At any rate, I'm certainly not an expert. But there seems to be some missing BS filter where people can recognize something as silly if the example is silly enough but not in the exact same logic fail for something that seems "more reasonable somehow".
A classic example I recall is a Feynmann story, where a group of researchers were getting very statistically sound and repeatable results of very unusual and unexplained particle track behavior in a cloud chamber. Feynmann looked at the data and said "you probably have a tiny piece of metal in the cloud chamber somewhere" and that turned out to be the explanation.
Similar examples in the social sciences include systematic bias in the preparation and administration of IQ tests to different groups of people (see Charles Murray's 'Bell Curve' vs. Stephen J. Gould's 'The Mismeasure of Man').
Hundreds of other examples can be found across all scientific disciplines, unfortunately. To quote the smartest PI I ever worked for "There's a lot of BS in statistical analysis".
It seems like there's this extreme reaction against people behaving like correlation equals causation, but instead of over-emphasizing correlation, it gets dismissed entirely.
Ruling out chance through significance and power, what phenomenon in the world is correlated without being causally related _somehow_?
Repeat every week with the worst traffic intersection for accidents.
What you find is. IT WORKS! HURRAH! These intersections are more than usually not the worst the following week! The evidence is clear. The correlation is utterly compelling. It is significant. It has power. How could it possibly be unrelated?
Now if we stop it being comically silly in our example and make it a red light & speed camera, see how the issue is much more difficult. There is a clear line of potential causation of fixing dangerous intersections. But is it really better than folk dancing for 20 minutes at 2am? 
 This example should not be interpreted as being an opposition to all red light and speed cameras.
So in other words, several of the commenters here are right. On the one hand we shouldn't jump to conclusions, but on the other hand we should listen to the clues.
Nevertheless, the fallacy is so commonplace. You will easily find a seemingly educated person selectively balking at the notion that causal relationship is ultimately a conjecture or at the notion that causal relationship is possible, depending on their pre-existing beliefs.
Being emotionally attached to purported causal relationship X->Y, they will count all correlational evidence in favor; when pointed out that the evidence is correlational, they will wave it off with more correlational evidence.
If that causal relationship does not happen to align with their world view, of course, they will be right onto you with the old correlation-does-not-imply-causation mantra.
There's billions of possible variables. There's N^2 possible pairs of variables. It's not feasible to look at every pair that is correlated.
so, everything defying common sense should be reviewed, to find why and how exactly is this happening.
If we can get there, then we can talk about what we can do to improve things from there.
Yes, I agree, and this is precisely my point. My experience with introductory stats was a heavy focus on the technical details, when in fact what would be more effective is focusing on statistical logic.
I’m specifically thinking that something like Judea Pearl’s The Book of Why would be good to introduce early in stats education.
I don't know, most of the misinformation on the matter I've seen is just flat out wrong. Not misinterpreting statistics incorrect, just flat out lying, using false numbers or statements, etc. Having a cursory knowledge of statistics won't help you if you're incapable of Googling to check if a statistic is true or not.
I think a lot of it is more ideological at the "average" citizen level - on both sides. Most people aren't looking at the data, they're believing whatever they're told that aligns with their personal beliefs.
People intentionally or repeatedly inadvertently publishing BS should be called out and their opinions down-weighted heavily.
People having a good BS filter is one step in the chain towards this down-weighting, but isn’t the whole chain. If anything, people slinging BS today are likely to gain additional reach and opinion-weight, rather than to lose it.
But thinking about this from a loosely signal-process-y angle, once you have a BS signal in one channel that routes to a a particular set of minds, how does one route the corrective signal to that same set of minds (as opposed to, say, just your local friends who already agree with you anyway)? And even supposing you do, those minds are already programmed to process these signals in particular ways that probably means they're predisposed to accepting one or the other before either signal even arrives.
The answer to this has always been to address the root of the problem, the preprogramming, through (relatively) uniform mass education, because that's the one and only place where you can (relatively) uniformly cram ideas into everyone's brain before they scatter to the winds and begin fancying themselves "free thinkers".
Right now, sources of bad information get systemically louder, not quieter, over time. That’s way worse.
This works well naturally in small communities, but once the society becomes too large, BSers, liars, and scammers can just move on to a new gullible crowd.
So we got social media with review & reputation management systems, and these are now, of course, promptly gamed to the max. Moreover, this gaming is being done by the very people who should be most de-amplified, in order to amplify their BS, inlcuding everyone from just trolls to professional RUS dezinformatsiya shops (that'll gather a lot of downvotes).
So yes, a huge part of the solution is to de-amplify the crowd that spews Bs or deliberate lies.
Sure, freedom of speech is a right, but no one has to be required to amplify you on their platform - that takes away the freedom of speech of the platform owner (e.g., if HN were required to amplify everyone, then moderation would become effectively illegal).
Why does this view gain downvotes so frequently? IDK, but it seems to be mostly readers with no nuance who think that freedom of speech requires zero restrictions, so any shadow of moderation or restriction rankles them, and they are not articulate enough to state a reason, but can still hit the down-arrow.
I don't think your opinion is unpopular because it's wrong. It's unpopular because it's empirically impractical. People don't suffer a reputational hit for publishing BS, and saying "But they should" doesn't get us anywhere (as you yourself point out). How do you propose that we actually cause reputational hits for such people?
One way is to teach additional statistical literacy to the general public.
There are probably other proposals worth trying and I'd be interested in hearing your takes on what they are. (One that might be effective - though certainly controversial - is for the government to say that Alex Berenson is actively putting lives in danger with lies and that, if the untruth of his statements can be proven in court, he should be subject to criminal penalties, just like Elizabeth Holmes is on trial for lying about her blood tests. But that seems a lot less good for society as a whole than teaching statistical literacy.)
Elizabeth Holmes is on trial for lying about things where she had a specific legal obligation to tell the truth. I’d never heard of Alex Berenson before today, but I doubt his situation is one in which he’s obligated to tell the truth. That’s okay. Sunday school preachers aren’t either and we’re cool with that. We’re good with the Santa and Easter Bunny myths.
The same is also true of more or less the entire field of nutrition, none of which has yielded anything useful, and has resulted in governments themselves spreading misinformation:
Incidentally, Berenson has written a long rebuttal to this kind of thing which you can find here:
This is a bold claim and I'd be curious to see you back this up. By "lockdowns" - do you mean actual, genuine lockdowns / quarantines (mandatory stay-at-home orders, government-distributed emergency food packs and other essentials), or do you mean capacity restrictions etc. that get called "lockdowns" in the popular media?
Note that my straw-man proposal (which I'm not seriously endorsing) is not that it should be prosecutable to have been wrong. Plenty of startups try to build something, and it doesn't work; they don't get prosecuted like Holmes. Holmes is facing prosecution for fraud, for knowingly telling falsehoods. If your implication is that academic epidemiologists, COVID experts, and the entire field of nutrition are all fraudulent as opposed to merely just going through the usual course of science - which, to be clear, I see as mostly but not entirely impossible - then yes, I think we have a rather serious problem on our hands, which we need to figure out for the survival of humanity, and I'll repeat my comment above: I'm very interested in knowing what proposals you have for solving it.
"Quarantine of exposed individuals", "contact tracing", "border closures" and "internal travel restrictions" are "not recommended under any circumstances".
"Home quarantine of exposed individuals to reduce transmission is not recommended because there is no obvious rationale for this measure, and there would be considerable difficulties in implementing it"
And: "Border closures may be considered only by small island nations in severe pandemics and epidemics, but must be weighed against potentially serious economic consequences."
Also: "There is also a lack of evidence for the effectiveness of improved respiratory etiquette and the use of face masks in community settings during influenza epidemics and pandemics."
Finally: "This document will serve as a core component of WHO’s influenza prevention and control programme in community settings".
Consider that this was published in 2019. Less than a year later every single position had been inverted, and epidemiologists / public health experts were telling the world that "the science" didn't just recommend all these things but outright required them. The masks issue is especially neuralgic because at the start they correctly stated that there was no evidence mask mandates would have any effect, then flipped their position overnight and asserted anyone who thought otherwise was ignoring science.
As you correctly argue, there must be never be punishments for being wrong. However this is not a case of merely being wrong. No new evidence came to light to cause these flips in position, and in fact - as predicted - lockdowns, masks and so on have had no impact on the course of the pandemic. The models that were used to justify lockdowns were never validated against reality, and even contained severe coding errors: the people behind them have never admitted they did anything wrong here. Moreover the people who pushed hardest for lockdowns consistently claimed that there was "scientific consensus" behind what they were doing, even though just a year earlier the WHO itself had published a document stating that their recommendations should never be used in any circumstances! In other words, they were lying.
And that's before we get to the fact that the WHO has a long track record of going into mad panics over diseases that are extremely mild or may not even exist at all.
Der Spiegel, 2010, "Reconstruction of a Mass Hysteria: The Swine Flu Panic of 2009", https://www.spiegel.de/international/world/reconstruction-of...
Unherd, 2021, "Is the WHO inventing diseases" (in reference to gaming addiction disorder), https://unherd.com/2021/11/whats-china-got-against-gaming/
Any standard that allowed people to be imprisoned for spreading misinformation that was applied fairly would quite simply result in the mass imprisonment of public health officials, advisors and experts.
Hence my question about what you mean by "lockdown." This document actually argues in favor of the sorts of things called "lockdowns" in the media, and against quarantines - which was not my personal position, but I think it definitely does not back up the claim that lockdowns (in the media sense) do not work, either.
I would also note that right beside all of the things you quote is a column "Quality of evidence," and the recommendations saying that you should avoid home quarantines and border closures are based on evidence of "very low" quality. So I don't think that you or the WHO actually have evidence saying that these things don't work. The WHO just went with their gut feelings that they were bad ideas. Now we have facts, which supersede feelings. That is an appropriate, science-based reason to change your opinions.
(Also, SARS-COV-2 is not an influenza pandemic, it's a SARS pandemic, and this document is about influenza.)
Edit: jesus christ you were right
(because of pregnancy)
Maybe basic introductory statistics is more useful than basic introductory calculus though.
Should the general population be better at such things? Yes, of course.
However, in nearly every case such things reach a broader audience via mainstream media. And how many times have we seen those entries confuse correlation with causation? We've seen it so many times that it's safe to assume it's intentional. Surely, after each incident of such negligence a teacher or professor or math savvy citizen reaches out to correct them. Yet? Never a correction or retraction?? Never a spark of "we need to educate our journalists"?
Repeat something often enough and it becomes truth in the minds of the receivers. Toss in confirmation bias and echo chambers and even if your better educated the masses, the media and those "journalists" would mitigate public's understanding.
A public education system that creates a population conditioned to believe whatever any 'authority figure' says is also a system designed to create a population ripe for exploitation by advertisers. Similarly, the ideal authoritarian state desires a population that is generally ignorant and obedient, and that's what's been created in much of the United States.
A general population that has the tools and skills needed to independently analyze the claims of government authority figures and cable TV and Internet advertisers, that's not what an elitist-authoritarian system desires.
It's very sad to see people who completely lack these tools and skills attempting to do their own well-intentioned analysis, they're so easily manipulated by dishonest actors. They know enough to distrust 'authority figures', but not enough to conduct independent evaluations of claims. Such people have been sabotaged by the educational system.
Maybe combined with motivated reasoning.
Statistics like any math class was just another pointless and imposed game of symbol manipulation, for most. Not something that affects how they see the world or how they process disinformation (which disables rational thinking by appeals to emotion, so rational capabilities aren't necessarily even the issue).
Humans are naturally using statistical type reasoning all the time and are very good at it. But when it comes to things like in-group out-group consensus-forming conformity mechanisms, the whole point is they _overcome rationality_ for social cohesion. To follow rationality instead of the group, you have to leave the group, which is unthinkable, so your mind prevents you from thinking it long enough to change your mind, by emotional terminations.
Another solution might be convincing people to not pay attention to so many hot botton issues and not turn everything into a debate. A certain amount of detachment is probably more healthy for individuals and for the society.
It is important because if you flip a coin 20 times and get 20 tails, there is probably something fishy with that coin and you probably should bet tails. If it is 100 out of 100 (or even 95 out of 100), there is effectively zero chance that the coin is fair.
This can be modeled using Bayesian statistics. You start by assuming with a reasonably high probability that the coin is fair, then you revise your assumptions as you get more and more data.
The general idea is: if a coin flip lands on tails for too many times, you should probably bet on tails. You shouldn't try that in casinos: games are seriously checked for fairness (of course, the rules make it so that the house has an edge). But in an informal setting, it can get you a small advantage.
It's harder to cure a gambling addiction than just giving them math facts. They don't even accept the fact they're addicts. To accept it would feel bad so they don't have the bad feeling thoughts. This emotional stuff just doesn't yield to facts.
We should teach math literacy -- how to use math to understand the world we live in, e.g. some stats as you mentioned, basic finance (the glories of compound interest), sizing stuff, etc.
There's an absolute jungle of information we're presented with each day, and clearly many people would just straight up buy the vaccines-cause-death statistics uncritically.
There's no critical thinking without critical stats. How are the numbers made, what do they mean? Just about every field requires you to understand this, especially the social science fields where we're talking about some quite substantial issues like replication crisis. Things like economics as well, they're things everyone wants to understand but we don't give people the tools.
Somehow we have also missed out causality, when we've had the tools for a while. I reckon it's actually quite teachable though it currently feels like an advanced subject due to historical quirks.
Try swapping the graph labels with:
Took vitamin D pills,
Excercised 30mins a week,
Got the vaccine.
Most would agree that all three points probably have some level of health benefit. Suddenly the cause vs correlation can be much more difficult for the average person to determine.
Do all three reduce the death risk? Do some of them just also trend with more health conscious individuals? Are any of the three just completely bogus?
What we are looking at is Simpson's Paradox, where the true causal relationship is obscured by information that isn't obvious from the plot.
Now before you correlation != causation, there is actually a causation here that you can access with statistics.
This example is not Simpson’s paradox, it is simply the misuse of statistics. Statistics, being mechanical transformations of data, only have semantics within a causal model. Simply picking variables randomly and then assuming causality when the statistics behave that way is inverting the process of knowledge formation.
EDIT: Thanks for the corrections—the real data that this fictional example is based on does show Simpson’s paradox, as the dependent variable (death rates) appears to show a positive correlation with vaccination status when aggregating the population, but a negative correlation for every age group individually.
If you read to the end of the post, you'll see that the author was using this correlation to prove that the mistake is identical to another claim related to COVID . This COVID-related correlation doesn't seem as spurious as the Ghostbusters one, but that's because it's much harder to spot errors like this when variables aren't so "random".
: "Vaccinated English adults under 60 are dying at twice the rate of unvaccinated people the same age"
Where it falls relies on the viewer's knowledge of the problem space, which can also be limited enough to lure them into false causations.
My point would be that a single graph showing two trends without any further info should never be taken as more information than "there is two trends". You'll still be free to decide there is true causality based on other information you believe.
> Being keenly aware of political biases on both sides, my goal is to try to remain as apolitical as possible and try to filter out what I perceive as political biases and describe what I consider to be key insights gained from a particular report or resource
It’s hard to tell what’s a joke anymore.
The study at the bottom shows that vaccinated people are dying at a higher rate than unvaccinated people. The joke is on the person who concludes that the increase in death rate is because of the vaccine and not the age difference.
They simply switched the labels.
Not very well. You can see they didn't change the axis labels in this image here: https://static.wixstatic.com/media/cf58cd_449149dafb04485eb2...
So the data is valid, the point is valid, but the point isn't about ghostbusters.
In the days of big data, to state that exact behaviors could not be determined is just not trying very hard.
For instance, this article has a silly example of confounding variables (which ghostbusters you watched as a child is correlated to your age, and age is correlated to covid mortality).
It proceeds to present two graphs “debunking” an anti-vax conspiracy. The first graph specifically controls for age, vaccination rates, and size of population.
After preventing strong evidence to the contrary, the article then implies the conspiracy theory made the same mistake as the ghostbusters analysis. It provides an incomprehensible graph as evidence.
So, F’s in Statistics 101 for everyone.
> Age 10-59
This is what he's talking about: https://en.wikipedia.org/wiki/Milankovitch_cycles
Here's a graph similar to his, hosted on German Wikipedia: https://de.wikipedia.org/wiki/Milankovi%C4%87-Zyklen#/media/...
Nobody brings it up, because scientists don't believe the observed changes in temperatures are due to Milankovitch cycles, since global warming is happening on the order of decades and not millenia.
Here's NASA's take: https://climate.nasa.gov/ask-nasa-climate/2949/why-milankovi...
There are certainly overlapping effects, but the model would fail to predict temperatures.
How do we know that temperatures inferred from ice-cores (or whatever) are not extremely smoothed due to natural phenomena? Can we really get resolution down to individual years such that they agree across different test sites and methods?
> Boghossian, Lindsay, and Pluckrose wrote 20 articles that promoted deliberately absurd ideas or morally questionable acts and submitted them to various peer-reviewed journals. Although they had planned for the project to run until January 2019, the trio admitted to the hoax in October 2018 after journalists from The Wall Street Journal revealed that "Helen Wilson", the pseudonym used for their article published in Gender, Place & Culture, did not exist. By the time of the reveal, 4 of their 20 papers had been published; 3 had been accepted but not yet published; 6 had been rejected; and 7 were still under review. Included among the articles that were published were arguments that dogs engage in rape culture and that men could reduce their transphobia by anally penetrating themselves with sex toys, as well as Adolf Hitler's Mein Kampf rewritten in feminist language. The first of these had won special recognition from the journal that published it.
> Mein Kampf and intersectional feminism aren’t usually lumped together in many people’s minds, but if linked with the right language and buzzwords, left-wing academic publications apparently will accept the combination as scholarship.
 - https://en.wikipedia.org/wiki/Simpson%27s_paradox#Correlatio...
For example, he portrayed New Zealand's 2-week quarantine requirements for incoming travellers to New Zealand as "indefinite confinement for New Zealanders". When people pointed out the gulf between what he was saying and what the law was, he doubled down. I'd share the exact tweets, but unfortunately his account is now suspended. Twitter really needs a way to access tweets from banned accounts in a way that removes their virality but preserves them for posterity.
The most charitable interpretation is he believes he is seeing something that the rest of us aren't, and he is willing to nobly risk his reputation in order to warn us and, thus, protect us. He is doing us a service at great cost to himself.
That is certainly possible. I think it is more likely that he likes attention and money. This isn't an insult to him - I also like money, and sometimes, attention. For only $29.99, you may buy his new book, "Pandemia: How Coronavirus Hysteria Took Over Our Government, Rights, and Lives". The link is available in his Substack. (And presumably would have been available in his Twitter account, had Twitter not suspended it.)
A pandemic, by itself, would be a tragic loss of innocent lives. A pandemic where half the people involved are telling each other to make themselves more likely to die, and then they all die as a result - now that's a plot Screwtape would love.
Remember Satan's original plan. Are you such a sheep that you're going to be afraid of one fruit because you were told to be afraid of it? Why live in fear? Look how good the fruit is, and make use of the freedom you have to eat it. "You will not surely die."
For me, the response to the pandemic - and especially the extent to which the pandemic is much worse because of the human response to it, from so many different politicians and business leaders in so many places - just confirms that human evil is real.
Deleting banned accounts whitewashes the history of the person that got banned, allowing them to repeat the cycle without changing names/pseudonyms.
That’s probably a win for engagement and trolls, but a loss for everyone else.
All of that to to say that describing NZ as a "reverse" open-air prison is so far beyond absurd I don't even know what to say. For one thing, Kiwis are free to leave NZ - perhaps it's Australia you're thinking of, which really did lock its citizens at home under punishment of 5 years in prison or a $66,000 fine?
It’s such a prison that billionaires are voluntarily securing land and building mansions in case the whole world goes tits up. Such a terrible place. /s
(Note: I’m aware it’s not some perfect utopia and one of its issues is things can be expensive to live there, especially housing)
Yes, I know that (most probably) New Zealanders were perfectly free to go out to another country had they wished to do so, but once there they couldn't have come back (unless they were a multi-billionaire like the Google guy), I regard that as a prison-like system, because it majorly forces you to remain put (most probably your family, your job, your everything are located in New Zealand, you don't want to give them away). Yes, it is a system that saved lives, but nevertheless it is a system that restricted the freedom of movement of its citizens for almost two years now.
A quarantine hotel that a bunch of assholes were so fucking impatient that they literally climbed fences and dodged security to escape from just to grab beer or some shit and wasted millions of dollars as New Zealand tried to contact trace everyone they came in contact with and try to keep a spread on it further.
When all they had to do was chill in a hotel for two weeks and then they'd be free to do whatever.
A couple of these might be the same person, I just did a quick google search, but I think I've seen at least a dozen of these stories out of New Zealand over the past year and a half.
That wasn't the argument Berenson was putting forth. He was saying that some large number of New Zealanders would be detained indefinitely in congregate settings purpose-built by the government.
Again, I wish I could cite the specific things, but I cannot. I was left with the very strong impression that Berenson did not care about facts.
I believe you, assume you're correct, he's (nor anyone else like that) just not 'on my radar' at all. I just assumed prominence/virality of at least this one post due to the existence of one (the submission) refuting it.
I had a discussion about it at work because my teammate is vocal about the alleged harm that vaccines cause and is no stranger to confirmation bias.
Shame that they lumped so many people into the same group, because if you look closer at the data for e.g. England:
There's a strong correlation between age and vaccine intake, because older people were given priority.
The difference in intake among the age groups is as high as 50 percentage points.
This is the flaw in the UK aggregation, as cited from Table 4 by the blogger. 10-59 lumps nearly-invulnerable children in the same bucket with 50-something obese diabetic smokers.
Table 8, and the last line of Table 1, show properly-weighted vaccination effects.
Most of the high level problems in our civilization require years of study to even be capable of formulating a valid opinion.
The thing people have to do is to instead focus on evaluating people and deciding who probably knows who they are talking about. This is the same thing successful leaders and managers have to do when they hire. Unfortunately there is no foolproof method. Going with the consensus in a field is going to yield better than average results, but it's not a perfect rule by any means.
What we do need to do is educate people out of new forms of innumeracy and illiteracy, where they are falling prey to basic fallacies of statistics or rhetorical tricks like motte and bailey and cat couplings.
People are generally familiar with logical fallacies like ad hominem, strawman arguments, or circular reasoning. New weapons of persuasion are getting crafted every day; we owe it to ourselves, each other, and the future humans to educate them on defense against the dark arts.
What I do see happening in that timeframe is a recognition that these skills are foundational to online culture and discourse, and a push to inculcate them in forthcoming generations through education and private and public policy action.
An immune response evolving to the environmental harms of Twitter, if you will.
But yeah - that chap who keeps failing at science in your Insta is likely a lost cause.
Exactly what the previous comment said.
It is an attempt to lower the status, and presumably power, of "the elites" (credentialed experts), mostly perpetrated by the real (monied) elites.
The wealthy or semi-wealthy are either riding the wave for their own benefit or don't like what the expertise says.
This is hard, possibly just as hard as “doing your own research”.
Most people I explain this to recognise the fallacy, even if they're not trained in statistics.
A huge problem with vaccine denialism is that it stems from motivated thinking. People aren't being persuaded by bullshit arguments; rather, they already agree with the conclusions, and look to these spurious correlations as emotional support.
If you scroll down to "Total Coronavirus Deaths" and click near the middle on December 11th, you'll notice a very rapid increase in deaths. December 11th was when we started vaccinating against covid.
I'm not saying that the vax is killing people, but this is a diehard argument from those who are negative against the covid vaccine.
What could a reasonable explanation be?
PS: Someone filed for more insight with our national institute of health (SSI) and they replied that following the first shots in December 2020, about 4.500 people died within 30 days. This is generally understood to be because the group we vaccinated first was already above the mean expected age, so their time was already up so to speak, ie. death could have been caused by anything, including old age.
I think it only caught the attention of the mainstream, because in all of 2020 we had a total of 1.250 "deaths with covid" whereof about 1.000 of these had more than 2 co-morbidities.
Present day we have about 430k active cases, which is almost 10% of the population, but the % is still 2.3%.
Vaccination has continued in Denmark so if vaccines were killing people we'd expect to see that rocketing as Denmark has one of the highest vaccination rates.
I think the causality is:
More illness -> More people get tested
More illness -> More people get vaccinated
More illness -> More people die
The reason we are testing 200k/day is because you don't have many options for moving around without a valid test or vaccine. Ie. school, shopping, work etc requires it.
Of course Alex Berenson understands this perfectly well.
He's among the utterly despicable group pushing various forms of covid denial for the benefit boosting their standing in their tribe. Whether it's for $-for-clicks or political capital or just to make themselves feel good, it's pathetic and terrible.
Speaking directly to the people doing this on HN (including in this very thread): you're going to have to go to the end of your life knowing that when things were bad, you made them worse, and got people killed who didn't have to die like that. Do you really want the biggest contribution of your life on the world to be bad one, and for petty, pathetic reasons? Really, think about it. Do you want your life to have been about fooling people about the risks of covid, covid vaccines, and the general value of science? You don't have to live a sad, pathetic, less-than-meaningless life.
If things aren't good, go out there and contribute rather than just tear things down.
Same thing here, this is only impressive to people who don't know how to interpret statistics.
I had mistakenly believed that Twain originated this remark until I looked it up just now.
> I have checked the underlying dataset myself and the graph plotted above [the photoshopped one] is correct. People under 60 who watched the 1984 Ghostbusters movie are twice as likely to die as people who watched the 2021 Ghostbusters movie. The overall deaths in Britain are running well above normal.
The poster of this article is observably a liar. Perhaps there is some kind of point to be made here, but I'll wait until someone honest attempts to present it.
I do like the original Ghostbusters movie, but I'm not sure that really added to the effect for me.
I’m commenting on the relative merit of the craft and thoughtfulness and humor that went into the attempt.
When 80% of the population is vaccinated, the base rate of dying of anything at all carries over with them as people change their own status from one category to the next, creating a false causality link between the base rate of dying anyway and their status change to vaccinated. I'd say now do covid and its variants, but regardless, well done.
We need smarter and more compelling people making these cases for important things instead of feeding lines to actors and poli-sci bureaucrats on television. The hardest part of the pandemic I think will have been establishments everywhere realizing that people thought they were too dumb to be believed. One of my favorite Holzer truisms is, "A lack of charisma can be fatal," and I when I look at how this has played out, it's because the people announcing information and policies couldn't be taken seriously by 30%+ of the population even when they were telling the truth - which, unfortunately, was less than the whole time as well.
"being vaccinated" -> "watched the 1984 Ghostbusters"
"unvaccinated" -> "2021 Ghostbusters movie"
There. Saved you a click.
Hey, what was that?
We detached this subthread from https://news.ycombinator.com/item?id=29369974.
Also, your account appears to be using HN primarily for ideological battle. We ban accounts that do that, regardless of which ideology they're battling for, because it's destructive of the core value of this site (intellectual curiosity). If you wouldn't mind reviewing https://news.ycombinator.com/newsguidelines.html and sticking to the intended use of HN, we'd appreciate it. We've had to ask you about this before, so please fix this.
Well, at least we know where you stand on that subject then. It may be a source of science denying on the left, I'm not aware of that but I am aware that it is is a main source of racism from the rabid right.
My take on what the Charles Murray crowd (and its antecedents dating back to Francis Galton's Social Darwinism) is that it's just an attempt to justify the social status quo based on 'genetic superiority of the ruling class'. This is merely a replacement for the previous (and completely discredited) religious justification for the social status quo, i.e. priests telling the serfs and slaves that 'The gods have blessed the divine kings'. We also have the economists getting in on the game, telling everyone that gross wealth disparity is the inevitable result of pure econometric theory and so on.
For other hilarious takes on this, I always point to the "Nobel Prize Sperm Bank"
Edit: this comment and others now appear to be nonsensical because OP essentially replaced their comment with an entirely different one.
No. This article is like factcheckers satirically explaining how statistics work to an author that clearly has no clue. In fact it’s not like that, it is that.
Still why would people with 1 dose be dying more than unvaccinated?
But due to the 3g rule (access to events or buildings is granted to the vaccinated, recovered or people with a PCR test less than 24h ago) in countries like Germany, guess which group is tested most: The unvaccinated. Other groups do not need tests!
"A study done by the CDC in New York accounted for the following — “A total of 1,271 new COVID-19 hospitalizations (0.17 per 100,000 person-days) occurred among fully vaccinated adults, compared with 7,308 (2.03 per 100,000 person-days) among unvaccinated adults”."
There could be value in reducing spread due to vaccinated people (depending on how much of it there is, as you say, we don't have good surveillance of it), but there's lots of value in reducing hospitalizations, and that's what many of those statements are about.
Just pointing out the faulty logic would've made for a boring post that many people wouldn't have bothered reading, and would risk being dismissed as hand-waving or rationalizing. Picking something eye-catching and obviously ridiculous keeps people's attention, and also can't be dismissed as mere rhetoric since the conclusion does actually hold.
I do agree with you that mockery is unlikely to win hearts and minds, but the whole problem here is that the concerns are not valid and the people with concerns are not studying the figures and the people they're arguing against are not saying "just do as we say," and yet the concerns persist.
> I don't know how to explain this other than movie-caused mortality.
The above sentence alone gets my Skepticism antennae whirling, let alone the majority of the (relatively unassociated) facts.
What the heck is movie-caused mortality?
An exact search[0^] returns this same HN post, no help there.
An inexact search[1^] returns results mainly about deaths that occurred during the filming of a movie or TV show. These deaths are very much not the point the OP is trying to make.
Issue #1): the sentence quoted above is non-sensical, as the OP's purported method for "how to explain this," doesn't explain anything, let alone anything related to the point OP is trying to make.
Issue #2): Even if "movie-caused mortality" was a valid explanation... Not knowing how to explain something doesn't allow one to arrive at any conclusion (other than, "the thing can not be explained," pedantically speaking).
Frankly, it makes as much (as little!) sense as, "I don't know how to explain this other than time-traveling telepathic murder bots."
BTW, More or Less is a great data science / stats podcast! https://www.bbc.co.uk/programmes/b006qshd