DEPROGRAMMING DISSECTION PART 1: A Vaccinated Person Will Have Less Severe Symptoms, Won’t Be Hospitalized or Die From Covid
Using Science to Prove their "Science" Isn’t Actually Science
For the record, I must be over the target with this one as it was immediately censored on LinkedIn as “misinformation.”
The claim repeated by Mockingbird Media, Big Tech, Big Pharma, 3-Letter Agencies, and Corrupt Politicians that “a vaccinated person will have less severe symptoms and won’t be hospitalized or die from Covid,” is DEBUNKED.
More specifically, such a claim might be true, or it might be false. Truth is we’ll never know.
Here is the straightforward, unfiltered, highly triggering truth and fact:
Such a claim is statistically impossible to measure.
IMPOSSIBLE.
It cannot be done.
Now that you likely are completely angry, I am going to challenge you to practice what you’ve preached to me and the millions of others you have dismissed as “anti-science” for the last 24 months: TRUST THE SCIENCE
I’d like to challenge you to let go of the phrase Trust the Science and replace it with Trust the Evidence. But, we’ll get to that eventually.
And, if you really believe that we must “trust the science,” then you need to use actual science to analyze the claims that have influenced our behavior and affected society since the inception of the “pandemic.”
I’ll spare you the textbooks on sound research design. However, I want to be clear that you don’t need an advanced degree in statistics or even a PhD like me to learn how you too can poke holes in the “science” you are told to blindly believe.
These are Freshman level introductory concepts, that all should understand to uncover the truth behind these wildly harmful and misleading scientific claims.
LACK OF INTEGRITY IN RESEARCH DESIGN
As a person who spent nearly a decade steeped in the world of research and my dissertation, I was able to develop a strong BS Detector when it comes to statistics and the outlandish claims made by researchers to suit their interests.
Yes, I learned through repeated observation how easy it is to manipulate findings to suit one’s own cause.
And sadly, it happens all the time especially outside an academic setting.
MY APPROACH
Whenever I encounter data and various claims (especially those that are emotionally charged like the one in question here), my BS Detector is activated.
This invariably leads me to go through my own internal process to analyze the validity and reliability of the claim (the statement you are told to believe by the “experts.”)
My first check is to assess that such claims are a result of some sort of formal study. If no such study was conducted, then I immediately discard the claim as not being driven by factual data, but rather an opinion or an untested hypothesis.
That’s when I immediately move into uncovering the agenda and underlying intent.
And in the event, a study was conducted, that’s when I dig deeper in analyzing the validity and reliability of the study.
The validity is the extent we can infer the outcomes, Dependent Variables (DVs) of a study can truly be attributed to the stated Independent Variable (IV).
In the case of the claim I am dissecting, the IV is the vaccine and the DVs are symptoms (their severity), hospitalization and death.
And reliability is how much we can infer such a claim can be generalized to an entire population beyond just those in the study.
Now is tricky part…
When my BS Detector is activated, my automatic response is to question the Parameters and Research Design of the study and the Special Interests of the researchers. I will go through each category for the claim I am dissecting, but at a high-level, I ask myself the following questions:
Parameters
What is the Independent Variable (IV)?
What are the Dependent Variables (DVs)?
What is the hypothesis that was tested?
What are the control variables of the study?
Who was included in the sample (I.e., check for diversity of the sample, how participants were selected, etc.)?
What was the sample size?
Research Design
What was the research design of the study / experiment?
How were the variables measured?
How did the researchers control for all the other variables (extraneous variables) that could affect the validity and reliability of the data?
Special Interests
Who funded the study?
Who conducted the study?
Who benefits from the study’s findings?
Who is harmed by the study’s findings?
By asking these questions, you will be able to quickly uncover if improper research design techniques were deployed and if manipulation of the data to support special interests took place.
If this is the case, then you will also be able to uncover if those making such claims have malintent and are deliberately misleading the People.
My assessment, based on countless observations and hours of my own research is that indeed, the People are being deliberately deceived. And those doing the deceiving, bank on your blind trust and intellectual laziness to not critically think about what they tell you.
Don’t let them get away with this unethical, immoral and possibly even illegal behavior.
This is also, why I am advocating for you to develop the muscle of intellectual fortitude.
LET’S APPLY THESE QUESTIONS TO THE CLAIM: “a vaccinated person will have less severe symptoms and won’t be hospitalized or die from Covid”
PARAMETERS
There are 4 parameters to evaluate here: Variables, Hypothesis, Controls, and Sampling.
1. VARIABLES
The independent variable (IV) in their claim is the vaccine. It’s the variable that would be manipulated to determine the impact on the dependent variables (DV). In their claim there are three specific dependent variables (DVs): 1) symptoms (severity of), 2) hospitalization and 3) death.
2. HYPOTHESIS
Stringing together our IV and DVs would give you a hypothesis that looks something like this: If you are vaccinated, you will be less likely to die and less likely to be hospitalized due to less severe symptoms.
Sounds good so far, right?
Here is where the wheels start to fall off the bus.
3. CONTROLS
In its simplest form, you can look at controls as the variables that could influence the outcomes of a study. For our claim, the non-IV and non-DV variables (extraneous variables) that would need to be controlled include: All comorbidities and demographics including weight, age, gender, underlying health conditions that are unknown, and genetic predisposition
I am sure there are other controls that should be accounted for, but at first glance, these cover the basics.
This takes us to the next parameter before we move into Research Design: Sampling
4. SAMPLING
To produce results that would allow researchers to generalize their claim to an entire population (external validity), it assumes the sample of study participants were representative of the entire population.
Therefore, such a claim that “a vaccinated person will have less severe symptoms and won’t be hospitalized or die from Covid,” implies they have controlled for all the extraneous variables stated above; meaning every comorbidity and demographic was controlled for in the analyses.
This also implies that the study’s sample was large and diverse enough to produce a statistically significant result while also controlling for all comorbidities and demographics.
Let me give you an example: it is becoming clearer with each passing day that obesity is the #1 comorbidity that leads to death from Covid.
And yet, “the experts” have made a generalized claim that “a vaccinated person will have less severe symptoms and won’t be hospitalized or die from Covid,” without mentioning the moderating effect that obesity has on such outcomes. They have willingly and knowingly chosen to mislead the general public. Things that should make you go hmmm… why?
They have pushed a narrative that states that the reason a person has less severe symptoms, won’t be hospitalized or die from Covid is only because of they are vaccinated, rather the due to their co-morbidities (or lack thereof) and other demographics.
And being that there is no data available on sampling that I was able to find in my own research, it lends me to believe this claim was created out of thin air to push a narrative.
Not only are the sampling characteristics unknown, but the sample size that led to their findings is also unknown.
These are two huge red-flags to anybody wishing to take the stance of “following the science” for understanding the claims being circulated in our world by our Mockingbird Media, Big Tech, Big Pharma, 3-Letter Agencies, and Corrupt Politicians.
And, in case you are still skeptical of my debunking, let’s keep going.
This takes us to the impossibility of their research design and where the wheels are completely removed from the bus.
RESEARCH DESIGN
Once a researcher has identified all the above parameters, they move into designing a study that will test their hypothesis by producing results that are not only valid, but also reliable.
I’ll spare you the mumbo jumbo technical speak of statistics and research design. But here is the crux of it all. In order to make a claim that “a vaccinated person will have less severe symptoms and won’t be hospitalized or die from Covid” it would imply the following characteristics of the study’s design.
1. Valid Measurement of Variables
Sure, vaccination, death and hospitalization are easy to measure since the responses are yes or no. But even then, vaccination and hospitalization are still too broad. Which vaccine was administered? How long was the participant in the study hospitalized? What treatment protocols did the hospital follow? So many questions… so few answers.
But where this entire study falls apart is in the severity of symptoms. I have heard many people blindly repeat the claim that an unvaccinated person will have more severe Covid symptoms than a vaccinated person.
Really?
Can you explain how they would know that?
How do you measure severity of symptoms?
You won’t be able to give a coherent educated response to any these questions because these are dependent variables that are impossible to measure.
For example, how do you measure the severity of a stuffy nose?
Even with producing a 5-point scale to measure a stuffy nose (with a 5 being completely clogged and 1 being completely clear), it’s still not a reliable and valid measure.
How do you know my version of a 5 isn’t your version of a 3?
Collecting a person’s assessment on the severity of their stuffy nose is self-reported and thus riddled with bias. And in the real world of ethical research, such a measure would never be allowed.
If I developed a scale like that for my dissertation my committee members would have laughed at me and sent me back to the drawing board. Not to mention, it’d likely bring my entire education into question.
And sure, you might be able to say that an unvaccinated person has a higher fever than an unvaccinated person. But, even then, you have to ask yourself the following:
How were the fever measurements taken in a controlled way?
Who took the measurements?
Did they all use the same reliable thermometer?
Was their fever level measured at consistent intervals upon the acquisition of the virus?
Holes, holes, and more holes.
And here is where the bus completely falls apart to the point it’s no longer a recognizable bus, but rather a heap of useless scrap metal: longitudinal study design.
This is the final blow to the completely false and misleading claim being repeatedly parroted out by those who benefit from your blind belief in their claim.
2. Longitudinal Study Design
Let’s go back to the claim: “a vaccinated person will have less severe symptoms and won’t be hospitalized or die from Covid.”
The only comparison that is a responsible comparison to support such a claim, is to do a cross-comparison analysis of a person’s symptoms of having Covid without vaccination, and then giving the same person Covid again to re-evaluate their symptoms after they’ve been vaccinated.
This would have to be repeated for a very large sample size. And such a large sample is the only way the researchers would be able to state with confidence that the effect size of the findings are not only statistically significant but also reliable.
The only way to be able to truly assess such a claim is through a single-subject design that follows the same participants in the study over time.
It would require the participants of the study are assessed at two specific points in time:
Point 1: Unvaccinated participants have Covid and the DVs are measured in a controlled way.
Again, hospitalization and death are easy to measure as the responses are yes or no. But, even in the case of death, you cannot possibly attribute the death to vaccination status alone because it is impossible to know whether they would have died even with vaccination. Claims of “might of” are not based in science. They are merely hypotheses that cannot be measured nor proven or disproven
Don’t fall into the “might of” trap.
Secondly, the challenge around the measurement of symptom severity variables is questionable.
Point 2: Participants are then vaccinated with the same vaccine, re-infected with the same original strain of Covid and the DVs are measured in a controlled way as they were in Point 1.
Ok, I have to ask.
Do you see where I going with this?
The current line of thinking is that the instances of re-infection are very rare. And yet, the only way of truly measuring their claim, is it’d require re-infection.
How could they possibly have a large enough sample size to measure this?
How can they control for the type of variant?
They can’t. It’s not possible.
In conclusion, from a scientific perspective, their claim that “a vaccinated person will have less severe symptoms and won’t be hospitalized or die from Covid,” is impossible to measure.
It might be true. It might not be true.
But in the world of science, stating that something “might” happen is not science. It’s a guess. And the more they push their guesses to support their agenda, the more inclined we should all be to recognize this as propaganda.
As a result, their claim that “a vaccinated person will have less severe symptoms and won’t be hospitalized or die from Covid,” is completely DEBUNKED.
It’s not that the wheels of the study’s bus just fell off, but rather the bus is just a giant heap of useless metal. There isn’t even a bus. This isn’t even a thing worth considering.
So that leads me to my third line of questioning once my BS Detector is activated: Special Interests.
SPECIAL INTERESTS
It is now crystal clear that such a claim is not founded in science. As a result, you have to dig into why such a claim is being made.
You have to ask yourself:
Who is behind the claim?
Who benefits from your belief in their claim?
Who is harmed by your belief in their claim?
Once you’ve gone through the questions of the BS Detector and you too see clearly that this claim doesn’t exactly pass the smell test, you must dig in further.
You can apply this same BS Detector tactic to every claim that is made by those who are wanting you to blindly trust their “science.” I encourage you to apply this across the board. You’ll be surprised how quickly you’ll see things differently.
You must take an active interest in developing your intellectual fortitude to see through the agenda and break the belief systems that have clouded your judgement.
COMING SOON
This leads me into Part 2 of this Deprogramming Dissection where I will go through my 4-part approach to analyze the claim that “a vaccinated person will have less severe symptoms and won’t be hospitalized or die from Covid.”
In my next post, I will do a deep dive into the Message, specifically, not just what is said, but what is meant by such a claim.
I’ll go through what you are expected to Think, Feel, Say, and Do as a result of blindly believing such a claim.
I’ll review the Psychological Manipulation Tactics deployed to get people to believe their claim.
I’ll dig into the possible reasons for Why such a claim has been made and the bigger picture agenda it supports.
Lastly, I will dig into a previous untapped topic around Psychological Operations, commonly called Psyops and how it ties into this subject.
In summary, I want to remind you of my purpose.
My purpose is to help deprogram ourselves from the beliefs that have been infused in our minds that keep us weak, divided and not truly thinking for ourselves.
I welcome you to join me on this journey by subscribing to my America Rebooted Substack and sharing these posts with those who need help in challenging the beliefs of others or those who need to have their own beliefs challenged.
Together we can be better.