UVC: Michael Alexander: Aligning Causation in Law and Science

The inaugural Understanding Vaccine Causation Conference, convened by World Council for Health Steering Committee Member, Shabnam Palesa Mohamed, took place on Feb. 5, 2022. The WCH Law and Activism Committee brought together legal practitioners, doctors, scientists, and jab victim data and advocacy groups to explore a key question: How are jab adverse events proved?

Lawyer Michael Alexander joined us to provide a perspective on causation in law and science. 

This clip from the Understanding Vaccine Causation Conference can also be found on Rumble and Odysee.

Transcript

Michael Alexander – UVC

[00:00:00]

Shabnam Palesa Mohamed: We’re going to begin with Michael Alexander and I’ll ask him to first introduce himself and tell us why meeting this conference is pivotal in 60 seconds, Michael.

Michael Alexander: Hi everybody, I’m Michael Alexander. I’m speaking to you from Toronto. I’m a constitutional lawyer trained in Canada and the US. I also work in Canada as a professional public speaker and writer. I think this is an extremely important conference, to use Shabnam’s word pivotal, because in the courts in Canada, and to some extent in the US, we are losing the battle of experts versus experts and studies versus studies.

We have to look at the way to present scientific evidence to the courts and in a new way, if we hope to succeed in the current environment where most institutions are stacked against us. And so this conference hopefully will be the first step in unlocking the solution to that problem. [00:01:00]

Shabnam Palesa Mohamed: Excellent and of course, Michael Alexander, we know that adverse events are being experienced by people. The question is how do we prove it? And that’s what this conference is all about. Now, your topic centers around aligning law and science on the topic of causation. The mic is yours.

Michael Alexander: Okay. Thank you, Shabnam. I will go to share screen here and we’d like to lead you through a relatively short PowerPoint presentation to get at the core issues. Are we good with everybody? Okay. Am I sharing the screen? Very good. Okay.

So the purpose of my presentation is to just establish the outlines of the problem, to raise issues. This template I’m about to present may change over time as we move from causation conference one to two to three. So this is truly a primer and it’s open to suggestions, comments, and criticism as we move forward.

So I’ve provided this to our participants today [00:02:00] ahead of the scheduled talks, just to give them an idea of some issues they might highlight in the course of conveying their particular message today. So, the problem is how do we take, scientific causation and align it, with legal causation, in order to persuade the courts that we have a case to make.

And so, as I said previously, the problem that we’re facing is we are faced in the courts either by the battle of the experts or the battle of the studies. The government or Big Pharma presents 50 studies, the other side presents 50 studies. By default, the decision goes to government, same thing with experts. We present five experts, they present five experts, default-it goes to government.

So we want to examine how to, in the current climate, overcome this problem, which normally would not be a problem. And the general [00:03:00] problem, of course, is how can we translate equations and numbers, graphs into language of law.

And that problem is, I would say, more with law than it is with science. And I’ve, posted this quotation from the great, late Lord Denning of the House of Lords who was referring to illegal tests, referred to as the balance of probabilities. And in describing that legal test, he said:

“The balance of probabilities, seen as more probably than not, which must be contrasted with the but-for test, and the criminal standard, is actually a sliding scale that varies according to the intention of the party, the gravity of the consequence, and the circumstances overall, which is the only way to bring true clarity to the evidentiary standard.”

Okay. So, that’s not exactly the quintessence of clarity and we will discuss going forward why these problems exist in relation [00:04:00] to the basic evidentiary standards which establish causation in law.

So we have three basic tests in law for determining whether, say in the case that you have a plaintiff so we need a defendant for damages, how much evidence must the plaintiff produce in order to prove that he or she, or it deserves to succeed and the defendant does not. Most cases in private law, which would include, contract and tort, which is the law relating to damages, go off on the balance of probabilities. And that means that more probably than not, the defendant is liable.

So what degree of certainty is more probably than not? Can you give it a, can you quantify it? And, according to, the greatest Supreme Court Justice in Canada on the subject of evidence of Johnson, Pinker 51% is sufficient to meet the balance of [00:05:00] probabilities. So 1% more than the other side in terms of evidence, the weight of the evidence, you can succeed. I think that’s rather insane, but we can, we can address that later.

Now we have the preponderance of probabilities. This is the standard that’s used in constitutional adjudication in Canada. So for instance, the government brings forward legislation that will infringe somebody’s individual rights under our charter of rights and freedoms, the question becomes, can the government justify that infringement? And, the Supreme Court test for that is the government must establish that the good accruing from the legislation, is greater than the good that would accrue from actually respecting individual rights. And that has to be done with 75% certainty.

Then of course we have the criminal standard, which we are all familiar with, where we have 90% certainty. The evidence overwhelmingly points to one side. Now, aside from the 51% figure, which I would say is not a figure on which, judges and jurists,[00:06:00] have agreed, the 75% for the ponderance is somewhat arbitrary on my part. I’m trying to just find the midway between the balanced and beyond a reasonable doubt. Beyond a reasonable doubt might be 90%, might be it’s 95. So, these figures, the latter two figures, are somewhat arbitrary, but I think it gives us some idea, from the standpoint of numbers, where we are in relation to these tests.

Now, as to causation in science, I’m going to speak from the standpoint of the randomized control trial, the RCT. And, within every RCT, as our scientists and doctors will know, there is something called a P value, and that’s assigned to the study based on the application of a statistical formula to the data.

I can’t say I fully understand that formula yet, but we are working on it, at this end. But I think what I do understand is that the P value must be less than 0.05 in order to establish [00:07:00] that the experiment is, the result of the experiment, is certain to a 95% degree within the parameters of that particular experiment, which the parameters may change from experiment to experiment. But less than point, excuse me, greater than 0.05, then we have a 95% certainty that the result is due to chance.

Now, the point I want to make about this is this P value is internal to this study. So we’re looking at the level of causation within the study itself, we’re not talking about comparing one study to another. And when we do that, we are into a different language when it comes to causation. We’re talking about the reliability of the experiment, vis-a-vis other experiments. And in an RCT, there are six criteria that we normally would want to meet and maximize in order to legitimize the result.

There must be a [00:08:00] large end value, a large number of participants.

There must be randomization of conditions. This is normally done through a lottery, so that whoever ends up in placebo and in the other group will be done on a strictly random basis, no bias in the distribution.

The study of course must be double-blinded.

It’s carried out for more than six months.

There is a representative sample.

And dependent variables are in a real-world context. And by that, we mean, for instance, if you’re testing a vaccine for a possible result, in terms of blood clotting, then the dependent variable will be D-dimer tests, which will establish at the end of the experiment, or the trial I should say, whether clotting has occurred or not.

Now the reliability of the experiment then can be seen on a line going from zero to six, becoming more reliable, the extent to which the experiment meets all [00:09:00] six criteria.

There’s the judge from Rick and Morty, which is a cartoon about a nihilist and a loner, not exactly something to cheer you up on a Saturday morning. But anyway, I like the judge. He is speaking to us here about the balance of probabilities in relation to the six elements of the randomized controlled study.

Now, if we met three of the RCT criteria, that might equate, and this is a very rough approximation, that might equate to the balance of probability standard. In other words, 51%. So if you met three criteria, perhaps your study could push you over the 50% mark, the 51%, and meet the balance of probability test for a finding in your favor, assuming you’re the plaintiff suing the defendant.

Then we have the preponderance of probabilities. We know we’ve assigned 75% certainty to that level of causation. And there, if we have [00:10:00] four to five of the RCT criteria, that would perhaps give us a result in the reliability aspect of 75%, thus meeting the test. And then if we meet all six criteria, then we’re looking at a truly reliable result and that would match up with the criminal standard of beyond a reasonable doubt.

What we can say as a result of looking at the connection between causation in science and causation at law, that a perfect RCT, if there is such a thing, would give us at least a reliability figure of 90%. And that, of course, captures all levels of causation. 51%, 75%, and then the criminal standard at 90%. The imperfect RCT, at less than 90% reliability, may or may not capture the latter two standards, which is to say the preponderance at 75% and beyond a reasonable doubt at 90%.[00:11:00]

So, that’s just a brief introduction to the randomized controlled trial and the legal standards of causation.

There is an entirely different way to approach this issue of bringing science into the courtroom. And this was revealed to me through the presentations made by Deanna McCloud and David Wiseman at the World Council for Health several weeks ago.

Deanna of course presented an analysis of Pfizer’s safety and efficacy study from February of 2021. And she demonstrated that if you re-crunch the numbers from within and gathered together information that was in Pfizer’s supplementary work, which unfortunately was not included in the main study, what you’ll discover is that the basic thesis of the study is false. The basic thesis being that it’s better for you to take the vaccine than not, more good accrues to the vaccine than not. And so her presentation totally refutes that. [00:12:00]

And David Wiseman did something similar in his presentation where he imploded, or exploded, claims made by the CDC, the FDA and Big Pharma based on an analysis of their own evidence.

And what this does is it gives us the opportunity to impeach the witness. Now, this is a very basic concept in law. If you have a star witness, let’s say the plaintiff has a star witness without which the case cannot proceed. And you are the defendant. You can put that witness on the stand for cross examination. If based on the cross-examination you find that the witness is in contradiction, based on prior statements and you can prove that during the cross, the witness is eliminated and the case will fall apart.

And so we have here Moderna and Pfizer as star witnesses based on their own statements and studies.

So if we were to take the Pfizer study for instance, and bring it before a court, we [00:13:00] need do nothing else. This is the study that has been relied upon or should be relied upon, Pfizer is its own star witness. If we blow that apart from within, in a very careful, extremely well-communicated way, we should be able to succeed on that alone, forget about the 50 studies and the 50 experts. This is one way to go directly to the heart of the matter.

I’m calling that the third way and I’m examining how we might apply that in litigation that we have ongoing in Canada as a solution to the existing problems of trying to reach the courts.

So there we have it. We have two avenues for pursuing the alignment, or a way of connecting, legal causation and medical causation. We can go the RCT route, or we can go the impeaching the witness route. And either way, I think we can achieve more promising [00:14:00] results as we move forward and, sorry to be narcissistic, there I am at the Supreme Court of Canada, and I’m hoping to be there someday making arguments like this, if they withstand scrutiny.

So I thank you very much for your time and hope that this will put us in a position to address some key issues this afternoon.

Shabnam Palesa Mohamed: Thank you, Michael Alexander would that brilliant, brilliant presentation, certainly opening up our minds to how to address causation and bringing together law and science closer together in what will become necessary, uh, during not only the course of this year, but in the years ahead.


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