# The Glorious Horror of TECO

In my oh-so-abundant free time, I’ve been working on my own little text editor. And one of my motivations is TECO: one of the oldest, and one of the very best, ever written. It’s both a text editor and a programming language – and, in fact, that’s exactly what made it such a brilliant tool. So much of the drudgery of programming is stuff that really could be done by a program. But we’ve spent so much time learning to be fancy that we’ve lost track of that. Nowadays, you can write an emacs lisp program to do the stuff you used to do in TECO; only it’s awkward enough that you usually don’t.

The problem, though, with just re-implementing TECO with a modern UI is that it was designed in a different time. When TECO was written, every byte was critical. And so the language, the syntax, the structure, it was completely ridiculous. And, as a result, it became the world’s most useful pathological programming language. It’s a glorious, hideous, wonderful, horrific piece of computing history

TECO is one of the most influential pieces of software ever written. If, by chance, you’ve ever heard of a little editor called “emacs”; well, that was originally a set of editor macros for TECO (EMACS = Editor MACroS). As a language, it’s both wonderful and awful. On the good side, The central concept of the language is wonderful: it’s a powerful language for processing text, which works by basically repeatedly finding text that matches some kind of pattern, taking some kind of action when it finds it, and then selecting the next pattern to look for. That’s a very natural, easy to understand way of writing programs to do text processing. On the bad side, it’s got the most god-awful hideous syntax ever imagined.

# Gender Bias, Sexism, and the Science Cheerleaders

My dear friend Sci seems to have stirred up a bit of a hornet’s nest by posting something less than entirely complimentary about the science cheerleaders. That sounds like a sarcastic way of saying that she wrote something taking them down – but actually it’s an accurate description of what she did. What she wrote wasn’t entirely negative or entirely positive. It was an honest, balanced assessment of just what she thought about the idea of the science cheerleaders and why they made her feel uncomfortable.

I think Sci’s assessment was dead-on. But over at Labspaces, there’s a whole discussion about it which has largely devolved into a bunch of people shouting at each other (complete with a sub-discussion about which dudes successfully banged hot but crazy smart chicks).

I don’t have much too say about the basic issue that hasn’t already been said. Personally, I’m very much behind Sci’s take on it. I’ve got a daughter who loves science, and I’d be very proud if she grows up to become a scientist; but I don’t like the message that I think the science cheerleaders actually deliver.

What I think gets missed in discussions like this is that there’s an awful lot of societal context that you need to consider in things like this. An awful lot of the criticism that’s been aimed at the people who aren’t thrilled with the science cheerleaders is, I think, based on ignoring that context.

We live is a highly patriarchal society. In our society, there is a constant message that men are important, and that women exist in order to serve men. A woman who isn’t attractive, who isn’t dressing in ways that show off her fuckability, is considered less valuable as a person.

This isn’t just an attitude of the misogynistic assholes in our society. This is an attitude of our society, reinforced virtually everywhere. It’s something that’s virtually impossible to avoid. No matter how much you think you’re better than that, that you don’t believe that you’re a sexist or a misogynist, you’ve still absorbed that message. Living in this society, it’s pretty much impossible to not absorb that message. Whether you’re a man or a woman, whether you’re young or old, whether you’re smart or stupid, whether you’re straight or gay, it doesn’t matter. This is a very deeply engrained attitude in our society, and you can’t avoid it.

I’m not saying this to insult men, or to insult women. But I am saying that if you deny that you’ve been influenced by the society you grew up in, if you deny that you’ve internalized the incredibly strong messages of sexual and gender roles that are such a part of your society, then you are fooling yourself.

Cheerleading is the most popular sport for young women in high school. There are thousands of girls who want to be cheerleaders, with huge competition for the few available spots. As a sport, it’s extremely demanding and difficult physically. It takes a tremendous amount of effort, practice, skill, and strength to be any good at it.

But what does a cheerleader actually do? What is their role as an athlete? It’s not to go out and win. Not even to compete. The primary role of a cheerleader is to support the male athletes. Cheerleaders are dressed up in impractical costumes – tiny skirts even in the coldest weather – and to dance, jump, and do all sorts of rythmic gymnastics while men are competing at the real sport. The women’s sport is very much subservient to the men’s, and the women’s sport is highly sexualized.

Even when you have co-ed cheerleading, you’ll find that the men typically wear long pants and a loose sweater, while the girls wear miniskirts and tight clinging, revealing tops.

In the male sports that have cheerleaders, the primary role of the male participants is to show off their strength and skill at the sport. The primary role of the chearleaders is to show how a group of attractive, fuckable women are supporting the talented male athletes.

This is basically the problem that many people have with the science cheerleaders. It isn’t that there’s anything intrinsically wrong with cheerleaders – but the societal context of cheerleading is that the cheerleaders aren’t part of the thing they cheer – they’re outsiders who support it by showing off how hot they are.

The “science cheerleaders” don’t actually cheer about science. They don’t show off their scientific skills. They don’t show that they know or care anything about science. Taken in the context of the society that they’re part of, and the traditional role and purpose of a cheerleader, they’re basically removing themselves from any role as an actual participant in science. Cheering isn’t part of the activity being cheered. A football cheerleader doesn’t play football; she supports the football player. A science cheerleader isn’t doing science; she’s supporting the scientists. And in our society, when you put together a group of hot women in hot costumes nad have them cheer about science, the basic message isn’t “Women can be interested in science” or “Women can be scientists”. It’s “science is cool, and you girls can support it by showing off how fuckable you are to all those smart science dudes”.

At best, what the science cheerleaders do is say “You can be interested in science and still be hot”. But put in context, that’s a very sad message: what it says is “As a woman, your primary responsibility is to be hot; you can be a scientist too, as long as you’re hot.”

Most people don’t want to think of themselves as being sexists or racists. Our self-image is that being a racist or a sexist is bad, and we’re not bad people. So we reject the idea that we’ve got these deeply ingrained racist and sexist attitudes. The problem is, we are sexists. We are racists. We’re not deliberately racist or sexist – but we all share the common context of our society, and it is ridiculous to pretend that we have somehow overcome that. And that causes some of the most pernicious problems of discrimination. The majority of discrimination today isn’t conscious and deliberate. It’s subconscious: it’s the attitudes and beliefs that we have internalized, which color our perceptions in ways we don’t even recognize.

I’ve done a lot of work recruiting, interviewing, and hiring people. And when you look at that, it becomes ridiculously obvious just how strong those subconscious biases are.

For example, in an experiment I’ve actually witnessed: Give a guy a bunch of resumes with names removed, and stripped of any content which could show the gender of the candidate, and they’ll pick out a bunch of resumes. If you look at the resulting selection, you’ll typically find that the number of women’s resumes who get selected are slightly above the proportion of women in the population. (This is another manifestation of sexism; in order to succeed, women need to be better than the corresponding male candidates; in a technical job, the average woman candidate will have better qualifications than the men she’s competing with, and in a blind resume search, that will result in the women being selected at a higher rate, because they have better qualifications.

Now, take the same batch of resumes, and an equivalent batch of screeners, but leave the names/gender identifiers on the resumes. You’ll get a dramatically different result. In the resulting pool of selected resumes, you’ll find that nearly all of the top male candidates from the initial round – better than 90% – were also selected in the open search. But of the women selected in the blind search, less that 20% will get selected in the open search.

And it’s not just men who do this. Use women as screeners, and you’ll see something similar. It’s not quite as as extreme – with women screeners in the open search, about 40% of the women from the blind search will also get selected. But still, the majority of women will be excluded, when the only additional piece of data is gender.

That’s the problem with the science cheerleaders. Not that there’s something wrong with cheering about science. Not because it’s impossible to be both a cheerleader and a scientist. The problem is that given our societal biases, the science cheerleaders play right into gender stereotype, and end up reinforcing the message that the primary role of women in science is sexual and supportive. You can be a female scientist – but if you are, it’s important that you do it in a way which shows your sexual subservience to the men. You can be a female scientist – as long as you’re also a hot chick who’s sexually available to male scientists.

As a closing point, before you start flaming me: just ask yourself, honestly: what would you think if a group of men dressed up in speedos and filmed a video cheering about science? Not doing any science – just dancing in their speedos chanting “science is cool.” In fact, can you even imagine a bunch of really great male scientists agreeing to dance in speedos while cheering?

# Thanksgiving Recipe: Mark's Cranberry Chutney

This is a repost of a recipe from last year. I just made this year’s batch, and I gotta say… this stuff is absolutely amazing. It’s so good that I can barely believe that I invented this, even though I know I did, because I was there.

Since I started doing my family’s thanksgiving dinner, I always made a simple cranberry relish – it’s the recipe that’s on the side of every bag of fresh cranberries – the cranberries, sugar, and oranges, into a food processor. The problem is, that really needs to sit for a couple of days, to let the flavors blend together, and to give the cranberry pectin a chance to thicken it. And last year, I completely forgot to do it in advance – on thanksgiving morning, I took the turkey out of the fridge, and saw my bag of cranberries.

So there was no time to let it sit. I figured I needed to do something else. What? Well, I love chutneys, and a good chutney sounded nice. I went hunting online for cranberry chutney. There were lots of recipes, but none of them appealed to me. So I said to hell with it, and ad-libbed.

The results were just delightful, and it’s become the new cranberry tradition in the Chu-Carroll household. It’s got fantastic balance: sweet, sour, spicy, and bitter all at the same time, in the right proportions to compliment the turkey.

# Grandiose Crackpottery Proves Pi=4

Someone recently sent me a link to a really terrific crank. This guy really takes the cake. Seriously, no joke, this guy is the most grandiose crank that I’ve ever seen, and I doubt that it’s possible to top him. He claims, among other things, to have:

1. Demonstrated that every mathematician since (and including) Euclid was wrong;
2. Corrected the problems with relativity;
3. Turned relativity into a unification theory by proving that magnetism is part of the relativistic gravitational field;
4. Shown that all of gravitational/orbital dynamics is completely, utterly wrong; and, last but not least:
5. proved that the one true correct value of $pi$ is exactly 4.

I’m going to focus on the last one – because it’s the simplest illustration of both his own comical insanity, of of the fundamental error underlying all of his rubbish.

# Obfuscatory Vaccination Math

Over at my friend Pal’s blog, in a discussion about vaccination, a commenter came up with the following in an argument against the value of vaccination:

Mathematical formula:

100% – % of population who are not/cannot be vaccinated – % of population who have been vaccinated but are not immune (1-effective rate)-% of population who have been vaccinated but immunity has waned – % of population who have become immune compromised-(any other variables an immunologist would know that I may not)

What vaccine preventable illnesses have the result of that formula above the necessary threshold to maintain herd immunity?

I don’t know if the population is still immune to Smallpox, but I would hope that that is just a science fiction question. Smallpox was eradicated, but that vaccine did have the highest number of adverse reaction (I’m sure PAL will correct me if that statement is wrong)

It’s a classic example of what I call obfuscatory mathematics: that is, it’s an attempt to use fake math in an attempt to intimidate people into believing that there’s a real argument, when in fact they’re just hiding behind the appearance of mathematics in order to avoid having to really make their argument. It’s a classic technique, frequently used by crackpots of all stripes.

It’s largely illegible, due to notation, punctuation, and general babble. That’s typical of obfuscatory math: the point isn’t to use math to be comprehensible, or to use formal reasoning; it’s to create an appearance of credibility. So let’s take that, and try to make it sort of readable.

What he wants to do is to take each group of people who, supposedly, aren’t protected by vaccines, and try to put together an argument about how it’s unlikely that vaccines can possibly create a large enough group of protected people to really provide herd immunity.

So, let’s consider the population of people. Per Chuck’s argument, we can consider the following subgroups:

• $u$ is the percentage of the population that does not get vaccinated, for whatever reason.
• $v$ is the percentage of people who got vaccinated; obviously equal to $1 - u$.
• $n$ is the percentage of people who were vaccinated, but who didn’t gain any immunity from their vaccination.
• $w$ is the percentage of people who were vaccinated, but whose immunity from the vaccine has worn off.
• $i$ is the percentage of people who were vaccinated, but who have for some reason become immune-compromised, and thus gain no immunity from the vaccine.

He’s arguing then, that the percentage of effectively vaccinated people is $1.0 - u - nv - wv - iv$. And he implies that there are other groups. Since herd immunity requires a very large part of the population to be immune to a disease, and there are so many groups of people who can’t be part of the immune population, then with so many people excluded, what’s the chance that we really have effective herd immunity to any disease?

There’s a whole lot wrong with this, ranging from the trivial to the moderately interesting. We’ll start with the trivial, and move on to the more interesting.

# Too Crazy to Be Fun: Pi Crackpottery

I always appreciate it when readers send me links to good crackpottery. But one of the big problems with a lot of the links that I get is that a lot of them are just too crazy. When you’ve got someone going off on a time-cube style rant, there’s just no good way to make fun of them – the stuff just doesn’t make enough sense to make fun of.

For example, someone sent me a really… interesting link recently, to a book by a guy who claims to have proved that $pi=3.125$. Let me quote the beginning of his book, to give you an idea of what I mean. I’ve attempted to reproduce the formatting as well as I can, but it’s frankly worse that I can figure out how to reproduce with HTML.

CONCEPTIONS OF π

One conception of π is the value 3.141… that is used for calculations, involving geometrical figures containing circles.

Another conception is that the number 3.141… is only an approximation. I interpret

π in this book as the relationship between a circle and its diameter, and not as the irrational number 3.141…

I have attempted to find a value that will result in exact calculations of circles.

SQUARING

The word “squaring” is used for the following:

A. The square with side of 4 u.l. so-called square squaring form

B. A circle with the diameter of 4 u.l., the circle squaring form

C. The only cylinder that has been produced by a square and two circles, from which come the cylinder squaring form

I identify the characteristics found in figures that I call square squaring, circle squaring and cylinder squaring and the principles behind these figures. I refer to three figures:

1. Square

2. Circle

3. Cylinder

It’s not particularly easy to make fun of that, because it’s so utterly and bizarrely nonsensical.

It’s pretty hard to get through his drek… But he’s got this way of characterizing different kinds of squares, and then different kinds of circles based on the different kinds of squares. The ways of characterizing the squares are based on screwing up units. There are three kinds of squares: squares where the number of length units in the perimeter are larger than the number of area units in the area; squares where the number of length units in the perimeter are smaller than the number of area units in the area; and squares where they’re equal.

That last group contains only one element: the square who’s sides have length 4. He concludes that this is a profoundly important square, and says that a square whose side-length is four of some unit is the “square squaring form” of the square. This is a really important idea to him: he goes out of his way to write a special note in extra large font:

N.B.

Squares with sides of 4 u.l. have a perimeter of 16 u.l. and an area of 16 u.a. Perimeter = 16 u.l. and area = 16 u.a. What I immediately observed was the common number for the perimeter and the area.

As you can see, we’re dealing with a real genius here.

From there, he launches into a description of circles. According to him, every circle is defined by a square, where the circle is inscribed in the square. It makes no sense at all; this section, I can’t even attempt to mock. It’s just so damned incoherent that it’s not even funny. The conclusion is that for magical reasons to be explained later, the circle with diameter 4 is special.

Then we get to the heart of the matter: what he calls “the circle squaring form”. This continues to make no sense. But it’s got some interesting typography. It starts with:

ln

of

the logarithm e

For no apparent reason. Then he goes on to start presenting the notation he’s going to use… And to call it insane is kind. In includes two distinct definitions: “Logarithm e = log e” and “Logarithm ln of e = log ln”. I have no clue what this is supposed to mean.

From there, he goes through a bunch of definitions, leading up to a set of purported equations describing the special circle related to the special square whose sides are 4 units long. What are the equations going to show us?

The formulae will define a circle that shows relation to;

• Its diameter to its circumference and area.
• Circles relation to its square.
• Its relation of the shaded area that is not covered by the
circle.
• Finally, how many per cent a circle cover its square’s
area and perimeter.
• Also relations to the cylinder.

So he gets to the equations, which are defined in terms of “ln of logarithm e”. His first equation, presented without explanation, is:

$Q = (ln sqrt{(e^{ln s})^2}/ln e^{ln s})^2/2$

What in the hell that’s supposed to mean, I don’t know. He doesn’t define Q. s is the length of the side of a square. Where eln s comes from, I have no idea… but he gets rid of it, replacing it with s. Apparently, this is supposed to be a meaningful step – we’re supposed to learn something really important from it! He goes through a bunch of steps, ending up with “Relevant Formula: ⇒ $4Q = ( ln sqrt{s^2 *2}/ln s)^2*2$“, which supposedly defines “the relationship between area, circumference, and diameter of a circle”.

I’ll stop here. I think by now you can see my problem. How can you make fun of this in an entertaining way? There’s just nothing that I can say about this stuff beyond “huh? what in the bloody hell is he trying to say here?”

He offers a cash prize to anyone who can prove him wrong. I think he’s pretty safe in not needing to worry about paying that prize out; you can’t prove that something nonsensical is wrong. Yeah, sure, π=3.2 or whatever in his universe: after all, for any statement S, $bot Rightarrow S$. Hell, $4Q = ( ln sqrt{s^2 *2}/ln s)^2*2$, therefore the moon is made of green cheese!

What kills me about this is how utterly, insanely, ridiculously wrong it is… My daughter, who is in fifth grade, did experiments last year in math class where they roll a circle along a piece of paper to get its diameter, and then compare that to its length. A bunch of fourth graders can easily do this accurately enough to show that the ratio of the circumference to the diameter is around 22/7. Any attempt to actually verify his number totally fails. But it would seem that in his world, when reality conflicts with theory, reality is the one that’s wrong.

# Fractals without a Computer!

This is really remarkably clever:

Since I can’t stand to just post a video without any explanation:

A fractal is a figure with a self-similar pattern. What that means is that there is some way of looking at it where a piece of it looks almost the same as the whole thing. In this video, what they’ve done is set up three screens, in a triangular pattern, and set them to display the input from a camera. When you point the camera at the screens, what you get is whatever the camera is seeing repeated three times in a triangular pattern – and since what’s on the screens is what’s being seen by the camera; and what’s seen by the camera is, after a bit of delay, what’s on the screens, you’re getting a self-similar system. If you watch, they’re able to manipulate it to get Julia fractals, Sierpinski triangles, and several other really famous fractals.

It’s very cool – partly because it looks neat, but also partly because it shows you something important about fractals. We tend to think of fractals in computational terms, because in general we generate fractal images using digital computers. But you don’t need to. Fractals are actually fascinatingly ubiquitous, and you can produce them in lots of different ways – not just digitally.