It turns out that no one does, not even academics! According to this devious but brilliant little paper published in the journal Complex Systems by Mikhail Simkin and Vwani Roychowdhury, researchers at UCLA who found an ingenious way [*] of estimating what fraction of academics actually read the papers they cite, the truth is that most “scholars” do not bother to read all the papers that they themselves cite in their published works. (Alas, the paper does not distinguish between tenured and untenured scholars. It would be interesting to measure which of these two groups of academics is engaged in greater amounts of scholarly deception.)
[*] Without getting into the technical details of their paper, suffice it to say that their method focuses on the distribution of misprints in citations.
Hat tips to xkcd for the cartoon and to Spartacus for taking me to Daniel Luzer.
A legislator in California, Mike Gatto (pictured below), recently set up the world’s first Wiki-bill in order to enable private citizens to act as cyber-legislators and help draft an actual law. According to Assemblyman Gatto:
Government has a responsibility to listen to the people and to enable everyone to be an active part of the legislative process. That’s why I’ve created this space for you to draft real legislation. Just like a Wikipedia entry, you can see what the current draft is, and propose minor or major edits. The marketplace of ideas will decide the final draft. We’re starting with a limited topic: probate. Almost everyone will face the prospect of working through the details of a deceased loved one’s finances and estate at some point during their life. I want to hear your ideas for how to make this process less burdensome.
Is this cool, or what? Perhaps in the future, we could expand this idea to create a streamlined system of “wiki-cases” — or “WikiJustice, the free dispute resolution system” — to enable people to act as cyber-judges and cyber-jurors and decide legal cases and controversies more directly, quickly, and accurately than under the current cumbersome legal system.
Yesterday, 1 January 2014, General Raul Castro (i.e. Cuba’s Pinochet) delivered yet another tedious and long-winded speech to commemorate the triumph of the Cuban Revolution. (Why are most revolutionaries, generally speaking, so much better at giving rousing speeches than respecting basic human rights?) You can read his dull and dreary speech (in Spanish) here, but why bother? It’s the same old tired rhetoric of yesteryear. But this remarkable event, the 55th anniversary of the Cuban Revolution, raises a larger and more important question. We Cubans are, for the most part, a strong-willed, independent-minded, and freedom-loving people, so how have Raul and his brother Fidel (like Mugabe in Zimbabwe) managed to stay in power for so long? When will Cuba be free and prosperous again (or at least prosperous)?
Put differently, what would a map of the USA look like if all the secession movements in US history had succeeded? This beautiful map [*], created by Andrew Shears, a professor of geography at Mansfield University, provides one possible to answer to this question. Thanks to digg.com and Chris Cillizza of the Washington Post for this whimsical pointer.
[*] Note: The State of Colorado is still pretty much in one piece on this map because Professor Shears’ counterfactual map covers secession movements up to the end of 2011.
According to this article in Wikipedia, there are only seven Mindball game sets in all of North America. (A Mindball game set is a medium-sized contraption consisting of a table, a small magnetized ping-pong type ball, and some electronic sensors capable of measuring one’s brainwaves. Check out the above video for a demonstration of this cool game.) My wife and I recently played a match of Mindball at one of these seven tables on the third floor of the Museum of Science and Industry in Tampa, Florida.
As you can see from the video, Mindball is fun and interactive, but it is also by far one of the strangest games I have ever played, for here is how it works: there are two players, one on each end of a table. Each player wears an electronic headband that is able to monitor the electrical activity in one’s brain. The player who produces the least amount of brainwaves (i.e. the player that is the “most relaxed”) wins the game!
What is so fascinating about this particular game is that it totally inverts the traditional emotional logic of most competitive or “zero sum” games, i.e. games where there is one winner for every loser. Most such zero-sum games tend to be do or die, adversarial and combative, generating intense negative emotions, which is not surprising considering the zero-sum nature of such games. (This is especially true, by the way, in civil and criminal litigation, or what I have referred to in my previous work as litigation games.)
In Mindball, by contrast, it is the most calm or relaxed player who wins, not the most aggressive or eager one, as is usually the case. This feature totally freaked me out as I was playing Mindball “against” my wife, creating a dizzy feeling of cognitive dissonance as I played.
Where does a game like Chess fit in this emotional spectrum?
Check out the website LOL My Thesis to find out. In brief, it’s what you get when you cross a formal academic dissertation with a cyberpunk format like Twitter. Here’s one example: “I thought there was a solution to invasive lionfish, but there isn’t.” [*]
Can you describe your favorite social science or humanities thesis in a single sentence or two?
[*] Footnote: As a quick aside, in the words of fellow blogger Handel, commenting on the micro-thesis posted above: “Replace ‘invasive lionfish’ with ‘X’, and if you elaborate you can describe nearly all post-enlightenment political history.” So true …
The holidays are a good time to reflect on one’s life, including one’s intellectual life. Here is a brief excerpt from my own self-reflections in my (as of yet unpublished) intellectual autobiography:
My intellectual life truly began during the summer of 1998, the year I left my law practice and began teaching. Like a modern-day Augustine, I emerged from the darkness of Plato’s cave and left behind my dull and dreary life of billable hours and corporate clients. But instead of converting to Christianity, Marxism, or some other dour dogma, I became a literary law professor and a devotee of mathematical models and science. But mind you, I didn’t start out this way. No one does. Before I entered the legal academy, the “Republic of Mathematics” and the sacred teachings of science were as foreign to me as the savannahs of East Africa or the steppes of Mongolia. This, then, is my story, the story of my madcap intellectual metamorphosis …
Read the rest of my “madcap intellectual metamorphosis” here.
How “inefficient” is Christmas and the tradition of gift-giving generally? According to this paper, The deadweight loss of Christmas, published in the prestigious American Economics Review 20 years ago this month (and from which the figure above is taken), holiday gift-giving destroys between 10 percent to one-third of the value of gifts. If you don’t feel like reading this classic paper for yourself, here is an overview from The Economist:
At the simplest level, giving gifts involves the giver thinking of something that the recipient would like—he tries to guess her preferences, as economists say—and then buying the gift and delivering it. Yet this guessing of preferences is no mean feat; indeed, it is often done badly. Every year, ties go unworn and books unread. And even if a gift is enjoyed, it may not be what the recipient would have bought had they spent the money themselves. Intrigued by this mismatch between wants and gifts, in 1993 Joel Waldfogel, then an economist at Yale University, sought to estimate the disparity in dollar terms. In a paper that has proved seminal in the literature on the issue, he asked students two questions at the end of a holiday season: first, estimate the total amount paid (by the givers) for all the holiday gifts you received; second, apart from the sentimental value of the items, if you did not have them, how much would you be willing to pay to get them? His results were gloomy: on average, a gift was valued by the recipient well below the price paid by the giver. The most conservative estimate put the average receiver’s valuation at 90% of the buying price. The missing 10% is what economists call a deadweight loss: a waste of resources that could be averted without making anyone worse off. In other words, if the giver gave the cash value of the purchase instead of the gift itself, the recipient could then buy what she really wants, and be better off for no extra cost.
While the general intuition of this paper might be correct (indeed, this is why we are big fans of gift cards and cash gifts generally), its methodology is of limited and doubtful value at best. Suffice it to say that data sets based on self-reported surveys are especially suspect. What are some other problems with Professor Waldfogel’s methodology? [Hint #1] [Hint #2]
Brian McGill, an ecologist at the University of Maine and fellow blogger at Dynamic Ecology, recently wrote (last June) a helpful overview and nuanced critique of Bayesian probability titled “Why saying you are a Bayesian is a low information statement“. We not only carefully read his well-reasoned post; like the good Bayesians we are, we also updated our epistemological priors accordingly …
Here, we wish to focus on a very, very good question that McGill poses midway through his June 2013 post. In brief, he asks why would anyone ever “favor serial updating of the probability distribution using repeated applications of Bayes theorem for each new data collection rather than performing a comprehensive meta-analysis on all data collected”? In other words, what’s so great about Bayesian updating?
That’s a great question. Does anyone have any answers?
For our part, this is our tentative take on McGill’s thought-provoking question. Broadly speaking, Bayesian probability is a way of updating one’s priors whenever one receives a new piece of evidence or new information. But, as McGill asks, why not wait until all one’s data is collected before one evaluates such data, just as juries must wait until the end of a case before they are allowed to evaluate the evidence presented by the parties? This question, however, neglects the flexibility and versatility of the Bayesian approach. Yes, there are some situations in which frequentist or traditional statistical methods can take the place of Bayesian methods (as McGill himself notes in his post), but the reverse is not true (something McGill fails to mention). Moreover, Bayesian reasoning is especially applicable not only to single-probability events (like political elections or competitive sports), but to any event with an uncertain outcome that occurs in real time, or when evidence and information are presented in a sequential manner. Jurors, for example, don’t really wait until the end of a case to evaluate the evidence. In reality, jurors are assessing the evidence and engaged in Bayesian reasoning from the start of trial.
