Wired on Neal Stephenson: stop and smell the world-building

This month’s issue of Wired has a great profile of author Neal Stephenson, whose work I’ve just discovered this summer. Stephenson is a geek’s geek – his writing is detail-oriented without just piling on the facts, and his delight in both big ideas and puzzle-solving is palpable. He makes you want to cheer for rationalism.

His next novel, Anathem, is due out 9 September.

Magpie, know thyself

Photo by p_adermark.

New in PLoS Biology: European Magpies can recognize their own reflection in a mirror. Self-recognition in a mirror is used as a test of self-awareness in non-human animals, so this suggests that magpies, and maybe other birds, are conscious of themselves as separate from other members of their species.

To see if a magpie knew that a reflection in a mirror was an image of itself, the study’s authors glued a colored paper spot to the feathers below a magpie’s “chin”, then allowed the bird to see itself in a mirror. The magpie would have no way of seeing the spot except in the mirror, so if it reacted to the mirror image by trying to remove the mark from itself, it can be said to have recognized its own reflection. (And, presumably, thought something like “What the heck is this on my chin?”)

The supplementary materials for the paper include a number of videos of the test in action: here’s a magpie reaching for the mark with its foot [.wmv file], and here’s one using its beak [.wmv file]. Black spots, which wouldn’t be visible against the birds’ black chin-feathers, served as a control.

This is the first time that a non-mammal has been shown to be self-aware, and (in this one regard, anyway) it means magpies are smarter than monkeys. (Great apes recognize themselves in mirror tests; monkeys don’t.) It’s also more evidence that what we think of as consciousness, that nebulous quality that separates humans from the rest of the animal kingdom, isn’t as clear-cut as we used to think. Human intelligence most likely evolved by the incremental assembly of different mental skills – including self-awareness, but also tool use and language – that we see in other smart animals.


Helmut Prior, Ariane Schwarz, Onur Güntürkün, Frans de Waal (2008). Mirror-Induced Behavior in the Magpie (Pica pica): Evidence of Self-Recognition PLoS Biology, 6 (8) DOI: 10.1371/journal.pbio.0060202

A sidelong look at the 2008 games

Photo by carinasuyin.

New Yorker film critic Anthony Lane reports on the first week of the Beijing Olympics. The result is snidely wonderful:

“The world has given its love and trust to China, and today China will give the world a big warm hug,” one of the masters of ceremonies said. While admiring their faultless English, you had to wonder why they had chosen to learn it by watching “Barney’s Great Adventure.” How, in less than twenty years, does a place go from mowing down student dissent with tanks to offering unconditional hugs?

Phelps vs Spitz: z-scores tell all

So, yesterday I suggested that, given improvements in training and equipment, Olympic athletes of today should be compared to those of the past using z-scores, rather than raw performance data. This was specifically with reference to comparing swimmer Michael Phelps and the historical performance of Mark Spitz, but I couldn’t find enough data from Spitz’s events in the 1972 Olympics to calculate the standardized z-scores.

(For those just joining us, z-scores use information about a distribution of data points to calculate a “universal” measure of how much one point stands out from the rest – in this case, how much Spitz or Phelps stands out from those among contemporary swimmers.)

Anyway: after another round of digging on Google, I’ve found detailed results (i.e., the final times for the top eight competitors) for the men’s 200-meter butterfly in 2008 and 1972. To convert Phelps’s and Spitz’s times to z-scores, I estimated the parameters of a distribution from the other seven men in the top eight by by taking the average (arithmetic mean) and standard deviation of those times in good ol’ Microsoft Excel [.xls file]. The z-score is just the difference between a single score and the average, divided by the standard deviation.

And …

Spitz wins! His z-score is -3.67, compared to -2.27 for Phelps. (The numbers are negative because the times are, of course, lower than the average from the other seven.) So, even though Phelps is considerably faster than Spitz, Spitz outperformed his competition by a greater margin than Phelps did.

Michael Phelps is fast, but what’s his z-score?

Even without following the Olympics in any detail, it’s hard not to hear about the success of U.S. swimmer Michael Phelps: a new record for career gold medals won by an athlete in any sport, and new time records for just about every race he swims.

Figure 1: Michael Phelps

Photo by sagicel.

But what do these records mean? Over on Slate, William Saletan lists a whole bunch of advantages Phelps has over past Olympic swimmers, including the high-tech LZR swimsuits, but also things like greater pool depth. All of which makes it hard to directly compare race times achieved by swimmers in the 2008 games and those achieved by past swimmers. Including those who set the records that Phelps keeps breaking.

Saletan suggests an “Olympic inflation index” based on the year-to-year improvements in athletes’ average performance; the New York Times devotes a whole article and an animated infographic to comparing Phelps to the great American swimmer Mark Spitz. But there’s a better option, proposed years ago by none other than Stephen Jay Gould: compare not the raw performance metrics, but z-scores. A z-score is how much an individual measurement differs from the mean of a group of measurements, divided by the standard deviation of the group. Converting raw performance measurements to z-scores gives us a standardized measure of how much an athlete’s performance stands out from that of his competitors. Gould applied this to batting averages, but it’s easy to do with any set of sports scores. For instance, here’s a scholarly article that does it with basketball results [$-a].

Unfortunately, I can’t make that comparison for Phelps and Spitz. In order to calculate a z-score, you need a reasonable sample size – say, at least five (and that’s if you make some assumptions about the way those scores are distributed). While the New York Times website lists the times for the top eight men in (e.g.) the 200m butterfly at Beijing 2008, I haven’t been able to dig up comparable data for Mark Spitz’s victory in the same event at Munich 1972 – or for any other event, either. Kind of a downer, I know – but I’m going to keep digging around for the data. If anyone has a lead, feel free to comment.

Edit: I found the data! Results in a new post.


Chatterjee, S, Yilmaz, MR (1999). The NBA as an Evolving Multivariate System. The American Statistician, 53, 257-262

How I spent my Summer Vacation

I’m back from time with the family in Bar Harbor and Acadia National Park, plus an afternoon at the New England Aquarium and a weekend visiting an old high school buddy in Chicago. It was good, at least until the flight home, which was canceled. (I got home only a day late, but my luggage still hasn’t caught up.) Highlights: climbing Dorr Mountain, whale (and bird) watching, visiting the Field Museum and the Lincoln Park Zoo in Chicago. Much bio-geeking, but nothing work-related. Although it turns out that the Field Museum has a fishbowl genetics lab in the middle of one exhibit, where you can watch actual scientists do basically what I do all day. Kinda creepy. Anyway, time for photos:

Photo by Jeremy B. Yoder.

Photo by Jeremy B. Yoder.

Photo by Jeremy B. Yoder.

Photo by Jeremy B. Yoder.

Photo by Jeremy B. Yoder.

Photo by Jeremy B. Yoder.

Airplane reading

Whilst on vacation, (among other things) I’m working on Neal Stephenson’s Cryptonomicon. I’m not done yet, but I’m prepared to give a very positive review. Cryptonomicon doesn’t achieve the same transcendently nerdy joy at the details of history and science that characterize Stephenson’s Baroque Cycle, but it comes close. And in some regards it’s better – parts of Cryptonomicon recall Douglas Adams’s unique talent for screwing with the reader’s perspective. Like this introductory passage:

Let’s set the existence-of-God issue aside for a later volume, and just stipulate that in some way, self-replicating organisms came into existence on this planet and immediately began trying to get rid of each other, either by spamming their environments with rough copies of themselves, or by more direct means which hardly need to be belabored. Most of them failed, and their genetic legacy was erased from the universe forever, but a few found some way to survive and to propagate. After about three billion years of this sometimes zany, frequently tedious fugue of carnality and carnage, Godfrey Waterhouse IV was born, in Murdo, South Dakota, to Blanche, the wife of a Congregationalist preacher named Bunyan Waterhouse. …

As nightmarishly lethal, memetically programmed death-machines went, these were the nicest you could ever hope to meet.

There’s also a wonderful bit where Stephenson explains a mathematical concept using Alan Turing’s malfunctioning bicycle as a metaphor. Clearly targeted squarely at those of us who never missed “Square One TV” when it was on the air. Which would include me.

Gone out. Back soon?

Getting up early tomorrow to fly east for a week of vacation with family: Bar Harbor, Maine, Acadia National Park, some whale watching, maybe Boston, maybe a jaunt north of the border. No idea what my Internet access will be like, and I’m inclined to think it wouldn’t be so bad if I didn’t have it. I’ve earned it; I got a manuscript submitted Thursday that I’ve been futzing around with for way too long.

I fully expect to take lots of photos like this:

Photo by Pear Biter.
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