE to almost everyone (the first time around), they still get ALL of their EVIL BENEFITS. Here's how..."
https://greatawakening.win/p/13zgXB5572/if-they-give-saline-to-almost-ev/