The Evolution of Cybernetics

The Evolution of Cyberneticshttps://sifter.org/~simon/journalA Journal by Simon FunkThu, 14 May 2026 11:08:25 GMTPyRSS2Gen-1.1.0http://blogs.law.harvard.edu/tech/rssDerationalizing, Part 1: Question the Obvioushttps://sifter.org/~simon/journal/20220125.1.h.htmlDerationalizing, Part 1: Question the Obvioushttps://sifter.org/~simon/journal/20220125.1.h.htmlTue, 25 Jan 2022 00:00:00 GMT<blockquote style="margin: 0 auto; max-width: 800px;" morss_own_score="2.951871657754011" morss_score="107.15187165775401"> <center> [<a href="https://sifter.org/~simon/journal/20211119.h.html"><<</a> | <a href="https://sifter.org/~simon/journal/20211119.h.html">Prev</a> | <a href="https://sifter.org/~simon/journal/index.html">Index</a> | <a href="https://sifter.org/~simon/journal/20220125.2.h.html">Next</a> | <a href="https://sifter.org/~simon/journal/20220125.2.h.html">>></a>] <h2>Tuesday, January 25, 2022</h2> <h4>Derationalizing, Part 1: Question the Obvious</h4> </center> My reply to this question from an acquaintance: <blockquote> As a young person, it's difficult to know about every topic that is discussed. What do you do as a young skeptic who holds few opinions? Do you become the Socrates in every discussion/argument while offering very few of your own opinions? </blockquote> <blockquote> How can you ever be ready to say "I believe x" if there's so much room to say "I don't know"? It's unlikely that you'll go through every source about any subject, so at what point should you be confident enough to form an opinion? </blockquote> <blockquote> What happens when you don't know what you don't know? </blockquote> <blockquote> [..] </blockquote> <blockquote> I guess the question here is: which strategy are people most receptive to in an argument? Which will help you learn the most? Is there a combination of these that allows for maximum learning efficiency? </blockquote> Imo there is only one answer to any of these and it's the answer to all of these, and you touched on it up top w/Socrates: Make your only objective: to understand why people believe what they do. (And in particular, not to try to convince anyone of anything before you've done that.) Once you achieve that (which you may or may not ever with any given person...), depending on what the answer is there are usually one of three options: 1) You realize they are right, 2) You use what you've learned about why they believe what they do to guide them to a new belief, 3) You realize the reasons they believe things are entirely irrational and, chances are, you're too honest to do what it would take to change their minds. Generally speaking you will find that honest people will self-correct before you get to the end. That is, if you just keep asking them about whatever bit isn't making sense to you, and assuming their answers don't clear it up for you and change your mind, they will crash into their own inconsistencies or unsupported premises in their effort to answer your questions, and will say "Oh, now that you mention it.... maybe I had that part wrong." So in practice, it's rare you ever get a chance to exercise (2) because those people self-correct before you get there. There are like 10 such people on the planet. I know 5 of them. Most of the time you'll eventually end up at (3), which is a hard end to reach because you'll rightly be very reluctant to accept just how irrational people are, particularly the academics who've been trained to present as rational. Sadly (1) will be more rare than you hope, too, for the same reason. To give you a head start on understanding why (most) people believe what they do, here's my distillation after half a century of studying how people think: 1) No matter how many reasons most people have for what they believe, the reality is belief is a feeling and all the reasoning is post-rationalization. Deep down, certain things are "obvious" to them, and this feeling of obviousness is the stopping condition that keeps them from ruminating endlessly into the most minute details or remote possibilities. In other words, the feeling of truth or obviousness is a key and necessary feature of cognition, and without it we would be unable to look up from our navel in time to eat. But the problem is, very few people recognize it for what it is--a subconsciously acquired emotional response (as opposed to a necessarily sound inference)--and they blindly heed its impulse, which is to stop thinking about the "obvious" thing in question. So, most people most of the time are not in a learning mode at all, they are post-rationalizing what they already feel. 2) What most people feel is true is programmed into them by their tribe--in this age via their chosen media and social networks. People in media know this, and use it (the caveat on (3) above does not apply to them). But it doesn't happen the way you think: It's not about presenting evidence and making rational arguments, because as I said that's not how people actually think. It's about adopting the desired "truth" as a presupposition and then portraying everything using that light. So "the terrorists stormed the church and held fifty people captive for three days" brings our conscious attention to the described action, but hidden from scrutiny is the choice of "terrorists" vs. "revolutionaries", which carries with it a great deal of emotional implications which directly program the readers. Even if the depictions don't seem super credible, repetition will make them into reality, because every time someone is exposed to a phrase or story like that, they picture it in their mind's eye, and their cortex integrates that experience as if it had been seen in the real world. In other words, if you can get people to listen to your stories for enough minutes of the day, they will integrate the presuppositions (the background reality implied by your stories) of those stories as their model of the real world. Doesn't matter if they believe they are reading fact or fiction. And looping back, once those presuppositions are programmed in, they define what is "obvious", and in turn what people will no longer think about. Again, most people who make it to positions of serious power understand all of this very well, and the world is run via these strings. The people you'll encounter will mostly be on the wrong end of those strings. So, you can try asking people why they believe what they do, but mostly their answers won't make sense (they will form a logical chain, but that chain will be just one of many logical chains and not necessarily the most likely one by any obvious metric), so there's a fair chance you won't come to understand why they believe what they do by asking them. Instead, find out what media they consume, and then go pay attention to how that media is crafted, and you will probably have your answer. Which is why, for case (3), there's usually nothing you can do about it. Just beware, once you pay attention to media at this level enough to see what I'm talking about, you'll have learned to perceive it in the same way you perceive a chair when you walk into a room, without having to analyze the legs and seat and logically deduce that there's a chair. I.e., you won't be able to un-see it, and then you'll spend the rest of your life living in Clown World where you can't believe you're surrounded by people who blindly swallow/follow this crap. <a href="https://www.youtube.com/watch?v=g4XiKChyK7A">They Live</a> (But you won't be able to take these glasses off.) All that said, to end on a more productive note and to tie in what I said at the start: Imo the best approach to take is to just ask questions. If you're actively debating someone, focus on the most important one or very few--people will throw a lot of chaff to distract you away from their inconsistencies. Just ignore the chaff (hard to do!) and laser focus on the important question--whatever most doesn't make sense to you about their stance. I have actually "won" a few debates this way, the sorts of debates that are not normally ever won by either side, which is as much a credit to them as to my approach because most will break down into full cognitive dissonance first: <blockquote> "I have learned that, for most people, if you inspire within them a conflict between what they feel is right and what they know is right, well, fireworks or waterworks are usually the result." -Rik Ling </blockquote> Equally important is to be that person who is willing to answer the important questions straight, and to admit error when you can't. You might just make it 11. Oh, and also actionable: To whatever degree all of the above is accurate and representative of humans in general including you and me, the primary control you have over what you believe, and the quality and accuracy of what you believe, is the media you expose yourself to. This is a very tricky decision to make well, because: <blockquote> "One thing I've learned in the half-century of living and learning is that if society establishes an organized process, cheats will enter, and game the system." -- <a href="https://jameslyonsweiler.com/2021/07/20/ghouling-targeted-study-retraction-is-biasing-scientific-literature/">James Lyons-Weiler</a> </blockquote> The most rigorous and seemingly trustworthy institutions are also the most insidiously corrupt. Independent bloggers and journalists are probably your best bet right now. Pick a wide range of ones who think well, and rely on their public position as aggregators to pull in what matters. Avoid the mainstream media like the NPC blue pill it is. (Once you start paying attention to slant, you won't be able to stomach mainstream media anyway. See Clown World.) Lastly... to make the implied explicit: You can do a lot to clean up your own belief system by simply being willing to entertain any challenge to something you consider "obvious" (at least long enough to make sure it's not a new angle you haven't honestly considered before; and even if you have, it's worth re-visiting if it comes from someone you consider sane). I.e., there's probably no way to avoid the emotional aspect of belief (and the subconscious absorption of presuppositions from media), but you can largely work around/patch it simply by understanding that that's how the (your) mind works. Which is a really long-winded way of saying: don't be over-confident about anything. <center>[<a href="https://sifter.org/~simon/journal/20211119.h.html"><<</a> | <a href="https://sifter.org/~simon/journal/20211119.h.html">Prev</a> | <a href="https://sifter.org/~simon/journal/index.html">Index</a> | <a href="https://sifter.org/~simon/journal/20220125.2.h.html">Next</a> | <a href="https://sifter.org/~simon/journal/20220125.2.h.html">>></a>] </center> </blockquote> Derationalizing, Part 2: Check your Blind Spothttps://sifter.org/~simon/journal/20220125.2.h.htmlDerationalizing, Part 2: Check your Blind Spothttps://sifter.org/~simon/journal/20220125.2.h.htmlTue, 25 Jan 2022 00:00:00 GMT<blockquote style="margin: 0 auto; max-width: 800px;" morss_own_score="2.9470588235294115" morss_score="44.94705882352941"> <center> [<a href="https://sifter.org/~simon/journal/20220125.1.h.html"><<</a> | <a href="https://sifter.org/~simon/journal/20220125.1.h.html">Prev</a> | <a href="https://sifter.org/~simon/journal/index.html">Index</a> | <a href="https://sifter.org/~simon/journal/20220204.html">Next</a> | <a href="https://sifter.org/~simon/journal/20230521.h.html">>></a>] <h2>Tuesday, January 25, 2022</h2> <h4>Derationalizing, Part 2: Check your Blind Spot</h4> </center> [Addendum to <a href="https://sifter.org/~simon/journal/20220125.1.h.html">last time</a>] I glossed over one key point that helps make more sense of the rest: Recall my example of walking into a room and seeing (perceiving) the chair in it. How do we do that, and what does "perception" mean exactly? The answer (my opinion, but one I'm very confident in) is that perception is the act of matching some inputs (the image hitting your retinas) with your existing model of the world. And by "model" here I mean (something equivalent to) a generative model--i.e. something that could "imagine" scenes from the world. I.e., you don't walk into a room and see a chair in a strictly bottom-up (concrete-to-abstract) way. Rather, you walk into a room expecting (being able to imagine, top-down) various things that might be there, and expecting what they might look like, and in effect you cull this set of possible things down to the ones that match the inputs you get. Why this matters is: People are utterly incapable of perceiving anything outside of their existing model. (People can update their models with time but this is slow and.. rare.) It's a little harder to illustrate for something like a chair (because we all have very detailed models of 3d objects in general) although it's more applicable there than one might guess, but probably the most accessible example is if you've ever tried to learn a new language with a different phonetic base than you are used to: You will initially perceive the language in terms of your existing base, and in general won't be able to properly group and differentiate some of the sounds. And by that I mean, someone native to the language might be able to say two sounds that are clearly different to them, and to you they will sound qualitatively the same. With practice those sounds begin to emerge as distinct, and eventually you will (effortlessly) hear them as two different things (as your model slowly updates to include them). Now, someone with a more elaborate low-level model of phonetics might be able to differentiate sounds from a new language immediately -- so it's not strictly true that you need experience with a particular thing to be able to perceive it; rather, it just depends on where your particular model has what level of detail. For someone who grew up in a single accent of a single language, there is no need to have a finer-grained model than the phonemes of that dialect, and so the brain generally won't waste resources on that, and they will be the most "blind" to the nuances of a novel language. Anyway, where this becomes more relevant is with more abstract things. Consider all the nuance of life, social interaction, politics, and so on, which are "invisible" to children, and which you learn to see more and more of in better and better detail as you get older. My point here is to reflect on what you could see a few years back and compare to what you can see now; there must be some examples of things you just naturally perceive now which you remember being completely unaware of a few years back? If you can hone in on that contrast, then realize the same applies between any two people -- there are ways that the people around you are or will be like children compared to you in terms of what you can easily see that is entirely invisible to them. I'm being long-winded on this, but it's super important, because we naturally tend to imagine that everybody sees the same world that we do. But the reality is they don't--things can be plain as day to you (not even a judgment call, just what seems to be a direct perception) and totally invisible to them, and vice versa. If you don't account for this, it's a lot harder to understand other people's perspectives. Once you do account for this, you can generally learn the limits of other people's models--typically by tribe since people's models are, as I mentioned, mostly absorbed from the presuppositions of their social/media context. And you can be on the lookout for anywhere that others seem to be able to see something you don't, and can proactively learn to see that thing. The example I gave before was media slant. I have now witnessed multiple people transition from being blind to it to seeing it. It is the closest real-world analogy to the "red pill" Matrix moment. In general, this only happens when they have been so personally familiar with something that they were forced to see the media version vs. the real version, especially as both evolved in real time. This serves as a training example, via the correlates between the nuances of the media and the particular ways and places they are deviating from or misrepresenting reality. For some reason, some people go through this but never develop that model. That's called Gell-Mann Amnesia. But people whose brains haven't calcified, or whatever is the issue, update their models and gain a new and permanent insight. The same situation with media exists with academia and science, unfortunately. (I've been collecting the patterns of bias and fraud for years; thinking of assembling them into a book some day.) And the same principle applies here: Most people simply can't see it, because they've not spent the time looking closely enough at it to build a model of how it works; and without that model, they simply can't see it even when it's right in front of them. Again, I've seen people transition (red pill) and almost always it is due to some direct personal experience where they knew something so well that they could not escape seeing the contrast between what was true and what was broadly and universally accepted, supported, and defended to the death by "science". (Until years later, when science finally comes around, and declares that those who thought otherwise before were right for the wrong reasons.) So, bottom line, don't assume the person you're talking to sees the same thing even if you're both looking right at the same thing. Study their tribe and how it models the world, and you'll eventually figure out what they will and won't be able to see; and once you know that, people make a lot more sense... (And you still won't be able to teach them anything, alas.) <center>[<a href="https://sifter.org/~simon/journal/20220125.1.h.html"><<</a> | <a href="https://sifter.org/~simon/journal/20220125.1.h.html">Prev</a> | <a href="https://sifter.org/~simon/journal/index.html">Index</a> | <a href="https://sifter.org/~simon/journal/20220204.html">Next</a> | <a href="https://sifter.org/~simon/journal/20230521.h.html">>></a>] </center> </blockquote> Covid Update: Vitamin Dhttps://sifter.org/~simon/journal/20220204.htmlCovid Update: Vitamin Dhttps://sifter.org/~simon/journal/20220204.htmlFri, 04 Feb 2022 00:00:00 GMT<blockquote style="margin: 0 auto; max-width: 800px;" morss_own_score="2.4871794871794872" morss_score="37.72792022792023"> <center> [<a href="https://sifter.org/~simon/journal/20220125.2.h.html"><<</a> | <a href="https://sifter.org/~simon/journal/20220125.2.h.html">Prev</a> | <a href="https://sifter.org/~simon/journal/index.html">Index</a> | <a href="https://sifter.org/~simon/journal/20220707.html">Next</a> | <a href="https://sifter.org/~simon/journal/20230521.h.html">>></a>] <h2>Friday, February 04, 2022</h2> <h4>Covid Update: Vitamin D</h4> </center> I've been mentioning vitamin D as a likely severe-Covid preventative with <a href="https://sifter.org/~simon/journal/20200904.html">increasing confidence</a> since <a href="https://sifter.org/~simon/journal/20200429.html">April, 2020</a>. Science Tribe representatives have consistently pushed back, adamant that it's woo woo nonsense, that there is "no statistically significant effect" and other such fine tools of motivated incompetence. (Their supporting evidence is always lame, but they refuse to peel that onion any further than the dry skin on the outside which has "vitamin D is not the cure you're looking for" sharpied on it.) Well here's the latest: <a href="https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0263069">Pre-infection 25-hydroxyvitamin D3 levels and association with severity of COVID-19 illness</a> <blockquote> "Patients with vitamin D deficiency (<20 ng/mL) were 14 times more likely to have severe or critical disease than patients with 25(OH)D >=40 ng/mL" (14x: 95% CI 4-51; p<0.001) </blockquote> That alone would be not very interesting if very few people had poor vitamin D status, but alas that's common enough not only to account for many Covid deaths, but to account for nearly all of them. See particularly figure 2: <a href="https://sifter.org/~simon/journal/ims/20220204/figure2.png"><img src="https://sifter.org/~simon/journal/ims/20220204/figure2.png"></a> Remarkably similar to the plot I posted April 2020, and once again showing that there are essentially no critical (and very few severe) Covid cases with strong (prior!) vitamin-D status. (And recall that <a href="https://www.sciencedirect.com/science/article/pii/S0960076020302764">this study</a> among others showed it to be a causal and effective intervention, not merely an indicator of underlying poor health.) It would seem that most Covid deaths were (and continue to be) easily avoidable. Along with billions of pharma profits, but I digress. <hr> [Update Feb 6: Since multiple people have replied that vit-D status is just a proxy for BMI, I will highlight this excerpt from the above study: "Finally, among patients with a BMI <30, 49.5% have a 25(OH)D <20 ng/mL compared to 63.6% among patients with a BMI >= 30+ (p = 0.07, 2-sided; p = 0.04, 1-sided). The intensity of the correlation between BMI and vitamin D deficiency does not indicate a strong correlation (Crammer's V = 0.117). As a result, 25(OH)D was not, and cannot be, used as a surrogate value for BMI."] <center>[<a href="https://sifter.org/~simon/journal/20220125.2.h.html"><<</a> | <a href="https://sifter.org/~simon/journal/20220125.2.h.html">Prev</a> | <a href="https://sifter.org/~simon/journal/index.html">Index</a> | <a href="https://sifter.org/~simon/journal/20220707.html">Next</a> | <a href="https://sifter.org/~simon/journal/20230521.h.html">>></a>] </center> </blockquote> Covid Update: Public Surveyhttps://sifter.org/~simon/journal/20220707.htmlCovid Update: Public Surveyhttps://sifter.org/~simon/journal/20220707.htmlThu, 07 Jul 2022 00:00:00 GMT<blockquote style="margin: 0 auto; max-width: 800px;" morss_own_score="2.8346984363365597" morss_score="125.48840088271636"> <center> [<a href="https://sifter.org/~simon/journal/20220125.2.h.html"><<</a> | <a href="https://sifter.org/~simon/journal/20220204.html">Prev</a> | <a href="https://sifter.org/~simon/journal/index.html">Index</a> | <a href="https://sifter.org/~simon/journal/20220725.html">Next</a> | <a href="https://sifter.org/~simon/journal/20230521.h.html">>></a>] <h2>Thursday, July 07, 2022</h2> <h4>Covid Update: Public Survey</h4> </center> Wherein the vaccines once again appear to be doing more harm than good. Given that all-cause mortality was higher in the treatment arms for the Pfizer, Moderna and Novavax trials--even after all the <a href="https://www.bmj.com/content/375/bmj.n2635">shenanigans</a> and <a href="https://jackanapes.substack.com/p/is-subject-12312982-the-key-to-proving">fraudulent omissions</a>--it seems prudent to watch the population statistics in order to establish that the wishful thinking we now call Science is justified. Unfortunately, the CDC <a href="https://www.nytimes.com/2022/02/20/health/covid-cdc-data.html">isn't letting that data out</a>, and the summary stats that have been released have <a href="https://probabilityandlaw.blogspot.com/2021/11/is-vaccine-efficacy-statistical-illusion.html">statistical anomalies</a> so extreme as to render them completely untrustworthy. So, thusfar, the simple, straightforward data we need to answer the most basic questions about these vaccines on a large scale is nowhere to be found even though it surely exists. This in itself should make one go "hmm", but we can do our best to answer this objectively from wherever that data may <a href="https://sifter.org/~simon/journal/20211119.h.html">leak</a> or be indirectly observable. Presently, that is in a series of public surveys commissioned by <a href="https://stevekirsch.substack.com/">Steve Kirsch</a> but performed independently and without bias (default demographics were used) by <a href="https://www.pollfish.com/">Pollfish</a>. Granted, public surveys are worth what they're worth, but at the very least they give a sense of the public's subjective impression. Since each of his 500 sample surveys covers many of the same questions, I've aggregated them for better statistical strength. I won't give explicit error bars here, but I'll provide absolute counts. The stats are roughly the same from survey to survey, so I think these merged totals are fairly representative. These surveys are broadly sampled from ages 18 and up. The age-stratified answers which account for some differences in age sampling from the general population are not significantly different anywhere, and where they are they are so in a balanced matter (not really affecting the A/B ratios where that's what we care about) unless otherwise mentioned. As a point of calibration and to inspire some confidence in the survey, let's start with 1,504 answers to: <pre> [For those who were vaccinated] which covid vaccine did you receive? 44.5% - Pfizer 33.4% - Moderna 12.6% - Johnson & Johnson 6.1% - Mixed types 3.5% - Not sure </pre> The CDC claims: Pfizer - 57.5%, Moderna - 34.7%, JJ 7.7%. This is the one place where the age stratification did make a difference: The adjusted JJ is a fair bit lower, so over all this isn't too far off, especially if we figure most of the "combo" included Pfizer since the CDC stats here don't account for that. But it's not clear how the CDC tracks this stuff since they don't have a central database of who's been vaccinated (too many different venues of administration) so I think there's a lot of extrapolation going on there. I personally would bank on these user polls being closer to the truth for a question this basic than the CDC's bureaucracy can manage. In any event, it appears the surveys are giving reasonable returns, so not total junk. Moving on, The first item of note, answered by 3,001 people is: <pre> Have you received a covid vaccine? 25.0% - No 9.3% - Yes, 1 dose 34.8% - Yes, 2 doses 24.3% - Yes, 3 doses 6.6% - Yes, 4+ doses </pre> For this age range, the <a href="https://covid.cdc.gov/covid-data-tracker/#vaccinations_vacc-people-additional-dose-totalpop">CDC claims 90%</a> of the population has had at least one does, as compared to our survey result of 75%. Many data analysts have been suspicious that the CDC is overstating vaccination rates, and this would strongly support that. This is a very important number to have right because it is the denominator in many inferred-value calculations, particularly for how we interpret the number of hospitalizations and deaths which are vaccinated vs. not. Simply overstating the overall vaccination rate could, for instance, make useless or even harmful vaccines look good. (It is also an important metric for messaging: 9 out of 10 people creates a lot more social pressure than 3 out of 4.) Moving on to the meat of the survey, answered by 2,001 people: <pre> Did anyone in your household die from having a covid infection? 96.1% - No 3.9% - Yes (78 people) Did anyone in your household die from the covid vaccine? 95.6% - No 4.4% - Yes (88 people) </pre> Both of these Yes numbers seem high, but they age-stratify down a bit (proportionally, so no change in the ratio), and it's likely that a lot of people stretch the definition of household to include "someone they know". The thing to focus on here is the ratio between the two. (Worth note that 82 of the 88 vaccine related deaths were reported by people who self-reported as vaccinated--i.e., not "anti-vaxxers".) With those caveats in mind, if we take this survey at face value, more people have been killed by the vaccine than by covid. But that doesn't necessarily mean the vaccine is net-bad: It could be because the vaccine works. For instance, if it was 100% protective against death, then without the vaccine there would be 15.6% reporting a death from a covid infection instead of 3.9%--far outweighing the vaccine deaths at 4.4%. (In other words, it could be that the vaccine, while causing 88 deaths directly, prevented 312 covid deaths, leaving only 78 who died because they were unvaccinated.) So we need to adjust these values a bit in order to compare apples to apples, for which this question, asked of the 78 above, becomes germane: <pre> Did your household member who died from a covid infection receive at least one covid vaccine? 66.7% - Yes (52 people) 28.2% - No (22 people) 5.1% - Not sure ( 4 people) </pre> Clearly the vaccines are not 100% protective against death. Now, we can merge these into an inferred question about the 166 people who died (this is directly implied by the above but was not asked explicitly): <pre> Was your household member who died of covid-related issues vaccinated? 84.3% - Yes (52+88 people) 13.3% - No (22 people) 2.4% - Not sure ( 4 people) </pre> If we assume most of the people who died were older, we should probably compare this to the vaccination rates in the oldest cohort. (This is the biggest hole in this analysis--we really need the ages of the deceased, and fine grained vaccine uptake rates. But for now...) The survey says for age 55 and up, 80% are vaccinated (vs 75% for 18 and up). And if we're conservative and assume the "Not sure" are all "No", then about 16% of those who died were not vaccinated, which is less than 20% and so implies the vaccines are, on net, doing more harm than good (even after fudging some in favor of the vaccines). Another way to run the numbers is to ask: assuming this sample is representative, how many people would have died (vs 166) if nobody were vaccinated, or if everybody were? Using the 80% (4/5ths) figure as the presumed base vaccination rate: If everyone were vaccinated, then 5/4ths as many would have died from the vaccine, and 5/4ths as many would have died of covid while vaccinated, so: <pre> total deaths = 5/4 x (88 + 52) = 175 </pre> If no one were vaccinated, then nobody would have died from the vaccine, but 5x as many would have died of covid while not vaccinated, so (conservatively including "Not sure"): <pre> total deaths = 5 x 26 = 130 </pre> This conservatively implies that being vaccinated increases your chances of dying (of covid related causes, including the vaccine itself) by about 35%. This goes up to 64% if we assume instead that all the "Not Sure" were vaccinated. So 50% increased risk is probably a nice, round, ballpark, unbiased estimate. But of course, error bars, public poll, and all that, so who really knows. Still waiting for better data... <hr> 2022-07-25 UPDATE: See also <a href="https://stevekirsch.substack.com/p/our-latest-poll-vax-2x-deadlier-than">Steve Kirsch's latest poll</a> using a different polling company. Note in the <a href="https://www.questionpro.com/t/7BoNDsZtrha">details</a> the percent unvaccinated. Note the very good agreement on the distribuition of vax type. Note 4% of the ever-vaccinated report ending up in the hospital from the vaccine. 2023-03-30 UPDATE: See also <a href="https://news.northeastern.edu/wp-content/uploads/2023/03/Lazervaccines.pdf.pdf">A 50-STATE COVID-19 SURVEY</a> (A joint project of: Northeastern University, Harvard University, Rutgers University, and Northwestern University) which finds 25% unvaccinated in direct agreement with the above, and also discusses the divergence of CDC estimates, stating "these deviations almost certainly reflect errors in the underlying official records used by the CDC". <center>[<a href="https://sifter.org/~simon/journal/20220125.2.h.html"><<</a> | <a href="https://sifter.org/~simon/journal/20220204.html">Prev</a> | <a href="https://sifter.org/~simon/journal/index.html">Index</a> | <a href="https://sifter.org/~simon/journal/20220725.html">Next</a> | <a href="https://sifter.org/~simon/journal/20230521.h.html">>></a>] </center> </blockquote>