Dubbed the “Mother of All Revelations*” by conspiracy theorist Liz Gunn, the data leak from Barry Young did reveal something. The leak is not just a gross breach of ethics and privacy, and misleading statistical “analysis”. It is a case study in how misinformation propagandists use common techniques to build, disseminate and cement their narratives.
But before we dive into these techniques, there is another internet law that needs to be explained.
The Bullshit Asymmetry Principle (Brandolini’s Law)
Those that fight against misinformation online often come face to face with this principle.
“The amount of energy needed to refute bullshit is an order of magnitude bigger than that needed to produce it”
This, mixed with the harms caused by accidentally amplifying the misinformation, leads to slower and more careful release of information that refutes the “bullshit.”
In response to refutations of the leak’s analysis and our last article, The leak, confirmation bias and media ecosystems, conspiracy theorists chided us for not responding to every point raised. To us, that would have been a time-consuming waste of energy when this boils down to the simple fact that when death rates are age-standardised we don’t have excess deaths in New Zealand.
Skeet by David Hood: “Since antivaxers are trying to frighten people with “look at all the days of high deaths in the last few years” using their illegally obtained health records, I have done a quick graph from public weekly data to show how misleading they are being. Made at speed but not in haste.”
We’re lucky in New Zealand to have publically available data around vaccination rates, deaths, and population size that can be used to check fallacious claims. While FACT Aotearoa are not experts in data analysis or health sciences, experts say that our death rates over the course of the pandemic are not above the norm.
So why isn’t that simple fact believed?
Credential Laundering
In Gunn’s video, Barry Young claimed he is a scientist. He has a Master of Computer Science degree – not epidemiology, statistics, or other relevant field. He is a database administrator, not a data analyst.
Propagandists like Liz Gunn love to misrepresent the credentials of their sources because that lends false weight to their claims. Many misinformation spreaders take degrees earned in one field and pretend that this qualifies them to speak authoritatively in another.
Gunn framed her video release of this information posing as an interviewer, and Young as an expert educating the audience. This film language lends an air of authenticity that is not backed by the facts.
Cherry Picking and other statistical sins
Young’s analysis of this data set starts with a predetermined conclusion – there are unexplained deaths amongst vaccinated people that must be linked to the Covid-19 vaccine – and works backwards from there.
The majority of the locations that Young identified as having high death rates were mobile units, designed to serve populations with less access to standard vaccination sites. They are often brought to places like rest homes. Thus Young was able to find “clusters” of deaths at a higher number than in the general population. A rigorous analysis of this data would group this data by age (“age stratification”) and pre-existing health status. After all, at any point in time older, sicker people are more likely to die than younger, healthier people.
And all analyses need basic sense checks. Since the vast bulk of New Zealand adults have had COVID vaccines, we would expect to see increased excess mortality in the last two years of the pandemic. But in fact age-stratified death rates are below expected levels.
Young took data collected for one purpose (tracking vaccine delivery) and used it for another (inferring cause of death). This is always problematic and requires a high level of statistical rigour to get right.
Young does not do any of this, and whether this is deliberate or due to ineptitude the result is the same: dramatic numbers that “prove” the conclusion he already made.
Appeal to Emotion
During his interview with Gunn, Young uses highly charged language, at one point breaking out in tears at the thought of all the people who he imagines must be victims of a global “vaccine genocide.”
Young says, “There is so much pain and tears in this that it just, it’s got to end.” As tears well up, “and I’m, I’m gonna prove that it is, it is the vaccine is killing people.”
A rhetorical appeal to emotion serves to bypass the audience’s skepticism and critical thinking. If someone is this emphatic about a claim, and using such highly charged language, the things they say must be true, or at least sincerely believed: Only a very callous or dishonst person would lie about something so serious as thousands of deaths.
Of course, people believe falsehoods all the time. The sincerity or strength of their conviction is not indicative of the truth value of those beliefs.
Prove Me Wrong
Young, and Kirsch make a point of asking people to prove them wrong, but will not listen to corrections when they are presented. This serves two functions: it positions them as honest actors, concerned with pursuing truth at any cost. It also shifts the burden of proof onto the critics, when the side making the outlandish claims in the face of all countervailing evidence should be the ones putting in the work.
Humans tend to lend credence to voices they personally identify with. By performing as maverick truth seekers persecuted for their beliefs, they appeal to people who think of themselves as this type of person.
Of course any attempt to rebut their claims will simply be met with denial. The data is not evidence so much as it is a prop. The MOAR data’s existence and the way it was obtained are more compelling than an honest reading of its contents. The propagandist loses nothing by a blanket denial of anything “the Establishment” says as lies.
Alternatively, some disinformation outlets such as Voices for Freedom have adopted a more measured posture. The data might not prove Barry Young’s claims, they say, but Young is still a whistleblower being persecuted by authorities with something to hide.
These outlets go on to claim that “full” data should be released. But if more vaccine data were presented to the public to refute Young’s claims, this would present additional privacy issues. And legitimate health researchers already work with and in government. Calls to “release the data” only make sense when your starting position is that they can’t be trusted. This is just a more sophisticated “prove me wrong.”
Flooding the Zone
Conspiracists constantly urge their audience to “do their own research.” They do this because they and their fellow propagandists produce so much content that a casual Google search will turn up more examples of misinformation, each piece supporting the others. Thus the odds of finding correct information are greatly diminished.
This phenomenon has memorably been described by alt-right strategist Steve Bannon as “flooding the zone with shit.”
The volume of content becomes in and of itself more “proof” of the truth of the claims: lots of people have questions and concerns. Why shouldn’t people be able to just ask questions? Why are you against free speech and open debate? If so many people are worried, there must be something to worry about. And as Brandolini’s Law suggests, the sheer amount of work required to push back is impossible.
As the saying goes, a lie can run around the world before the truth can pull its boots on. Refuting falsehoods takes more effort than creating them, and when the algorithms that deliver content to users of social media prioritise sensation, shareability and controversy the facts can easily be buried by lies. What you can do is share resources from people that are refuting the bullshit. Let that rise to the top of the pile.
*BONUS: The term MOAR (Mother of all revelations) could be a callback to MOAB (Mother of All Bombs) that has been used extensively in QAnon circles, including by the suspected author of some of the Q “drops,” Ron Watkins, just prior to the January 6 riot at the US capital.
