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Archive for the 'Academic Geekiness' Category

Every Time You Make A Powerpoint

This happens, although don’t click on that link unless you have some tolerance for dark humor.

Well, I think it’s funny, and I also think Edward Tufte’s stand on PowerPoint is interesting (if not news at this point):

Slideware may help speakers outline their talks, but convenience for the speaker can be punishing to both content and audience. The standard PowerPoint presentation elevates format over content, betraying an attitude of commercialism that turns everything into a sales pitch.

For example, here’s a scathing criticism of PowerPoint use in NASA:

I examine a key slide in the PP reports made while the Columbia was damaged but still flying….In the reports, every single text-slide uses bullet-outlines with 4-6 levels of hierarchy.  Then another multi-level list, another bureaucracy of bullets, starts afresh for a new slide.  How is it that each elaborate architecture of thought always fits exactly on one slide?

Anyway, to my knowledge, no animals were harmed in the creation of the first link.

h/t: Felix Salmon

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National Grammar Day

To the dismay of linguists everywhere, it is once again National Grammar Day. Yes, you read that right: dismay. As my colleague Gabe explains on his blog Motivated Grammar:

My problem with National Grammar Day (and most popular grammarians in general) is that it suggests that the best part of studying language is the heady rush of telling people that they shouldn’t say something. But if you really study language, you know that there’s so much more to it than that. Each time March 4th comes and goes, we’re missing an opportunity to show people how wonderful the field of linguistics is.

Gabe goes on to describe a couple of papers that got him interested in linguists, and then proceeds to celebrate National Grammar Day by debunking ten common myths about grammar. So rather than giving into the “better than thou” spirit of the day, go read Motivated Grammar and learn something new and inspiring about language.

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Mathematical non-games

The world of Algebraic Geometry (to which I have personal but absolutely no professional ties) is kind of tempest-tossed at the moment. I wouldn’t be suprised but what a number of you would enjoy thinking about and commenting on what’s going on.

In brief, lay terms, as I have heard it, there was this brilliant young French mathematician in the 1950s by the name of Alexandre Grothendieck who all but single-handedly revolutionized/created certain fields of Algebraic Geometry. Some 10-15 years later, he gave up academic life, moved to the Pyrrenées, and became a sheep farmer.

Since Grothendieck’s disengagement, his body of work has remained wildly useful and has formed a bedrock for later mathematical generations. The respect accorded to his own writings has gone so far as to inspire its own personal Distributed Proofreaders analogue for creating a TeX version of a long systematic work, “Séminaire de Géométrie Algébrique” (or SGA). The free electronic SGA project has been ongoing for the better part of a decade or more; volumes SGA 1 and SGA 2 are up on the arXiv already.

It seems just possible that might not be true much longer.

Behold the text of the until-recently-current webpage for the SGA 4 project:

Alexandre Grothendieck a malheureusement souhaité que cessent les travaux de réédition de SGA. Les pages qui étaient consacrées sont donc closes.
Dernière actualisation : 2 février 2010.

There is slightly more information, and much discussion, at Scott Morrison’s post on the Secret Blogging Seminar, a group math weblog. Again in brief (and English), Grothendieck apparently resurfaced enough to put out a letter stating that he doesn’t want his work republished or translated.

And he wags his finger at anyone who has done so or wants to.

Which is the really weird part. Assuming the letter is genuine, what legal ramifications does it actually have? Why use a phrase like “unlawful in my eyes,” which sounds to me deliberately obfuscatory? (Legality is not a matter of an individual’s vision.) The comments on the SBSeminar post seem weighted towards arguments as to the moral dimensions of Grothendieck’s stated wishes and a given mathematician’s obligation to respect them (or not). To me, the legal questions are more pressing and pertinent. Whether one has a moral obligation to respect an author’s wishes is a decision one makes for oneself. Whether the mathematical community as a whole has a legal obligation to take Grothendieck at his word has greater ramifications–and probably a single, findable answer (unlike a question of personal morality).

Edixhoven, one of the prior leaders of the TeX SGA project, did research the distribution question through the publishers and was told copyright had in fact reverted to the original authors (as he states on the linked page). This seems to indicate Grothendieck is not out of line to say he withholds his permission. But the questions only start there. …

Some on the SBSeminar comment thread made the “glass half full” suggestion that maybe it’s time SGA got a revamp anyhow. Yet the original is still a precious resource. I’ll be interested to try to follow what decisions are made.

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On Facebook and Twitter

danah boyd is a researcher specializing in social issues surrounding new technology, particularly social networking. In a recent blog post, she discusses differences in the cultures of Facebook and Twitter status updates. She points out that despite their superificial similarities, these two networks have different norms with respect to the directionality of communication:

Facebook’s social graph is undirected. What this means is that if I want to be Friends with you on Facebook, you have to agree that we are indeed Friends. Reciprocity is an essential cultural practice in Facebook… Twitter, on the other hand, is fundamentally set up to support directionality. I can follow you without you following me.

She goes on to discuss how these differences in directionality affect the way we present ourselves and the cultural norms that develop on these two different networking services. (Read the full post.)

I found it really interesting to read boyd’s analysis, as it matches up well with my own experience with the two sites, but in ways that I had never been consciously aware of. More generally, I’m really excited about the fact that people are taking social networking and other new media seriously as a subject for research. There is a tendency among some to dismiss these services as all the same, and as poor substitutes for “real” face-to-face interactions. In highlighting the ways in which social norms can develop around new media, boyd’s research also demonstrates the unique role that social networking can play in our lives–not replacing but rather augmenting our other forms of social interaction.

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HRSFAN achievement: Rush or Relax?

Jessica Hammer ’99 and her research team recently won a grant to design iPhone games that will help people stop smoking.  The grant speaks for itself:

The game is intended to be an alternative to smoking with the goal of reducing or eliminating tobacco use in players’ lives. The game involves breathing into a microphone to control gameplay, and is coupled with sound, color, images, challenges and feedback to mimic the stimulant and relaxant effects of smoking. The design elements within the game result in two modes of play (“Rush” and “Relax”). These will be tested for their stimulant and relaxation effects through emotional response and physiological (EEG, heart rate, galvanic skin response) measures, and compared to subjects after smoking or who play the game in lieu of smoking. If successful, the game will emulate the effects of smoking as a replacement therapy for smokers who want to quit. It will do so by allowing smokers who crave the physiological effects of smoking to reach for this five-minute game rather than for a cigarette.

I think it’s a great idea.  Although I also thought about this, and it creeped me out.  (Spoiler alert for that link, if you read beyond the first page or so.)

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Periodic Table

I wonder where I can get one of these? Using the lanthanoids and actinoids as a bench is quite clever. (Yes, I’ll admit, I did have to look up what those rows are called.)

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Khan Redux

You might remember earlier this year, Kevin Martin’s post about how many a’s people put in Khan. He also mentioned that one might fit an equation to the curve.

To a geeky statistician, those are dangerous words. Dangerously appealing words.

Before you continue, let me warn you: extreme geekitude follows; performing some analysis of this was like bringing an elephant gun to a squirrel hunt. A very geeky squirrel hunt (perhaps squirrel fishing). If you’d just like to see a graph of the final model, feel free to skip to the end.

So, the first thing we do is try to come up with a model for this curve. The basic idea is this: every time someone puts up a web page mentioning Kirk’s Khan scream, they have some number of a’s which they’re going to use. We consider that everyone has some number of a’s they tend to feel is appropriate, and that we are selecting from the population of people who put Khan scream references on the web. So we are modeling some underlying distribution of preference for a’s among these people.

Footnote: I also have to recognize that in addition to a distribution of preference over people, an individual person has some variation in how many a’s they actually put up; that there may be multiple populations of people; and that different kinds of people are more likely to add references to Khan on the web. Some may even post multiple times. While a more complex model which took this into account might be able to make a better fit to the data, we simply consider it all as combined into a single conditional distribution–given that the post was made, what is the probability of it including a certain number of a’s.

The first model is pretty basic: it says that after each ‘a’ is added, there’s a chance that you’ll stop, add an ‘n’, and be done. This probability is the same after each a–it’s not dependent on how many you’ve entered before. This results in the number of a’s being expected to follow a geometric distribution: each ‘a’ entered is a trial, and we continue adding a’s until we ‘succeed’ and add an ‘n’. On a log scale, this model is a straight line.

original geometric model

After seeing this (and a few other models), and doing a little web research, we remove the two leftmost points from the data for our model. These are ‘Khan’ and ‘Khaan’ (1 and 2 a’s). They are much higher than the rest, and substantially change the model. We suspect that their references are largely due to very different sources: anyone referring to Khan Noonien Singh himself (or Gengis Khan, or any other Khan) for the first, and anyone referring to Khaan (an actual animal and also a common alternative transliteration of Khan) for the second.

After we do this, we can see an improved fit, though there are clearly still some regions of higher- or lower-than-expected occurrences.

cleaned geometric model

So we now make our model a bit more complex, reflecting in part the complexity discussed above. We make a mixed model, suggesting that there are two populations posting Khan references. One follows the geometric model we used above; but the other, we will model as a negative binomial distribution: one explanation is that these are people who are aiming for a large number of a’s, and we are modeling their variation in what they think of as “a large number of a’s”. Fitting this mixed model (using maximum likelihood to determine how many people fall into each group, and the distribution parameters for each group) gives us the next graph.

mixed geometric/negative binomial model

A more complex model would attempt to model the conditional probability of adding another a (given how many a’s have already been added) as varying smoothly, depending on the number of a’s already added…we could, of course, model this as some sort of generalized additive model…sorry, please excuse my drool. Let’s continue.

Of course, I had to take it another couple of steps further. When I started this project, I wrote a perl script which would go to google each day and save the number of Google results for each search, stored in a file by date. Further, I extended the range to 125 a’s (anything longer than this, Google considers too long). So what we now have is a time series: for each day, we have an entire graph of values. Using this, I was hoping to see how the numbers change over time. Unfortunately, it appears that the results are not consistent over time, having significant variance up or down. Presumably, this is a result of Google trying out different variants on what results to return. But it means that rather than seeing counts increase over time, we see some variance in each count. For example, the counts for “khaaaaaaaaaaaaaaaaaaaaaaaaaan” (26 a’s) vary from around 150 to around 8000.

variance in counts of 26-a khan

You can see the variance overall by looking at a boxplot of the ranges for each number. For some reason, there’s a lot of variance for 5-34 A’s, but not too much outside of that range.

boxplot of counts over time

So, time series analysis is pretty much out; this is a shame, because you can pretty easily make a video of the counts on each day, over time (with a fitted model for each day). The trouble is that the counts are more affected by the algorithmic decisions google is making behind the scenes than by any underlying change in the number of pages.

movie of change over time

(click to see animation)

But we can at least try to use this variance to see if it smooths out any of our earlier outliers. Here, we’ll take the median reported values, over time, for each number of a’s (rather than the individual reported numbers on any specific day) and repeat the earlier geometric/negative binomial mixed model:

Final model: Mixed Geometric/Negative Binomial on median counts
mixed geometric/negative binomial fit to median counts

And that, I think, actually looks like a pretty decent fit. Notice that the negative binomial portion is actually fitting the low-A section now, rather than the strange middle-A hump we saw before; this seems to give a more natural interpretation: most people will put in around 6 A’s for KHAAAAAAN!, and for people stretching longer, a geometric distribution fits pretty well for determining how long they’ll keep adding A’s.

So there you go. Proof that anything can be overanalyzed. If people like this (drop a comment here or email me), I’ll keep collecting data and will look at doing some additional analysis with more data in a few months.

You can download the perl and R code and khan data from thomaslotze.com. While this was inspired directly by Kevin Martin’s post referencing squidnews, there were also earlier graphs from drtofu, Walrus, and Jim Finnis.

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Unscientific America and the popular image of science

I was intrigued but ultimately left unsatisfied by this article on Salon.com. Titled “Why America is flunking science”, the article takes on the question of why so many Americans don’t know basic facts about science. But rather than repeating the same tired claims about the uneducated masses, they consider instead the image of science presented by Hollywood and by scientists themselves. They walk through a number of examples (the well-researched but still implausible plot of Angels & Demons, Michael Crichton’s denial of global warming, the supposed link between vaccinations and autism) to demonstrate that the problem isn’t always a lack of education:

Consider vaccination. An army of aggrieved parents nationwide, likely spurred in part by Robert F. Kennedy Jr., swears today that vaccines are the reason their children developed autism, and they seem virtually impossible to convince otherwise. Scientific research has soundly refuted this contention, but every time a new study on the subject comes out, the parents and their supporters have a “scientific” answer that allows them to retain their beliefs. They get their information from the Internet, from other parents of like mind, from a few non-mainstream researchers and doctors who continue to challenge the scientific consensus, and perhaps most of all — as was much the case with Crichton and global warming — from a group of celebrities, most prominently Jenny McCarthy and Jim Carrey, who have made a cause of championing such misinformation and almost assuredly deeply believe in it.

Yet the parents who listen to McCarthy and Carrey — rather than the CDC and the FDA and the National Academy of Sciences’ Institute of Medicine — tend to be well-to-do and highly educated. Calling them “ignorant” is hardly accurate. After all, they’ve probably done far more independent research on a scientific topic that interests and affects them than most other Americans have. Like Crichton, they may be misusing their intelligence, but it’s not as though they don’t have any to begin with. Perhaps Mark Twain put it best: “The trouble with the world is not that people know too little, but that they know so many things that ain’t so.”

While I’m highly sympathetic to the take-home message that we should be paying more attention to the popular portrayal of science, I found the article incomplete in significant ways. Most importantly, I’m not convinced that the portrayal of science in Hollywood is as big a problem as they make it out to be. The spread of misinformation by celebritites, yes, certainly problematic. But to rail against the archetype of the mad scientist in fiction seems like an overreaction. The relation between this image of science, and the fact that even educated people are confused about science, seems more nuanced than the article presents. When we consider educated people who are being misled about scientific problems, isn’t the problem exactly that they do care about science but don’t know how to recognize reliable information? This is very different from the problem of avoiding science altogether because of unfavorable stereotypes.

While the article discusses some new institutions that are trying to tackle the image problem, it doesn’t give any concrete suggestions about what individual scientists can do to improve the image of science. Fortunately, the authors, Chris Mooney and Sheril Kirshenbaum, have just released a book, Unscientific America: How Scientific Illiteracy Threatens our Future, dealing with themes like those in this article. I’m very much looking forward to reading it.

If you’re interested in this topic, you might also want to follow Mooney and Kirshenbaum’s blog, The Intersection, where they are currently engaged in a high-profile debate with Pharyngula’s PZ Meyers.

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Ideas Worth Spreading

I expect that most of our readers are familiar with TEDTalks. The TED Conferences takes place annually and “bring together the world’s most fascinating thinkers and doers, who are challenged to give the talk of their lives (in 18 minutes).” Their talks are then published on their website, so that we mere mortals can experience them as well.

In the past I’ve mostly watched individual talks that others have pointed out to me, but today I took some time to explore the site and find things on my own. One of my discoveries was the “TED in 3 Minutes” series, which includes shorter talks. I particular liked “Arthur Benjamin’s formula for changing math education“. His idea, which I whole-heartedly agree with, is that high school math education should shift its focus away from calculus and onto statistics. Although calculus is integral (pun intended!) to higher math and sciences, most students will never need it. Probability theory, on the other hand, is immediately applicable to every student’s life. As we manage our finances or make medical decisions, it’s important for everyone to be able to intelligently assess risks and benefits.

To help spread all these ideas, the TEDTalks website has transcripts for all their videos. The transcripts allow the text of each talk to be searchable, and through the “interactive transcript” feature you can jump straight to the point in a video where given text appears. The “TED Open Translation Project” allows anyone to submit translations of these transcripts into other languages, to further spread these ideas beyond the English-speaking community.

With over 450 videos available, it’s difficult to know where to start watching TEDTalks. If you have a favorite talk or two, please let us know in the comments.

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Keep Libel Laws Out Of Science

Sense About Science, a UK-based science outreach organization, has launched a campaign to prevent British libel law from being used to stifle scientific debate. The direct motivation for this campaign was a lawsuit brought against Simon Singh by the British Chiropractic Association. Singh holds a PhD in physics and has written bestselling popular science books on a variety of topics. In April 2008, in conjunction with the publication of his book “Trick or Treatment? Alternative Medicine on Trial”, he wrote an article in The Guardian about the BCA’s claims that chiropractice can treat a variety of illnesses including asthma and ear infections. Singh denounces these claims as unsubstantiated and reckless.

The BCA’s response was not to provide any evidence for the efficacy of these treatments, but rather to sue Singh for libel. And this is not an isolated incident: British libel law has often been used to threaten journalists and other writers who aim to provide objective criticism of scientific or other topics. A variety of factors, including excessive costs and a “reverse burden of proof”, make such claims particularly difficult to defend against. (This article in the Wall Street Journal provides more details on the topic, including a discussion of how British law can threaten writers around the world, not just those in the UK.)

Although Singh’s situation is obviously upsetting, I’ve been impressed and heartened by the thoughtfulness and good spirit with which Singh and others have responded. Singh is fighting the libel case out of his own pocket: he explains in a statement that despite the immense financial risk, he finds the issue sufficiently important and feels a personal obligation to challenge this flawed system:

Moreover, the article was about an issue of public interest, namely childhood health and the effectiveness of particular treatments for some serious conditions. Hence, I was not prepared to apologise for an article that I still believed was important for parents to read, and which I believed was accurate and legally defensible.

The final reason for fighting on was that I knew that I was able to devote the time, money and energy required for a long legal battle. Most journalists would have been forced to back down and settle under the pressure of a libel threat, so it seemed that I had a duty to fight on in light of my privileged position. I knew when started, and I still know now, that this legal fight will be horrendously expensive and draining, but it will not destroy me.

Singh and Sense About Science have received an outpouring of support from the scientific community, and from science bloggers in particular. Within 24 hours, more than 2,000 people signed a statement published by Sense About Science calling for a reform of British libel law. In Singh’s statement, he writes touchingly about how grateful he is to the members of a facebook group created to support him, and to the numerous bloggers and journalists who have been following his case. Throughout, Singh has been admirably even-tempered, presenting his thoughts straightforwardly and without malice. Likewise, his supporters have been encouraging and optimistic, without being rude to those on the wrong side of the debate.

Despite the grief that Britain’s libel laws have caused Singh and others, I take heart in seeing how the scientific community has come together to productively oppose these unreasonable laws, how science blogging in particular has been used to quickly spread awareness of this issue, and how Singh himself has taken on the burden of standing up for productive scientific inquiry and debate.

free debate

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