Common misunderstandings of Ayn Rand

Ayn Rand, the author of Atlas Shrugged. You either love her or hate her!

But I read Atlas Shrugged without knowing that you were supposed to love her or hate her. I just knew that it was a title that kept popping up here and there, in a number of different contexts, and so eventually, I felt I had to read that book that so many people seemed to be talking about!

And my reaction was:

'Wow!... I've never looked at it this way before!... This woman is bright!'

Afterwards, when talking about this book, I discovered the strong emotional reactions people have to her. I also discovered how - as can be expected when feelings run hot! - most people had a rather incorrect idea of what she had actually said, and what she actually believed.

One common misunderstanding of her that I came across was this one:

"She claimed that rich people are some kind of altruistic, highly talented, good-hearted super-humans that if left alone will never do anything bad, but only use their talents and riches to improve the world."

This is not what she said.

Ayn Rand said that there are exactly TWO ways to become rich in this world. No more and no less. The first one is to be pretty much what was described above: Talented and productive. You produce some kind of value that people are prepared to pay for, willingly! They buy whatever you are producing, and feel that they have made a good purchase; that they got good value for their money. You get rich and they get satisfied. Everybody wins.

The second way to get rich, also the last way, since there are only two, is to loot somebody else who is productive. There are no other ways, she said! The value has to come from somewhere - it doesn't just fall from the sky or spring out of thin air. And so if you are rich, then either you produced that value or you stole it.

She also said that it's not necessary that the person you loot be richer than you, or as rich as you. She said there is also the Indian Maharaja: The only rich person in a country of poor. Because no matter how poor a population is, there is always enough to loot for ONE person to be rich! And she said the problem in our societies is that too many people want to be that Indian Maharaja. You often find them in politics. They don't care about the prosperity of society! They don't care if society plummets into utter despair! So long as they can steal enough from it to be rich, themselves. And the problem with this, of course, is that there can be only one Maharaja... So the only thing they will succeed at is to make society poorer, to the detriment of all. Everybody loses.

“When a society establishes criminals-by-right and looters-by-law, men who use force to seize the wealth of disarmed victims, then money becomes its creators' avenger. Such looters believe it safe to rob defenseless men, once they've passed a law to disarm them. But their loot becomes the magnet for other looters, who get it from them as they got it. Then the race goes, not to the ablest at production, but to those most ruthless at brutality. When force is the standard, the murderer wins over the pickpocket. And then that society vanishes, in a spread of ruins and slaughter.”

Ayn Rand - Atlas Shrugged

 

 Another misunderstanding of Ayn Rand that I came across was this:

"She's such a hypocrite! She wrote 'The Virtue of Selfishness' only as a desperate attempt to justify why she didn't help her poor relatives back in Soviet, after she got rich in America."

Let me show you another quote from Atlas Shrugged:

“People think that a liar gains a victory over his victim. What I’ve learned is that a lie is an act of self-abdication, because one surrenders one’s reality to the person to whom one lies, making that person one’s master, condemning oneself from then on to faking the sort of reality that person’s view requires to be faked…The man who lies to the world, is the world’s slave from then on."

 Ayn Rand - Atlas Shrugged

Tell me: Can somebody who writes a quote like that be a hypocrite? No, I would say. Because a person who feels that a quote like that rings true wouldn't WANT to lie... It would be an act of self-abdication. Of making oneself the world's slave, condemned to trying to fake the kind of reality that the world approves of. Ayn Rand doesn't care what you approve of! She stands up for HER OWN beliefs.

The quote continues, in the book:

“There are no white lies, there is only the blackest of destruction, and a white lie is the blackest of all.”

This reveals even clearer how very strongly she feels about any kind of dishonesty or of bending the truth. But I intentionally put this separate from the lines before it, because I don't feel it fits the context! The lines before are a cool, logical reasoning - this is a sudden outburst of emotion! And as Virginia Wolf writes, in A Room of One's Own: "An angry writer is a bad writer". Ayn Rand is often a bad writer, because of her anger seeping through. She was, after all, an illegal refugee from the Soviet Union, and she is angry with her motherland, oh how angry she is!...

And I believe this is why most people love her! Not because they understand what she really meant with her philosophy, but because they share her anger towards communism and socialism! Because the villains in Rand's books do come out as very Soviet communist-like... That was the face of evil, to her. But when American Christian right-wing politicians expressed love for her philosophy, she protested! They were far too limiting of people's freedom for her. For one thing, she was sex positive, perhaps even polyamorous in her ideology, although those terms didn't exist at the time. She was also a staunch atheist and advocated abortion rights. American Christian Conservatives were, of course, far from this! Had she grown up in the USA instead of the Soviet Union, perhaps they would have been the paint that she painted her villains with? Who knows.

And had that been the case, the left-wing would have been the ones who loved her! Now, sharing a common enemy with her.

Ironic, though. Isn't it?

I warmly recommend you read the book. Not as a novel! It's not a great novel (although the story is also captivating), and you would have to put up with her anger, which gets rather bitter, at times... But in her good moments, Ayn Rand is, indeed, a very bright woman. She has some very clear thoughts, well worth reading for oneself, rather than through the lens of somebody else who either loves her or hates her, probably for the wrong reasons... 😏

Overall Mortality for Vaccinated and Unvaccinated Respectively

That's what we want to know, isn't it? So that we can see if the vaccines have saved lives or not, when considering not only the risk from the disease, COVID-19, but also the rare side effects of the vaccines.

However, there is no institute or agency that publishes this data that I've found. At least not directly. But here is my brave attempt at compiling this data myself, from statistics that are available. I will discuss uncertainties etc. below, as I narrate how I did my compilation, but this is the end result:

(A person here counts as "vaccinated" if they have had at least one injection. Most of those have also had two or three injections.)

This looks pretty good! Clearly, the vaccines have saved lives, especially in the 80+ group. But if we zoom in on the lower age groups, which are maybe a bit too small to see in the above graph, it actually looks like this:

Here, we see that the mortality is actually slightly higher among the vaccinated than among the unvaccinated in the age group 10-39!... Now, the death numbers in this group are very low so it's likely this small difference is not significant, and the data is also preliminary. Therefore, this result may very well change when the numbers are finalized. Then again, if this does turn out to be the case, it is, of course, a huge scandal.

This is the data table:

About the data

There are uncertainties in the above data. Mostly so because even though there is rather good (if also preliminary) data for the number of deaths, and the health care knows exactly how many vaccination doses they have given, it turned out to be hard to find exactly how many unvaccinated people there were!... The number of unvaccinated is the population size minus the number of vaccinated, but population data is apparently just an estimate.

But here, let me explain what I did, before presenting my conclusions below:

As I said, I wanted to know the overall, i.e. all-cause, mortality for vaccinated and unvaccinated respectively. This would give a robust measure of whether or not the vaccines have saved lives, and if so roughly how many, independent of differing definitions of what constitutes a "covid death" and other vagaries. Since both a death count and a vaccination count are so robust and straightforward, this also minimizes the risk of any human bias in collecting the data.

I chose England for my analysis, because someone tipped me off that their Office for National Statistics, ONS, publishes data over death numbers by vaccination status. They do so in a table looking like this:

That is the tab "Table 12" from the Excel file that can be downloaded here:

https://www.ons.gov.uk/peoplepopulationandcommunity/birthsdeathsandmarriages/deaths/datasets/deathsbyvaccinationstatusengland?fbclid=IwAR3NI_xGROkmMEcyW48zKRffmVR2WNFJAxKcEsJhnkQBut9gSTAzh0q3GJs 

by clicking "Deaths occurring between 1 January and 31 December 2021 edition of this dataset".

Now, to find and compare the mortalities for the different groups, I needed to know how many people were in each group, vaccinated and unvaccinated respectively. I found such data by clicking "Download" here, on (the beautiful) date 2022-02-20:

That's the bottom graph on this UK Government page on COVID-19:

https://coronavirus.data.gov.uk/details/vaccinations?areaType=nation&areaName=England

(You have to choose "England" at the top of the page for this graph to appear.)

I downloaded the data in JSON format, and then converted it into an Excel file with some online converter, probably this one: https://www.convertcsv.com/json-to-csv.htm 

I noticed that this gave me the number of vaccinations given each day, plus the cumulative value on that day, and also the population size in each age group on that day. But when working with the data, I soon noticed that the population was exactly the same for every day of the year, in each age group. This obviously wasn't right, since every day people have birthdays, thus moving in and out of the age groups... As you can maybe see in the image above, they say: "For English areas, the denominator is the number of people aged 12 and over on the National Immunisation Management Service (NIMS) database." Why this is the same every day, I don't know. But anyway, if the UK Government felt it was good enough for them, I decided it was good enough for me!

But now, I encountered my first real problem. I had only the total death number for each group for the whole year, but people switched from unvaccinated to vaccinated during the year! Nicely illustrated in this BBC image:

So how could I know how many were in each group at the time of death? I.e. the denominator for the mortality.

I never found a complete solution to this problem. But unless I'm thinking wrong somehow, this is the effect I believe it will have:

If death numbers were evenly distributed over the whole year, it wouldn't be a problem at all. I just calculate the average size of each group over the year, and divide the death number in that group with that number.

However, deaths in our northern countries tend to congregate around the winter months, especially in the higher age groups. Therefore, for those groups that got vaccinated right by the end of winter, the mortality would be underestimated for the vaccinated, as they would have an unproportionally large share of summer months in the year in question. For those groups that got vaccinated just before the next winter, mortality would be overestimated for the vaccinated, as they would have an unproportionally large share of winter months in the year, and for those who got vaccinated in the middle of the summer, the mortality would be about right, as they would have the correct winter to summer months ratio. The error would also be small in the lower age groups, as their few deaths tend to be rather evenly distributed over the year.

Thus, I calculated the average size of the different groups over the year, by age and vaccination status, and used this as the denominator for the mortality. I.e. the number 166 for example, for unvaccinated 40-49 year-olds, means the whole-year mortality for unvaccinated 40-49 year-olds was 166 deaths per 100,000 (N.B. per 100,000 unvaccinated, not per 100,000 in the whole group of 40-49 year-olds).

The second problem that I wasn't really able to solve was the lowest age group. For one thing, ONS lumps together a very large group there! 10-39, to compare with all the other groups which have only 10 years in each group. It would be interesting to know the benefits for 10-19 year-olds and for 20-29 year-olds separately, but we don't have this data. For the other thing, the vaccine uptake data - and therefore the population size data - starts with the age group 12-15 year-olds... Thus, I am comparing the deaths for the group 10-39 year-olds with the population size of 12-39 year-olds. If, again, I'm not mistaken, this means that the mortality would be overestimated among the unvaccinated in this age group... because all the people aged 10-11 would be unvaccinated. Therefore, the real denominator for the unvaccinated group is bigger than in my calculations, which would give a smaller real mortality. On the other hand, the real denominator for the vaccinated group would be the same as the one I've used - including 10-11 year-olds wouldn't make a difference to the number of vaccinated.

I did find another ONS estimate of the population size of the 10-39 year-old group, here:

https://www.ons.gov.uk/peoplepopulationandcommunity/populationandmigration/populationestimates/datasets/populationestimatesforukenglandandwalesscotlandandnorthernireland 

That is the mid-2020 estimate, they say. But if I sum up the groups from 10 to 39 there, I get 21,358,326, which is smaller than the value 23,691,079 I got from the UK Government graph on vaccine uptake!... How can the population be 10% smaller, when I include 5% more ages? Has the population really grown that much since mid-2020, to whenever the NIMS took their data from?

I decided, in any case, to stick with the NIMS data given by the gov.uk page on vaccine uptake. But I did check, and even using the smaller denominator of the ONS mid-2020 data, the mortality is still slightly lower in the unvaccinated group than in the vaccinated group for this age group; 29 per 100,000 instead of 28 per 100,000 for unvaccinated, to be compared with 30 per 100,000 in the vaccinated group. However, as stated above, the real denominator should reasonably be larger than the NIMS data, not smaller, as the NIMS data is for the age group 12-39, not 10-39 as it should be.

Finally, we can note that the vaccination coverage in the very lowest age groups is only around 60%. It is reasonable to assume that the vaccine coverage is higher in the high-risk groups within this age group, than in the age group at large. This would give a higher mortality for the vaccinated, without indicating that the vaccines are at fault, as the high-risk individuals would have had a higher mortality in any case.

Conclusions

Let me repeat the images again, so that we have them at hand:

The  data indicates that the COVID-19 vaccines have indeed saved lives. Mortality in England in 2021 was 30 - 60% lower in the vaccinated groups than in the unvaccinated groups for ages 40 and above, with a bigger difference the higher the age.

This made a huge difference in the higher age groups, where mortality was high. In the 40-49 group, on the other hand, the mortality was very low in both groups. (You hardly see them in the first graph.) The 30% relative reduction in this group therefore corresponds to an only 0.04 percentage units of absolute reduction. (From 166/100,000 to 122/100,000, i.e. from 0.166% to 0.122% = 0.044 percentage units.)

However, in the large group of 10-39 year-olds, the data indicates that the vaccines may have taken more lives than they have saved - mortality was 9% higher among vaccinated. It is worth noting that this is based on "only" 6,831 deaths, of which 4,181 among the unvaccinated and 2,650 among the vaccinated. The difference may therefore not even be significant, in which case the only correct conclusion we can draw is that it doesn't matter to mortality if you are vaccinated or not, in this age group.

An analysis of the error sources in this group, however, gives at hand that the final number might be even more to the disadvantage of the vaccines than the above. This is primarily because the death numbers were given for the age group 10-39, but the population number was given for the age group 12-39. Since none of the 10-11 year-olds would be vaccinated, all in this age group would be in the unvaccinated population, thus lowering the mortality (deaths per 100,000) for the unvaccinated group even further. However, it might also be the other way around, that the vaccines have greater advantages in this group than this data has shown, as the higher mortality among the vaccinated may be caused by more high-risk individuals in this group.

In any case, it is unlikely that we will ever find any large positive effect of vaccinating the younger age groups, except maybe for the high-risk individuals. This because the risk from the disease COVID-19 in this age group, as the mortalities above confirm, is very near 0, and thus can't very well be lowered much further.

Final words

In this analysis, I have only differed between "vaccinated" and "unvaccinated", where "vaccinated" includes anyone who has had at least one injection of COVID-19 vaccine. Even though the majority of those who have had at least one injection have also had two or three injections, the result might be different if we compare the mortalities for the groups with more than one injection. This could go in either direction, as the protection against COVID-19 would increase with more injections, but so would likely also the risk of side-effects, including death.

ONS also has data over people who died within 21 days of an injection. Also this data might reveal results that differ from the above, but I have not looked into that at this point.

Comments and inputs are most welcome! I'll also be happy to send you my Excel files where I've made my calculations, on request.