This will be a quick review and summary of what I learned from the first three pieces under the "Propaganda Files" lens. In order, these were Neil Baron's "Legal Culpability" piece in Newsweek, the Dean Obeidallah "Aaron Rodgers" piece for CNN, and the Father Martin "How Do You Respond?" essay for the New York Times.
All were opinion pieces vetted by Newsweek, CNN, and the New York Times, respectively. As such, fact-checking and editorial oversight were the responsibility of these three media titans, while direct responsibility for the pieces could be laid at the authors' feet.
I'm an analytic plodder. The worst writer employed by any of these three entities is a far better writer than me. Any editor in their employ is a far better editor than me. Frankly, that is a large part of what bothers me. The misdirection and spin, sometimes edging into the realm of misinformation, should have been evident to any editor reviewing these articles.
What We've Learned
I'll be returning to Obeidallah's Aaron Rodgers piece for "Part Two" later this week to connect some big dots. For now, what we've seen and, more importantly, not seen from these three published opinions include the following:
Missing
1) No mention of viral loads at all. Viral loads of infected vaccinated compared to viral loads of infected unvaccinated is important.
2) No mention, ever, of estimated R-values, which would compare vaccinated transmissibility with the transmissibility of the unvaccinated.
3) Very little mention of the Biden administration's Covid death toll, which undercuts the vaccine effectiveness narrative.
4) No discussion of vaccine efficacy for Delta and Omicron, and especially no comparison of vaccine efficacy for the original strain versus the new variants. No comparisons of Covid vaccines' efficacy to previous normal flu vaccines' efficacy.
I suppose that if you're going to pitch vaccination as a cure-all, these topics need to remain unstated and undiscussed.
Emphases
What gets emphasized are very specific statistics. These stats are presented with little discussion, as if the stats themselves provide a self-evident story.
1) Despite no viral load or R-value discussions, the stats that get repeated are the hospitalization and death rates for unvaccinated versus vaccinated. The tone and fear factor are reminiscent of the old "This is your brain on drugs" advertisements. The death rates for unvaccinated are much, much higher, and people need to be aware of them. However, all of the summaries I have read addressing the increased risk for the unvaccinated fail to frame the death rates in any kind of overall context.
For example, as the U.S. approaches a million Covid deaths, if we assume an adult population of roughly 260 million, the actual chances of dying of Covid have been less than .4%. That means, of course, that you have had more than a 99.6% chance of NOT dying of Covid. I say this not to make any particular point but to provide context, regardless of where the context takes anyone's decision-making.
In a similar vein, the case fatality ratio in the United States has been 1.2%, and this is a recent (thus presumably accurate) number from Johns Hopkins. This 1.2% represents a blend of vaccinated and unvaccinated dying from Covid. Obviously, being vaccinated now reduces this by a large factor, perhaps knocking down fatality likelihood to under a tenth of a percent. The question for individuals is whether the difference between under a tenth of a percent chance of dying and, say, a two percent chance of dying (assuming, as Dr. Fauci has said, that everyone will eventually be infected) is something that should be legislated. If you're not legislating tobacco products or morbid obesity with regard to mortality percentages, should the government be legislating vaccines for Covid? Why are some mortality risks treated differently than others?
If you're giving people statistics to make decisions, give them all of the statistics. The job of the federal government and national media is not to cherry pick what is presented for "the public good." The job is to present the data, unvarnished and unspun, to the public. If people are innumerate or simply distrustful of government, spinning the narrative and omitting stats is still not the job of government or media.
2) Another emphasis features (perhaps dated) stats, varying quite a bit, that the unvaccinated are 4.5 times to 10 times more likely to be infected than the unvaccinated. These are interesting statistics if the modest vaccine efficacy versus new variants is to be believed. It's hard to reconcile the (usually unstated) modest vaccine efficacy with the high rate of infection among the unvaccinated. What's strongly suggested by the stats (but not the authors we've examined) is that the correlation must be largely due to behavioral differences or varying laws. If the unvaccinated are clustered in states with minimal masking, social distancing, and lockdown rules, then of course the unvaccinated are more likely to be infected, and by a wide margin. The difference can likely be due more to behavioral differences and location laws than to actual vaccination efficacy in preventing infection. Need it be said? Correlation does not equal causation. In this case, because the current vaccines do have some ability to prevent infection, there is a cause-effect between vaccination and not getting infected in the short term, but nowhere near the disparity being presented. And with Dr. Fauci stating on January 12 that he expects almost every American to get Covid, the role of vaccines in preventing infection can be viewed as quite limited in the long term.
What's Implied
It's what's implied in these essays, and implied by much American institutional Covid public relations, that is the most bothersome, manipulative element of these influence communications. Writers and American institutions are relying on implication to convince people how to behave because the stats themselves, honestly presented in context, aren't going to get the job done.
1) If a writer states infection rates for vaccinated as compared to unvaccinated, and then doesn't even mention correlational variables, he is implying that direct cause-and-effect is all that is in play. Why skip the possible correlational variables? It's misleading.
2) If a writer bundles not masking and being unvaccinated together so as to be able to state that "they" are "dangerous to others," that is purposeful. It is misleading because with these current vaccines and variants, the unvaccinated, once infected, are no more superspreaders than the vaccinated. Bundling "not masking" and "being unvaccinated" as a "they" is misleading. The "they" in this case are two completely different things. Labeling them as "they" is propaganda.
3) If a writer bundles the argument that "unvaccinated are not superspreaders" with the separate argument "not a pandemic of the nonvaccinated" so as to employ a specific study as a debunking tool, that is manipulative. When the study in question does not actually debunk the "not superspreader" argument, but the author doesn't point that out, he is being purposefully misleading. It is propaganda.
None of these writing decisions are accidental. They are planned and quite carefully executed, a kind of Don King "trickeration" with the goal of making public some statistics, masking others, and having particular effects on audiences.
Purposeful Propaganda
When phrases are bundled or unbundled in service of specific hoped-for effects, that is purposeful writing. It's writing that emphasizes the writer's end (influencing the audience) over what should be the writer's means (using objective facts to share the truth as the writer knows it).
When writers employ these strategies with a scripted end in mind, this is propaganda. When editors see these obvious manipulations and allow them in service of a smooth, homogeneous narrative, this is also propaganda.
We are awash in it. It's occurring at the highest levels of American writing and at the most experienced, polished levels of editing.
Bob Dietz
February 6, 2022
