Category: Modern Veblen

Journalists and Scientists

Seth Roberts8 Comments

A few days ago I quoted an editor who works for Rupert Murdoch as saying that journalists care too much about impressing their colleagues and winning prizes and not enough about helping readers. Here is Walter Pincus, a Washington Post reporter, saying the same thing:

Editors have paid more attention to what gains them prestige among their journalistic peers than on subjects more related to the everyday lives of readers. For example, education affects everyone, yet I cannot name an outstanding American journalist on this subject.

I quote this to support the Veblenian view I’ve expressed many times on this blog — that scientists would rather do what gains them prestige among their peers than what helps the rest of us, who support most science. I think it’s hard to understand the success of my self-experimentation (e.g., new ways of losing weight) until you understand this aspect of science. I was successful partly because my motivation was different.

One Man Vs. All Education Professors

Seth Roberts16 Comments

According to a recent New York article about Rupert Murdoch, Robert Thomson, one of Murdoch’s top editors,

thinks most [journalists] are liberals overly concerned with writing stories that will impress other liberal journalists and win prizes in journalism competitions.

Well, yes. Not everyone is a liberal, of course, but basically everyone wants to impress their colleagues. Scientists have an amusing spin on this: They call it “peer review.” The amusing part is that somehow no one else’s opinion should matter. (E.g., all journals must be peer-reviewed.) Scientists get away with this bizarre view of economics (thinking someone should pay you and get nothing in return) perhaps because it is indeed difficult to assess the quality of this or that bit of science if you’re not in the field and because science has produced huge benefits for the rest of us in the past.

As I said, this is just human nature. As far as I can tell, professors act this way — try to impress colleagues — in every academic department. In schools of education, the result is this:

Amy Treadwell . . . received her master’s degree in education from DePaul University, a small private university in Chicago. . . . But when she walked into her first job, teaching first graders on the city’s South Side, she discovered a major shortcoming: She had no idea how to teach children to read. “I was certified and stamped with a mark of approval, and I couldn’t teach them the one thing they most needed to know how to do,” she told me.

It’s no secret that many schools of education do a poor job of training their students to teach — which is nominally one of their main goals. I am just repeating what Veblen said long ago.

What’s new is this: One man, Doug Lemov, working mostly alone, has figured out how to make people better teachers. One man. Not a professor. Did he build on the work of others? No, he started from scratch. He’s made a list of about 50 techniques. They are teachable. He gives workshops about them. As far as I can tell from this magazine article, Lemov has done a better job of figuring out how to train teachers than all the education professors in the world put together. If you arrived on earth from outer space, and didn’t understand human nature, you’d think this couldn’t possibly be true, but apparently it is. It’s like something out of a comic book.

Exploratory Versus Confirmatory Data Analysis?

Seth Roberts33 Comments

In 1977, John Tukey published a book called Exploratory Data Analysis. It introduced many new ways of analyzing data, all relatively simple. Most of the new ways involved plotting your data. A few involved transforming your data. Tukey’s broad point was that statisticians (taught by statistics professors) were missing a lot: Conventional statistics focussed too much on confirmatory data analysis (testing hypotheses) to the omission of exploratory data analysis — data analysis that might show you something new. Here are some tools to help you explore your data, Tukey was saying.

No question the new tools are useful. I have found great benefits from plotting and transforming my data. No question that conventional statistics textbooks place far too little emphasis on graphs and transformations. But I no longer agree with Tukey’s exploratory versus confirmatory distinction. The distinction that matters — at least to historians, if not to data analysts — is between low-status and high-status. A more accurate title of Tukey’s book would have been Low-Status Data Analysis. Exploratory data analysis already had a derogatory name: Descriptive data analysis. As in mere description. Graphs and transformations are low-status. They are low-status because graphs are common and transformations are easy. Anyone can make a graph or transform their data. I believe they were neglected for that reason. To show their high status, statistics professors focused their research and teaching on more difficult and esoteric stuff — like complicated regression. That the new stuff wasn’t terribly useful (compared to graphs and transformations) mattered little. Like all academics — like everyone — they cared enormously about showing high status. It was far more important to be impressive than to be useful. As Veblen showed, it might have helped that the new stuff wasn’t very useful. “Applied” science is lower status than “pure” science.

That most of what statistics professors have developed (and taught) is less useful than graphs and transformations strikes me as utterly clear. My explanation is that in statistics, just as in every other academic area I know about, desire to display status led to a lot of useless highly-visible work. (What Veblen called conspicuous waste.) Less visibly, it led to the best tools being neglected. Tukey saw the neglect –Â underdevelopment and underteaching of graphs, for example — but perhaps misdiagnosed the cause. Here’s why Tukey’s exploratory versus confirmatory distinction was misleading: Because the tools that Tukey promoted for exploration also improve confirmation. They are neglected everywhere. For example:

1. Graphs improve confirmatory data analysis. If you do a t test (or compute a p value in any way) but don’t make an associated graph, there is room for improvement. A graph will show whether the assumptions of the computation are reasonable. Often they aren’t.

2. Transformations improve confirmatory data analysis. That a good transformation will make the assumptions of the test more reasonable many people know. What few people seem to know is that a good transformation will make the statistical test more sensitive. If a difference exists, the test will be more likely to detect it. This is like increasing your sample size at no extra cost.

3. Exploratory data analysis is sometimes thought of as going beyond the question you started with to find other structure in the data — to explore your data. (Tukey saw it this way.) But to answer the question you started with as well as possible you should find all the structure in the data. Suppose my question is whether X has an effect. I should care whether Y and Z have an effect in order to (a) make my test of X more sensitive (by removing the effects of Y and Z) and (b) assess the generality of the effect of X (does it interact with Y or Z?).

Most statistics professors and their textbooks have neglected all uses of graphs and transformations, not just their exploratory uses. I used to think exploratory data analysis (and exploratory science more generally) needed different tools than confirmatory data analysis and confirmatory science. Now I don’t. A big simplification.

Exploration (generating new ideas) and confirmation (testing old ideas) are outputs of data analysis, not inputs. To explore your data and to test ideas you already have you should do exactly the same analysis. What’s good for one is good for the other.

Likewise, Freakonomics could have been titled Low-status Economics. That’s essentially what it was, the common theme. Levitt studied all sorts of things other economists thought were beneath them to study. That was Levitt’s real innovation — showing that these questions were neglected. Unsurprisingly, the general public, uninterested in the status of economists, found the work more interesting than high-status economics. I’m sensitive to this because my self-experimentation was extremely low-status. It was useful (low-status), cheap (low-status), small (low-status), and anyone could do it (extremely low status).

More Andrew Gelman comments. Robin Hanson comments.

Written With A Straight Face? Dept.

Seth Roberts18 Comments

Jonathan Cole used to be provost of Colombia University. He has written a book called T he Great American University, in which, according to this review,

He lists their dazzling achievements, which in biology and medicine include findings on gene-splicing, recombinant DNA, retroviruses, cancer therapies, coch­lear implants, the fetal ultrasound scanner, the hepatitis B vaccine, prions, stem cells, organ transplantation and even a treatment for head lice. . . . In a chapter on the social sciences, he cites, among many others, such useful innovations as theories of human capital and social mobility, research in linguistics and even the use of prices to reduce traffic jams.

“Research in linguistics”? Yes, that sounds dazzling. I’m sure those “theories of human capital” have been v v “useful”. And who would have thought that if you raise the price of something (“use of prices to reduce traffic jams”) . . . people use less of it? Which was traffic engineering, not social science. Did the reviewer, an economics professor at Harvard named Claudia Goldin, write this with a straight face?

The “dazzling achievements” in biology and medicine are only slightly less unconvincing.”Gene splicing” and “recombinant DNA” research are different names for the same thing. Fetal ultrasound scanners may cause autism. Vaccines were not invented by an American university professor. The discovery of prions has had no obvious non-laboratory use — besides being questionable. Stem-cell research has yet to produce anything of use outside of labs. To be fair, gene splicing has been used to produce human insulin, which is better than the insulin previously available, but conspicuously absent from the list of accomplishments is prevention of diabetes — not to mention allergies, obesity, depression, arthritis, stroke, or any of the other lifestyle problems that a large fraction of Americans suffer from. Such achievements would be truly useful. Great American universities haven’t given us any of those . . but they have given us a treatment for head lice.

There’s a reason for the term ivory tower. Apparently Cole, conscious of the term, is trying to argue against it — but merely shows why it exists. (I’m assuming the review is accurate.) It reminds me of the time that top Chinese students, visiting top American colleges such as Harvard and Yale, found the American students ignorant and arrogant. The theme of Cole’s book is that American universities are in trouble and need more support. What useful stuff they’ve accomplished is central to his argument. When I was an undergrad, I read Thorstein Veblen’s bitter The Higher Learning in America, which said American universities were dysfunctional. He mentioned “committees for the sifting of sawdust.”

More “Graduate school in the humanities is a trap” (via Marginal Revolution).

Assorted Links

Seth Roberts1 Comment

Thanks to Oskar Pearson and Dave Lull.

Insurance Group VP Questions Climate Science

Seth Roberts2 Comments

Science journalists, like other journalists, have a built-in problem: What they write affects the careers of the scientists they talk to. So those scientists are unlikely to be honest. No doubt most science journalists realize this but cannot say it, for fear of damaging their own careers. Dirty little secret is the phrase.

This is why, when Climategate happened, the many claims of climate scientists that the emails meant nothing themselves meant nothing. “The reason for the denial was the need for it,” Thorstein Veblen was fond of saying. What the climate scientists really thought they were unlikely to make public. The faux-horrified reactions of the few who made a living on the other side of the debate also meant nothing.

And this is why this reaction to Climategate, from Robert Detlefsen, an insurance industry group vice president, is meaningful: what he says will have no effect on his career. He is disinterested. And he makes some good points:

  • “The CRU e-mails show that a close-knit group of the world’s most influential climate scientists actively colluded to subvert the peer-review process [to prevent publication of disagreement]; manufactured pre-determined conclusions through the use of contrived analytic techniques; and discussed destroying data to avoid [FOIA] requests.”
  • He quotes from the Wegman report, which I hadn’t heard of. The Wegman report is by a group of statisticians. It says: “‘ independent studies’ may not be as independent as they might appear on the surface”. It also says that when climate scientists were asked to explain their work, “the sharing of research material, data and results was haphazardly and grudgingly done.”

He concludes that the science is less certain than has been claimed.

Chimamanda Adichie on Academia

Seth Roberts12 Comments

After a few years of being a writer, Chimamanda Adichie — author of my Short Story of the Year — wondered if she should be a professor. (Her father is a statistics professor.) And she wanted to learn more about Africa. So she enrolled in an African Studies program at Yale. In an interview, she said:

I met very lovely people at Yale, so it wasn’t an entire waste of time. . . . After two years of the program . . . academia I discovered — particularly political science as it is done in the US — is not about the real world. It’s about academia. I would joke and say that what they do is they create straw men, and they beat them down. While all this is going on, the real world is going on in a parallel universe. It is completely disconnected from what happens in academia. I didn’t understand most of what I read. It wasn’t written in English, it was written in political-science jargonese.

This is the usual critique, but it is well-put. If you spend enough time in academia, as I have, you can see it becoming that way, disciplines turning inward, becoming less and less interested in reality. Becoming more and more ivory-towerish. Statistics, for example, became less and less concerned with real-world problems; but I could say the same about every other area (engineering, English, etc.).

This is glaringly obvious, roughly as clear as the sun rising in the morning, but some Berkeley professors denied it. “English departments have really lost their way,” I would say. No they haven’t would be the reply.

eConspicuous Waste

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The term conspicuous consumption got more attention but Thorstein Veblen, in the same book, also coined the term conspicuous waste. The purpose of conspicuous consumption was conspicuous waste. Show how rich you are. Fine. So what do we do now, when driving a car with hood ornaments would make you look like an idiot rather than a rich person?

The creators of Paperless Post have not taken Veblen into account:

Paperless Post takes the e-invite into a civilized age, letting you design and send custom invitations and announcements expediently online. Created by siblings Alexa and James Hirschfeld, the site cleverly allows subscribers to choose among a dizzying array of card styles, fonts and design flourishes that perfectly mimic the heft and look of elegant stationary, complete with envelopes that open with a click. In addition to feeling good about your carbon footprint, you’re also easily able to monitor as recipients receive their invitations, and manage their replies.

Fancy invitations were an example of conspicuous waste. They were expensive. Everyone could see that. Here’s my suggestion: Sell these e-invites by the card and to each card add a donation to charity per card. Stated on the card. Let’s say the donation is $2. So 100 cards sent = $200 to some charity. That way the sender shows that he or she is rich.
Via Very Short List.

In Academia, High Status = Useless

Seth Roberts8 Comments

In a good article about what caused the financial crisis, John Cassidy quotes an economist:

During the past few decades, much economic research has “tended to be motivated by the internal logic, intellectual sunk capital and esthetic puzzles of established research programmes rather than by a powerful desire to understand how the economy works—let alone how the economy works during times of stress and financial instability,” notes Willem Buiter, a professor at the London School of Economics who has also served on the Bank of England’s Monetary Policy Committee.

It isn’t just “the past few decades” and it isn’t just “much economic research,” it’s all academia. Thorstein Veblen made this point a hundred years ago in The Theory of the Leisure Class. Academics show their high status by doing useless research. Useful research is low status. When, as a professor, you see this in your own department — the uselessness of what people do — you think surely other departments are different. They aren’t. As a Berkeley grad student in engineering said to me, “95% of what goes on in Cory [Hall — where her department is] will never be used.”

Easy versus Hard: Hunting, Agriculture, Etc.

Seth Roberts10 Comments

Coming across this sentence

The more intensive the agricultural system, the more work required for a unit of food.

in Charles Maisel’s The Emergence of Civilization (1990, p. 35) made me think for a while and make a list:

  1. Hunting: Easy.
  2. Agriculture: Hard. In agriculture you have to start from scratch in a way you don’t when hunting.
  3. Self-Experimentation: Easy.
  4. Ordinary Science: Hard. It is much harder to discover something useful via ordinary science than via self-experimentation.
  5. Fermentation: Easy. It is easy to make yogurt or kombucha, for example.
  6. Medical Drugs: Hard. Hard to invent, hard to make, hard to sell, hard to get, hard to afford, not to mention dangerous. It is much easier to cure/prevent problems by eating fermented foods, such as yogurt.

What’s interesting is the starkness of the differences. Hunting and agriculture are two answers to the same question. I suppose we backed into agriculture because we over-hunted. In the other two pairs, I think the basic Veblenian dynamic was/is at work: The more useless, the more high status. Scientists must be elaborately theoretical and high-techy and wasteful to be high-status. Likewise with home remedies (such as fermented food) versus medical drugs: To be high-status, doctors had to promote elaborate, obscure, hard-to-get remedies.