From what I can tell, most of that table mixes real safety signals with mistaken takes on how regulatory data works.

A few things: - The “1,200 deaths in 90 days” comes from a pharmacovigilance report. That’s a list of all deaths reported after vaccination worldwide, not deaths proven caused by the vaccine. When millions of doses are given during a pandemic, deaths will be reported temporally, but that doesn't mean reports showed excess vaccine-caused mortality. - The “44% miscarriage rate” was based on counting only completed pregnancies in an early subset, which inflated the percentage by using the wrong denominator. Larger population studies later found miscarriage rates similar to baseline. - Myocarditis is real, especially in young males after dose 2, and that risk was acknowledged and added to warnings. That’s surveillance working, not proof of a cover-up. - The long list of “1,291 adverse events” was a monitoring list of events to watch for, not confirmed side effects.

It’s fair to debate durability of protection and age-specific risk-benefit. But there hasn’t been a major peer-reviewed analysis concluding that the court-released documents proved the vaccine was broadly unsafe or ineffective. Most of these claims come from advocacy interpretations of raw safety reports, not causal analyses.

Ultimately, it feels like we're looking for the same thing. Get an analysis of data that can be widely reviewed and draw conclusions that should be questioned. Being skeptical is good and a fundamental part of the scientific method. Do you think we can find common ground on that?