I’m going out on a limb a little, but, Miss Marple is perhaps as iconic a character as Hercule Poirot is. At least most of everyone who has heard of Poirot will have heard of Miss Marple. And while I think Poirot has been adapted into movies more often, Miss Marple might have been more influential. I can’t think of any other detectives who exist because of Poirot, but Murder, She Wrote would not have happened without Miss Marple.

Having said that, there can be no question of which one Agatha Christie wrote more of. There are something like three times as many Poirot stories as Miss Marple stories. Part of this, of course, is that Poirot had a seven year head-start. Those were seven very productive years for Agatha Christie, too—in addition to several Poirot novels, she wrote a great many short stories.

The subject of short stories is interesting, here, for while Poirot first appeared in a novel, Miss Marple first appeared in a short story. Most of the Miss Marple short stories were gathered together into the book The Thirteen Problems, and in the introduction to it—written years after most of the short stories themselves—Agatha Christie opines that Miss Marple is at her best in short stories, while Poirot demands novels. This is curious because she only wrote a few more Miss Marple short stories, while she had yet to write eleven of the twelve Miss Marple novels that she would ever write. This may, perhaps, be attributed to the changing economics of fiction. In the twenties and thirties the real money was in short stories; this was much less the case in the 1950s and 1960s. (I’m not sure how things were in the 1940s; television had not yet taken over from short stories as popular short entertainment but magazines and newspapers were hit hard by the war, especially since paper was in short supply.)

She also remarked in that introduction that Miss Marple was as popular as Poirot—she got about an equal number of letters requesting that she drop Poirot in favor of Miss Marple as requested that she drop Miss Marple in favor of Poirot. And here we come to one of the things that intrigues me about Miss Marple: it was twelve years between the first Miss Marple novel (The Body in the Vicarage, 1930) and the second (The Body in the Library, 1942). While the stories themselves were written (and published) between 1927 and 1930, the foreward to The Thirteen Problems was written in 1932. After declaring Miss Marple to be as popular as Poirot, it would be ten more years before she published another Miss Marple novel. And so far as I can tell looking at original publication dates, she only wrote three Miss Marple short stories in that time, one in 1939 (commissioned by the BBC as a radio play) and two in 1941. Two more would appear in 1942 after the publication of The Body in the Library, another in 1954, and the final Miss Marple short story in 1956.

I can’t help but wonder why it is that Agatha Christie thought that Miss Marple was better in short stories but after the first collection wrote her mostly in novels, and thought her as popular as Poirot but waited twelve years to write more of her.

That said, the wait did her no great harm. Miss Marple was always a creature from a previous age so she did not suffer greatly from how the world changed during and after the second world war—if anything, she felt less out of place after the war than before it. Young people in the 1920s and 1930s were concerned with being Modern in a way that only the hippies of the 1960s came close to. By the 1950s, people simply didn’t look down on their elders as they once did and Miss Marple’s Victorian girlhood was not the object of (indulgent) ridicule that it once was.

Which reminds me: I wonder if Agatha Christie, in writing Miss Marple, was at all inspired by G.K. Chesterton’s Father Brown. Certainly not entirely; she mentions inspiration from her own grandmother who had a sheltered Victorian upbringing and thought the worst of everyone. That said, the indulgent way that people assumed that Miss Marple knew nothing of the world is very reminiscent of the indulgent way that people assumed that Father Brown knew nothing of the world—and they had been assuming that of Father Brown for seventeen years by the time Miss Marple came on the scene. If so, she was inspired well.

But getting back to my main question, I wonder if it was merely that it was harder to come up with plots for Miss Marple stories than it was for Poirot stories. Miss Marple was a very different kind of sleuth and her stories (almost) always involved a great deal more investigation by people other than Miss Marple herself. It would be an exaggeration, but not too much of an exaggeration, to say that until the last few novels Miss Marple didn’t appear in the novels more than she did in the short stories, there was just a lot more of other people in the novels padding them out to full length. This means that the stories for Miss Marple require a setting in which amateurs (or ordinary policemen) can do the investigating and find the clues, but not understand them. This is not so easy to do. It is much more convenient for the author, especially of a novel, to have a detective who can look for clues that most people would not. Often this is unraveling the mystery of a red herring so that it can be set aside and further clues looked for, but it in any event helps.

This is also, I think, why Agatha Christie said that Miss Marple is at her best in short stories. Short stories allow there to be a summarizing of the evidence without much time to think about it, then Miss Marple can give her brilliant interpretation. If this is to be done in a novel, it’s trickier both to come up with a mystery which will last without anyone figuring it out, and also to come up with red herrings that don’t need to be cleared away for the right evidence to be discovered.

This is only speculation and I have little confidence that this is correct. Unfortunately, Agatha Christie says nothing on the subject in her autobiography, so I doubt that I’ll be able to advance much beyond speculation.

Something I hear a lot when it comes to the recent AI stuff like Stable Diffusion, Dall-E, chatGPT, etc. etc. etc. is some version of “this technology is just in its infancy, imagine what it will be able to do in a few years!” I’m not saying that these AI technologies won’t improve, but the thing is, it’s just not true that these technologies are in their infancy. These technologies are all developments of technologies which have been worked on for decades.

At their core, these approaches are various ways of doing massive quantities of massive matrix multiplications in order to encode the relationships between data. The T in chatGPT stands for “Transformer,” which is a variant of the previous types which had generally had some form of “neural” in the their name, such as Convolutional Neural Networks or Recurrent Neural Networks. In particular, Transformers (which were first mentioned publicly by a team at Google in 2017) replaced RNNs as the model of choice in natural language processing by being simpler and having the feature of being able to do the pre-training in parallel, which made vastly larger training data sets feasible.

Transformers were not a radically new idea that created a field which didn’t exist before; they were a new approach which was created because a large number of well funded smart people had been working in the field for a long time on relatively similar approaches. It’s an innovation which yielded noticeably better results, it might even be a breakthrough. What it’s not is the first dipping of humanity’s toe into something no one had ever done before. It may be the first supersonic flight; it is not the first flight at Kitty Hawk.

Moreover, the hardware to execute these things has been under development for a very long time. A huge breakthrough in performance came when the AI algorithms were adapted to run on GPUs (graphics processing units, the things that do all of the calculations for 3D graphics). This provided a relatively inexpensive source of incredibly high performance in number crunching that made the massive amount of processing involved in AI far more accessible. The thing is, this was like a decade ago. Since then special-purpose GPUs have been created to do the work even more cost-effectively (One I know of in the current generation of them is the nVidia A100 which costs around $10,000). But wait, there’s more!

Cerebras developed the Wafer Scale Engine—an AI processing chip the size of an entire silicon wafer—back in 2019. It’s an impressive piece of technology; it consumes about 22kW of electricity in a silicon wafer that’s 300mm in diameter (basically, 1 foot wide). It’s quite a technical achievement, but it went on sale back in 2019. There will be newer and better ones, to be sure, but it’s not a new idea with completely untapped potential.

Don’t get me wrong. I’m not saying that this is the end of technological development, or that AI won’t get any better. It would be outright shocking if there were no further improvements. My point is that the improvements that we’re going to see are most likely to be much slower than the people who don’t know anything about the history of AI development think it will be. We’re not at the very beginning of an exponential curve.

I do strongly suspect that generative AI is going to be useful, just as classificational AI has proven useful. The thing is, classificational AI has been with us for a while—it’s things like face unlock on phones and de-noising of video and audio and actually usable speech-to-text. It’s gotten better, and it continues to get better, but speaking as someone who develops technology: a technology becomes viable when it works all of the times for a use, not merely when it can do an impressive demo under favorable circumstances. And in the real world, edge cases are often 99% of the work and not being able to handle them often means that a tool is more work than it saves. The result is frequently a limited-use tool for cases which the new technology is good at, and it’s one more tool in the toolbox of a human being who can handle all the edge cases.

That’s why the result of all of the labor-saving devices is people being so busy all the time.

As Abraham Lincoln once said, the problem with internet quotations is that many of them are not genuine.

Sun Tzu, The Art of War

A while back I looked into a paper that described the actual mathematics/programming behind chatGPT (really, behind GPT3, which is basically the same thing but with a less sophisticated front-end). I find it interesting how often the thing is misunderstood.

ChatGPT is, as it will candidly tell you, a Large Language Model. That language part is very important. It does not model facts, or concepts; it has no understanding of anything. It does not try to have an understanding of anything. What it does is model language, but not in the way that grammarians model language. It models how language is used in practice. That is, it is a model of the sort of things that people actually say.

Without getting into the details of how the model works, it is enough to know that it was trained by taking in the appearance and order of words within approximately everything that the people at openAI were able to scrape off of the internet about two years before going public with chatGPT.

(This, btw, is the big improvement in chatGPT over previous large language models; the T stands for “transformer” and is a particular kind of use of matrices which allows the model to be “trained” in parallel, which allows for massively larger training sets than had previously been used in large language models. That said, its interesting to note that you can’t increase the training size to much larger than “approximately all of the text that has ever been written”, so on this basis alone we’d expect to see improvements in large language models slowing down after chatGPT because improved training is no longer an option. By contrast, this is not a problem for image-generating AI training. Generating massively larger numbers of images is quite straight forward.)

The output of chatGPT can loosely but accurately be described as “the words that the people who wrote the text chatGPT was trained on would probably say following whatever you said to it.” It doesn’t understand subjects and has no concept of what it is saying or the truth or falsity of what it is saying, it only has a concept of the probability of words appearing in an order on the basis of what words came earlier.

Like all modern “AI” stuff, the “AI” part takes input and produces output that a human being would not recognize as related to what the AI is being used for. Translating from a use case into the input of the AI model, and translating from its output back to the use case, is the work of programs written in normal programming languages that the programmers understand quite well. This front-end software is responsible for things like chatGPT being able to use references to previous subjects, or handle special cases like refusing to tell people how to commit crimes or adding a disclaimer to everything it says that is fitness-related that you should consult a doctor. They seem to be constantly adding more to this front-end, such as the ability to take instructions like, “write a sentence that ends in the word apple.” A language model only produces a set of words in order that are probable based on its training set; following directions is not related to this. Thus any amount of following directions is entirely in the front-end and consists of programmers looking at what kinds of instructions it’s been given and writing front-end code to handle those cases.

I’ve heard people say things like, “if they add the ability for it to check whether the things it is saying are true,” but no one has developed an AI which can identify what parts of a sentence constitute facts that could be checked. Consider a simple sentence like, “Mary, Queen of Scotts, once placed a bet on a game of tennis.”

What even are the facts that the sentence asserts? Let’s list them:

• A person named Mary exists (or perhaps is a fictional character in a published work)
• She was queen of the Scotts
• The Scotts are a people, specially who live in Scottland
• Scottland exists (or existed)
• There was at least one event at which this Mary made a bet
• That bet was on a game of tennis (anywhere)
• A game of tennis was played during the lifetime of Mary, Queen of Scotts

Some of these facts do imply others. For example: if Mary did in fact bet on a game of tennis, then it must be the case that a game of tennis was played during Mary’s lifetime. That is not necessarily the order you want to check them, though; it is common when fact checking to start with the easy-to-check facts.

There are complications, though. When we say “tennis” do we mean the medieval game played in an indoor court in which the walls (and some roofs) were in play, or do we mean “lawn tennis” which is the modern use of “tennis.” Is the sentence asserting something about Mary relating to the modern game of tennis, or only to the game which was more popularly played in her day and from which the modern game called “tennis” (more properly, “lawn tennis”) is derived?

ChatGPT doesn’t even begin to have anything within its model relevant to answering any of these questions.

Last Sunday’s reading at Mass was from the Gospel of John, and was the story about Jesus giving sight to the man born blind. Towards the end of the story, after the man born blind is questioned by the pharisees, he runs into Jesus, who asks the man whether he believes in the Son of Man. The man born blind asks a very interesting question: “Who is he, Sir, that I may believe in him?” (emphasis mine.)

It is interesting to contrast this with Pontius Pilate when Jesus said, “For this I was born and for this I came into the world: to testify to the truth. And those who are of the truth hear my voice.” Pilate’s response was, “Truth? What is truth?”

Jesus answered only one of these men, though they were, in a sense, asking the same question.

It’s interesting to contemplate why.

They were asking essentially the same question, but for opposite reasons. The man born blind was asking so that he may believe. A man cannot believe in something he does not know; faith is not the opposite of knowledge, but actually impossible without knowledge. The man who was born blind was willing to have faith, but he did not yet have the knowledge which would let him have faith, so he asked for it.

Pontius Pilate asked for knowledge in order to avoid believing in it. His question was not the seeking of truth but rather the denial of the possibility of attaining truth.

Despite what internet trolls will tell you, questions are not neutral things. We do not encounter questions floating in a vacuum. Questions always come from questioners, and questioners always have a goal in asking their questions.

As G.K. Chesterton said in Orthodoxy, motives matter:

But there is an anti-patriot who honestly angers honest men, and the explanation of him is, I think, what I have suggested: he is the uncandid candid friend; the man who says, “I am sorry to say we are ruined,” and is not sorry at all. And he may be said, without rhetoric, to be a traitor; for he is using that ugly knowledge which was allowed him to strengthen the army, to discourage people from joining it. Because he is allowed to be pessimistic as a military adviser he is being pessimistic as a recruiting sergeant. Just in the same way the pessimist (who is the cosmic anti-patriot) uses the freedom that life allows to her counsellors to lure away the people from her flag. Granted that he states only facts, it is still essential to know what are his emotions, what is his motive. It may be that twelve hundred men in Tottenham are down with smallpox; but we want to know whether this is stated by some great philosopher who wants to curse the gods, or only by some common clergyman who wants to help the men.

Back during the pandemic I did a number of posts looking at all-cause mortality in the USA. As a reminder, all-cause mortality is worth looking at because of the clarity of its definition. To give an example, if somebody has COPD and gets COVID-19 and dies, but probably wouldn’t have died if they only had one (then; COPD is eventually fatal), do you classify that as a COVID-19 death or a COPD death? Or as both? Different medical systems will reasonably differ on this question. (Then there are far less reasonable diagnostic criteria, like recording all deaths where a person had COVID-19 regardless of the cause of death.) This stuff can vary from hospital to hospital and state to state.

All-cause mortality data gets around these problems because, while it can be hard to agree on why a person died, it’s easy to agree on whether they died. Eventually. There is still the problem that it can take months for a death to actually be reported to the CDC. So much so that the CDC doesn’t even bother publishing all-cause mortality data for the most recently two weeks, and there’s very little point in looking at the last 3-6 weeks of data that they do publish. (They have algorithms that try to predict how many deaths will be reported eventually based on the data that has been reported so far, but it has a tendency to under-count what eventually gets reported.)

As I said, I put up several posts looking at this during the pandemic, and I recently became curious to look at it again now that the pandemic is in retrospect. So, here’s the data from the CDC as of February 20, 2023:

Let’s look at it a bit closer. To make the time frame of the data a little easier to follow, I’ve marked the approximate location of January 1 with yellow lines and the approximate location of July 1 with green lines:

If you’re curious, the Pfizer vaccine received emergency use authorization in December of 2020. The more infectious Delta variant of SARS-CoV-2 was named in March of 2021. The Delta variant had mutations in the spike protein which is how the virus enters cells as well as the thing that the vaccine gives the immune system to detect. This simultaneously made it better at entering cells, and also reduced the efficacy of the immune response acquired through vaccination or infection with the original variant.

Because I sometimes would look at Sweden’s data, here’s their COVID-19 deaths/day as reported by the Swedish government:

This data is in no way directly comparable to the all-cause mortality data above, but it is none-the-less interesting to note how, with the exception of Summer 2020, the spikes like up pretty well. It is widely theorized that the US’s summer spikes correspond to air-conditioning season in the southern united states, when people stay indoors during waking hours. To the best of my knowledge, Swedish summers are far more mild than are the summers in the American south, so one would expect them to be absent.

That hypothesis brings up an interesting question looking at the USA data, though: why was there no summer spike in 2021? There was a spike in deaths in the fall of 2021, not the summer. One explanation is that COVID-19 deaths started taking longer since the onset of infection to kill people (or at least to contribute to their death). If that is the case we would expect all subsequent spikes in deaths to also come later and, indeed, they do. The winter spike in deaths (in early 2022) also came later than the spike in the winter of 2020/ 2021.

If that is the case, why should it be? One hypothesis which covers these facts—though is in no way certain—is that later mutations of SARS-CoV-2 took much longer to kill people than the original ones did. Another hypothesis which would explain the delay is that the most vulnerable people were killed off in the first waves, and everyone who is left are less susceptible. (Though they are less susceptible, it can still contribute to their deaths when they are weakened by other diseases.) These are just two hypotheses; the truth could involve some version of either, both, or neither.

Of course, another explanation which covers this data is that the response to the increases in prevalence of SARS-CoV-2, or very technically, the response to increasing numbers of positive SARS-CoV-2 tests, was responsible for the increase in deaths. This will, of course, vary among the states as they had very different responses to COVID; some states like California were known for draconian measures, while other states imposed very few restrictions, and many were inbetween. It is reasonable to suppose that the extra stress of lockdowns, closure of businesses, etc. would have some negative effect. There are no actions without consequences and it would be absurd to suppose that drastic actions like the ones taken in response to COVID-19 are free.

For reasons relating to other data I’ve looked into but don’t have time to get into here, I am skeptical that this explains all of the increase in mortality over the years before COVID, but I haven’t seen any data to conclusively rule that possibility out. I am also a bit resistant to this explanation because it would be too convenient; I think that the responses to COVID-19, after the first few months, were wildly overblown and a massive overreach of government power. Lockdowns could be justified in the face of a pandemic of the magnitude of the Black Death—something that could kill off a third of the population in a short time. During the very early rapid spread of SARS-CoV-2 there were reasons to believe that SARS-CoV-2 was an escaped bio-weapon that could have been that kind of threat—the kind of threat which could potentially justify temporarily suspending all of the normal rules of society. After a few months it was obvious that SARS-CoV-2, escaped bio-weapon or not, was in no way another Black Death. Since I think that what ensued as an unjustified massive overreaction, it would be very convenient if SARS-CoV-2 was barely worse than a normal flu and most of the bad consequences of it were actually due to what I consider to be an overreaction.

I like to be careful of convenient conclusions, especially when conclusive evidence is intrinsically hard to come by.

Whatever the cause and whatever exactly happened, it does seem very clear that it’s over. A few people still wear masks, but few enough that they might all be immuno-compromised people for whom trying to filter the air that they breathe in public places makes sense anyway. We still have some lingering excess mortality, though only slightly. It was never all that high—this is more clear when you look on a multi-year timescale rather than zooming in—and it is very possible that the last few years were a perfect example of Alexander Pope’s line, “a little learning is a dangerous thing.”

We had tests to detect the SARS-CoV-2 virus, but we didn’t know how it spread, how bad it was, or how bad it would be. Thirty years before, without the tests to detect the virus, the entire experience might have been radically different. The absolute worst weeks had increases in mortality of about 40%, but a 40% increase in a small number is still small. Throughout everything, there were only a few cases of hospitals becoming so over-full that they had to send patients elsewhere and there were no (or at least statistically no) instances of people dying because of a lack of treatment because the hospitals were full. Without the PCR tests that could detect the virus without symptoms (or with symptoms that could be a cold or the flu), and thus allow us to map out its spread, we might not have done much more than think that there was a nasty flu for a few years.

I recently came across this interesting video on a quasi-scandal involving Samsung smartphone cameras taking better pictures of the moon than the physical camera elements actually allows:

The video brings up an interesting question about what the pictures that smartphones take actually are. In the video Marques proposes that the images that the smartphone generates are something along the lines of an image which is what the smartphone “thinks” you want the slice of reality you were trying to capture to look like.

It’s no secret that smartphones these days do massive amounts of processing on the photos that they take and that this goes way beyond removing noise and compensating for camera shake; for years now they’ve been actively recognizing the subject in front of them and adjusting focus, faking bokeh (the way in which subjects behind the focal plane are blurred), punching up colors, adjusting contrast in only some parts of the picture, etc. etc. etc.

There is a problem with this when it comes to taking pictures of the moon, though, because there is only one moon, we only ever see one part of it because it’s tidally locked to the earth, and we’re so far away from it that there is effectively only one angle to take the pictures from. In short, except for haze in the atmosphere or objects in front, there’s only one picture you can take of the moon.

Using AI to improve pictures of the moon is thus not easily distinguished from just replacing your picture with a better picture of the moon. It is different; the approach Samsung uses preserves whatever color in the moon you see due to haze in the atmosphere (a honey moon, a red moon, etc) and won’t override a cloud or bird in front of the moon when you take the picture. But if you’re not capturing weird lighting or something in front of the moon, a cleared-up version of your picture of the moon isn’t really different from just using a better picture instead.

Smartphones have been clearing up the pictures that they take for a long time now, and for the most part people don’t really object. (Every now and then when posting pictures of my superdwarf reticulated python to Instagram I have to note that the camera punched up the color, though it’s not a big deal because it’s what he looks like outdoors in sunlight, so it’s only a slight inaccuracy.)

It’s just weird that there happens to be a subject where you can only take one picture and so the AI image enhancement doesn’t need your original photo to present a clearer version of the photo you took. From what we can tell it does use your photo and doesn’t improve every photo of the moon to a pixel-perfect photo of the moon, but in some sense that’s just an implementation detail and imperfect photo enhancement, respectively.

Of course, the same thing that makes this a problem makes it purely academic; there’s no important reason to take photos of the moon because at best they look exactly like photos you can easily look up. And if you’re doing it for fun, you’re going to use a real camera not a smartphone camera.

It is an interesting academic problem, though.

This is, admittedly, very similar to a previous video, but this one is one hour long instead of two! And it covers how to keep an acquaintanceship ambiguous in order to create space for the two people to get to know each other without having to make rush judgements.

Some day I will break this into several videos by specific subjects, and with God’s grace they’ll be like 15 minutes each…

Or, in this case, Rat Trap:

Technically it’s really just a better rat-trap holder, but it’s very clever. If you ever have rodent problems, this is very much worth a watch. Also worth it if you enjoy seeing cleverness.

Not long after I graduated with my master’s degree in mathematics, I came across the song Finite Simple Group (of Order Two). It’s an a cappella love song that consists almost entirely of puns from graduate-level math.

The number of people who will get all of the jokes is substantially lower than the number of people who have PhDs in math, though getting a master’s degree will allow you to get many of the jokes, at least from having heard other students talking about classes you didn’t take. (For example, some of these come from differential geometry, which I never took, but heard people talking about.)

Even the name is a mathematical pun. A klein bottle is a mathematical manifold somewhat akin to a mobius strip, except you cannot create one in three dimensions without a self-intersection. It can be created without a self-intersection in four dimensional space, hence why four is associated with “klein”. (There appear to be five people in Klein Four, but this is something of an implementation detail.)

This video was uploaded to YouTube 16 years ago (as of the time of writing), which was several years after it was recorded. The website kleinfour.com doesn’t seem to exist anymore. (Last time I checked it, it said that the members of kleinfour had long ago got their PhDs and went on to be professors at different universities, so were not in a position to make more music.)

I find it interesting to look at it now, after so much time has passed. As I recall it came out roughly at the time that I was in grad school, and it felt incredibly relatable. Grad students in math do an enormous amount of work; it’s not even that they’re assigned so much as that they are there because they live and breath math. That creates a lot of pressure of its own, quite apart from grades and assignments (which create their own pressure), and so they sometimes need outlets where they do something else. I can remember late at night taking a break with some other grad students I was working with to do some experiments dropping paper helicopters down the area next to the central stairs and seeing what designs too the longest to reach the bottom. (Of the kinds we tried, it was spirals with a small central weight.)

This song is well done; it is composed well and the singer sings well. The puns were generally not strained. I had hoped that they would go on to do other things, but it was not to be. I have no idea whether the members of the group ever think about the Klein Four anymore; sometimes it’s easier to forget work that one has done than it is to forget art by someone else that one really appreciated. (Sometimes not.) The fact that no one has bothered to keep up the Klein Four website makes me suspect that all of its members have moved on.

If they have, though, there is still this video up on YouTube. Video has the curious property that it never changes. If you watch it a hundred times, it is the same moment in history, every time. You change as you watch it, of course, but I think that, properly considered, this gives a bit of insight into that strange aspect of how this life works. The past is real, but we cannot get at it, and yet it still matters. I believe it was Saint Augustine who first proposed the image of our existence being shattered over the moments of time and God, at the end of time, gathering up those shattered fragments and putting them together into a coherent whole.

Ironically, it is the past mattering that is why one should not dwell on the past. Because we will, after the end of days, be reunited with the past, we need to put our efforts into the present—because it will become part of that past that will eventually become an eternal present. That is, of course, harder to see when the goodness of the moment is less clear than it was at some of its clearest moments in the past, but that’s only a defect in our sight.

Another great Mitchell & Webb sketch:

I really love the confidence that this forger has. It reminds me of what Chesterton remarked on Orthodoxy:

Thoroughly worldly people never understand even the world; they rely altogether on a few cynical maxims which are not true. Once I remember walking with a prosperous publisher, who made a remark which I had often heard before; it is, indeed, almost a motto of the modern world. Yet I had heard it once too often, and I saw suddenly that there was nothing in it. The publisher said of somebody, “That man will get on; he believes in himself.” And I remember that as I lifted my head to listen, my eye caught an omnibus on which was written “Hanwell.” I said to him, “Shall I tell you where the men are who believe most in themselves? For I can tell you. I know of men who believe in themselves more colossally than Napoleon or Caesar. I know where flames the fixed star of certainty and success. I can guide you to the thrones of the Super-men. The men who really believe in themselves are all in lunatic asylums.” He said mildly that there were a good many men after all who believed in themselves and who were not in lunatic asylums. “Yes, there are,” I retorted, “and you of all men ought to know them. That drunken poet from whom you would not take a dreary tragedy, he believed in himself. That elderly minister with an epic from whom you were hiding in a back room, he believed in himself. If you consulted your business experience instead of your ugly individualistic philosophy, you would know that believing in himself is one of the commonest signs of a rotter. Actors who can’t act believe in themselves; and debtors who won’t pay. It would be much truer to say that a man will certainly fail, because he believes in himself. Complete self-confidence is not merely a sin; complete self-confidence is a weakness. Believing utterly in one’s self is a hysterical and superstitious belief like believing in Joanna Southcote: the man who has it has `Hanwell’ written on his face as plain as it is written on that omnibus.”

By the way, here’s Van Gogh’s Sunflowers, for comparison:

I think that the ten pund note was closer to the original.

I was recently reminded of the existence of trading cards, which of course calls to mind the scene in A Charlie Brown Christmas where Lucy asks whether Beethoven ever had his picture on a bubble gum card. This prompted me to look into the history of trading cards a little (i.e. on Wikipedia).

Trading cards as we know them today seem to have begun with cigarette manufacturers including trade cards in the packages of cigarettes. Trade cards were the business counterpart to calling cards—things you would give someone with your name and some information about you, including how to contact you, which you might leave if you called on someone and they weren’t home, or else as a means of introduction. Tradesmen would have cards for themselves in their professional capacity, and these might include instructions on how to find them (in the days before standardized addressing schemes). Businesses would also have similar cards for similar reasons, and cigarette companies started including theirs in the packages of cigarettes both to help protect the cigarettes (by stiffening the package) and also to help advertise their brand.

In 1875, the American tobacco company Allen & Ginter began to print pictures of more interesting things on the cards. According to Wikipedia these pictures were of, “actresses, baseball players, Native American chiefs, boxers, national flags, or wild animals.” In the UK, John Player & Sons introduced a series of cigarette cards called, “Castles and Abbeys.” People began to collect these cards and trade them to build up their collections, and the phenomenon quickly spread, with candy makers taking it up before long.

At approximately the same time, baseball cards were getting printed as trade cards. In the late 1800s baseball teams and players were posing for photographs, and these became available to things like sporting goods stores who used them as trade cards (interesting picture on one side, information about the store on the other). It would not be too long before these sorts of trade cards began to be included in cigarette packs and confectionery, and have information about the player rather than about a business on the obverse side.

If we distinguish trading cards from the broader set of collectible cards by whether or not there’s anything one can do with the cards such as play a game that the cards were designed for—the latter category including standard playing cards with 52 cards in 4 suits, Pokémon, Magic the Gathering, etc—trading cards had mostly disappeared from popular consciousness by the time I was a kid in the 1980s. I remember a brief fad for Garbage Pail Kids, but they were a joke and lasted about as long as one would expect a joke to last. (I don’t know if anyone collected them for even two years.)

I had a very minor baseball card collection, for about a year, almost entirely because I’d heard about how much money old baseball cards were worth and figured I might as well try in case they’d be worth anything in thirty years. That’s not much of a reason to pay money for things and then store them, though, which is why I quickly gave it up. I had never heard of anyone else collecting baseball cards even for that reason, and certainly not with any interest in the things for themselves.

Thinking about this made me wonder why anyone ever collected trading cards. The best that I can come up with is that it mostly makes sense as a pre-television and pre-color-magazine phenomenon.

Magazines began being printed in color in the late 1930s, so I expect that they were (approximately) all printed in color by the late 1940s. This would provide a common source of pictures that people could cut out and look at any time they wanted. Television only turned to color in the 1960s, but even black-and-white television provided many opportunities to see celebrities and sports stars for free. Prior to these things, though, how would a kid know what his favorite baseball players looked like? There were pictures in newspapers, of course, but that was a bit more haphazard and only turned to color in the late 1970s and I’m not sure when the quality of the photographs actually became decent.

To put it very simply, in the era when color photographs were not common, it makes sense that color photographs printed on cards might have been valuable. I don’t mean in the monetary sense that rare cards from people’s youths eventually were bought for large amounts of money, but rather in the simpler sense that people would actually want the things and spend some effort to collect them or trade them.

Of course, like most things that built up cultural inertia they would have continued to be made and collected for a while after they really made sense. If I’m right that trading cards stopped making sense in the late 1940s, then it seems possible that people might still be collecting them (in earnest) and talking about them into the 1960s, for Lucy to ask, in 1965, how can you say that someone is great who’s never had his picture on a bubblegum card?

Of course, this question of Lucy’s was written by adults, and moreover written as a joke. If it was an instance of adults thinking that kids still did what they themselves did when they were kids—it would not have been the first.

I was recently in a conversation discussing how people treat each other, and it came up that the big problem, these days, is that there is substantial disagreement as to what a human being even is. Ideally, the first question that a person should ask after “how should I treat this thing” is “what is it?” A person should treat a human being, a dog, and a cell phone differently because they are different things. So what, then, is a human being.

The Christian answer, from which one kind of answer about how to treat people follows, is that human beings are contingent beings created out of love by God so that he can give us more, and he put us in the same time and space so that we could take part in the act of creating each other (every time one gives food or knowledge or whatever to another, that is added to his being, and so one is becoming part of God’s act of creating him). Hence we should love other human beings, i.e. will their good for their sake.

The atheistic answer to “what is a human being?” is very different. The more accurate but less common answer is, “A joke with no punchline that no one has told.” or “A pointless illusion that no one is seeing.” More common, however, is to go with the creation myth of evolution (as distinct from the scientific theory of evolution, which doesn’t get enough attention): DNA wants to reproduce itself as much as possible and so it created us to do it. All that we call pleasure and happiness are just carrots that our blind and stupid master dangles in front of our faces to try to get us to do its idiot bidding. He were designed badly and will fall apart into nothing after a while. Fortunately for us, our master is blind, and we can sometimes trick him into giving us the carrots when we only pretend to pull his cart. Contraception is probably the best example of this; we can get the pleasure of reproduction without having to pay the price of reproducing.

So how should one treat human beings, if that’s what they are, and what happiness consists of? Being a human being oneself, obviously everyone else will either be a fool (in which case they are easy pickings) or will be trying to trick one into giving them pleasure without paying for it. So look out for the fools and try to trick them, while at the same time do your best to avoid being tricked by the people more clever than you.

And there you have modern dating in a nutshell.

I recently ran into an article on a study which compared the “Green Mediterranean Diet” with the Mediterranean diet and a “healthy diet”. The article begins

The green Mediterranean diet was pitted against the Mediterranean diet and a healthy diet in a large-scale clinical interventional trial- the DIRECT PLUS. Subsequent analysis found that the green Med diet reduced visceral fat by 14%, the Med diet by 7% and the healthy diet by 4.5%.

A bit later, we find out what the heck they mean by “green Mediterranean diet”:

The DIRECT-PLUS trial research team was the first to introduce the concept of the green-Mediterranean diet. This modified MED diet is further enriched with dietary polyphenols and lower in red/processed meat than the traditional healthy MED diet. On top of a daily intake of walnuts (28 grams), the participants consumed 3-4 cups of green tea/day and 100 grams (frozen cubes) of duckweed green shake/day. 

The first thing that jumps to mind is that the Mediterranean diet is popular among diet researchers because it is very low in red meat. How much lower could one make it? It is not plausible that a tiny amount of red meat causes enormous deleterious health effects since there’s obviously no corresponding dose-response to higher doses (people who eat a pound of red meat a day don’t die off at 15).

However that goes, worse is that this modification introduces three additional foods. This is the very opposite of controlling variables. Granted, the scientists in question probably think of it only as “introducing polyphenols”, but there’s a lot more in the foods they introduce than just polyphenols. Even worse, in terms of controlling variables, is that they are almost certainly not increasing the calories of the people on the diet, so they’re also going to be removing something or some things, introducing even more variables. You can tell that this is the case from the quote that they have from one of the professors who conducted the study (emphasis mine):

A healthy lifestyle is a strong basis for any weight loss program. We learned from the results of our experiment that the quality of food is no less important than the number of calories consumed and the goal today is to understand the mechanisms of various nutrients, for example, positive ones such as the polyphenols, and negative ones such as empty carbohydrates and processed red meat, on the pace of fat cell differentiation and their aggregation in the viscera

This strongly suggests that specific kinds of foods were removed from the diet at the same time that the polyphenols were added. That is really lousy variable control.

To be fair, it is possible to test many variables at once as a preliminary study to further, actually controlled studies, except that this isn’t a great way to do that unless you’re looking for something like an acute poison. If you design a study where on the one hand you test increasing protein intake and smoking cigarettes, and on the other hand reducing dietary trans-fats and moderate cocaine usage, who knows which group you’ll end up following up with, but either way you’re going to miss out on some important stuff.

Yet another variable in these kinds of studies is that they’re almost never free-feeding studies. By “free-feeding, I mean, “eat however much seems appropriate to you, of whatever food you’re hungry for/seems appropriate to you, whenever you’re hungry.” That is, free feeding is what normal people do. The number of people who actually weigh out all of their meals and eat according to some macro nutrient plan, every day of their lives, is approximately the number of bodybuilders there are. So we have yet another variable going on, which is that people who are watching their macro nutrient intake eat differently than people who don’t.

The reporting on this is also extremely lacking. For example, the summary at the top indicated a reduction in “red/processed meat”, while the professor who did the study referred to “processed red meat”. These are not the same things, and the top one is a much larger category. It includes fresh red meat and processed chicken, while the latter includes nothing that the former doesn’t too.

There’s also no mention of the limitations of the type of study performed. It’s an intervention study on 294 people (no indication if that was the starting or ending number) over 18 months. There’s no way that they had the money to keep the test subjects in a laboratory or hospital for all 18 months and strictly control all food given to them—not to mention, who would be willing to spend 18 months of their life under these conditions—so this had to have been an at-home study with self-reporting of compliance. Compliance rates for those are usually pretty bad, especially after the first month or two, and actual compliance as opposed to self-reported compliance is especially bad.

I’ve seen it argued that how difficult a diet (or other intervention) is to comply with is important, and this is certainly true. However, one of the things that affects compliance is the participant’s belief that compliance will reliably achieve something. Someone who wants to build muscle is far more likely to comply with a regimen of weight lifting because he is certain that if he complies, he will get the results he wants. An experimental method of muscle gain, where no one has any idea if it works, is far more psychologically difficult to comply with. Suppose one were to test out building muscle through twenty minutes a day of staring into the mirror and visualizing oneself with more muscle. Compliance with that will get difficult after the first day or two because there’s no obvious reason to keep going. (The flip side of this is that studies where one keeps participants in a lab and feeds them 100% of the food that they eat have phenomenal compliance, though higher drop-out rates, but they’re so expensive that in general they can only be run for 4-8 weeks and there’s very little of significance that one can find out in that short a span of time.)

The funding section is interesting, too:

This work was funded by grants from the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) – Project number 209933838- SFB 1052; the Rosetrees trust (grant A2623); Israel Ministry of Health grant 87472511; Israel Ministry of Science and Technology grant 3-13604; and the California Walnuts Commission.

None of the funding providers was involved in any stage of the design, conduct, or analysis of the study and they had no access to the study results before publication.

The California Walnuts Commission being one of the funders will, of course, sound alarms in the heads of the cynical or the conspiratorially minded. And, to be sure, the disclaimer that the funders of the study didn’t get to design it (etc) is no guarantee that the funders had no influence, because of course this isn’t the last study that the researchers are going to do and they will need funding again. By that same token, though, people who didn’t give a dime to this study may still have influenced the study by the researchers hoping to get funding from them next time. There is, as yet, no disclosure of funders who the researchers hope to get funding from in the future. All that said, it’s quite possible that the funding from the California Walnut Growers wasn’t that significant; they might well throw money at anyone who is trying to prove that walnuts are good for one’s health without overmuch worrying about the results of any one study. If you do fund enough studies looking into the health benefits of your product you’ll eventually get the favorable results you want by random chance, if nothing else, and this way your hands will be clean. It might even be cheaper, as it may potentially cost more to get someone with a decent reputation to falsify their results on purpose. But everyone makes mistakes.