Wednesday, February 29, 2012

Reading the New York Times in Stata

One useful command for taking a break from research is Neal Caren's "nytimes" ado file. This command lists the most recent headlines with brief summaries from the New York Times. Best of all, no subscription is required!

Tuesday, February 28, 2012

Utility Theory as Naive Cultural Theory

Here's a fascinating presentation by the economist Steve Keen on utility theory and neoclassical economics. From the perspective of a cultural sociologist, what is of particular interest is that the utility theory underlying neoclassical economics has the appearance of a naive cultural theory. Specifically, the indifference curves that constitute supply and demand curves in neoclassical analysis are based on strong, disproved assumptions about how people value things in the world: first, completeness (i.e., that the individual knows their evaluative ranking of all combinations of things); second, transitivity (i.e., if thing A is valued to B, and B to C, then A is valued over C); third, non-satiation (i.e., more things are always valued to less); fourth, convexity (i.e., for each thing, additional value falls); fifth, structural independence from culture (i.e., what an individual values is independent of how much income the have); finally, no curse of dimensionality (i.e., information processing abilities are unlimited). No cultural theory  in sociology has even approached the disbelief required for these kinds of assumptions. Fortunately, some sociologists (for example Michael Hechter), have sought to correct this naive cultural theory, and have advocated eloquently and convincingly for a richer understanding of values in economic models of human behavior.

Monday, February 27, 2012

The Phil Gramm Effect

I recently re-read Andrew Abbott's brilliant article on the problems with classical linear regression. One of the most persuasive criticisms is that statistical models are extremely difficult to use for examining small changes with big effects (but big changes with small effects can be modeled). I like to call this the "Phil Gramm Effect" because arguably one of the most important causes of the 2008 financial crisis (an undoubtedly big effect) was Phil Gramm (a small change), since he was the driving force for gutting the Glass-Steagall Act and shifting government regulations in favor of private companies (often called "deregulation," but more accurately termed "re-regulation").

Sunday, February 26, 2012

Big Science in Sociology

The search for the Higgs Boson particle has captivated a wide range of people all over the world, and the construction of the Large Hadron Collider is the reason for this widespread interest. Is such a "big science" approach possible in the social sciences, including sociology? Although the details to me seem obscure, researchers in Europe have developed a proposal for what they call the FuturICT, a "big science" project for the social sciences (ICT stands for "Information and Communication Technology") in the mode of the Manhattan Project, Apollo Project, and Large Hadron Collider. But what is it, exactly, that they are proposing? I get the sense it's a giant computer simulation, but it doesn't seem entirely clear.

Saturday, February 25, 2012

Social Learning is Efficient

I encountered this clever article by several social scientists, including the cultural anthropologist Rob Boyd. Through various data, they show that it is beneficial to copy others (i.e., engage in social learning) rather than innovate by oneself. This highlights clearly the fiction of the "self-made" man, and the importance of one's cultural and social environment in leading to human flourishing.

Friday, February 24, 2012

3-D Bar Graph "Masterpiece"

I encountered this post on how to turn a "boring" bar graph into a 3-D "masterpiece." What's striking to me is that most of the people commenting actually want to replicate this graph, even though it violates the basic principles of effective statistical graphics, according to Tufte and others. For example, the 3-D effect distorts the information displayed by the "boring" bar graph, making comparisons difficult, and the visualization effects distract from the underlying data as conveyed by the differing heights of the bars. Here's the "masterpiece" in its full glory:

Thursday, February 23, 2012

Violin Plots

Violin plots are an excellent way of displaying the distribution of a continuous variable by levels of a categorical variable. In essence, violin plots are box plots and kernel density plots combined. For instance, here are a set of violin plots from Stata's auto data:

These same data could also be displayed in tabular form, but again this is case in which a graphical display is a more effective way to examine and convey the patterns in the data.

Wednesday, February 22, 2012

Big Data and the End of Theory?

An article in The Guardian gives appropriate caution to claims that data analysis (and only data analysis) is the solution for all or even most academic and research problems. As Max Weber observed in  his brilliant essay on objectivity in the social sciences, even the process of data analysis depends on values that cannot be empirically proven as right or wrong: "The 'objectivity' of the social sciences depends [..] on the fact that the empirical data are always related to those value-ideas which alone make them worth knowing and the significance of the empirical data is derived from these value-ideas. But these data can never become the foundation for the empirically impossible proof of the validity of the value-ideas."

Saturday, February 11, 2012

Era of Big Data

The New York Times has a great article discussing the era of big data. This might have a Kurzweil-esque ring to it, but due to technology change big data is becoming increasingly available and ready for analysis: in fact, there are more data sets out there than brains to analyze them, especially when one notes the incredible number of combinations of analyses that could be conducted even on a single data set with 100 variables (in what is known as the curse of dimensionality). However, one problem with big data is that, since so much of the data are collected by private entities, much of it may not be available to academics and independent researchers.

Thursday, February 02, 2012

Theory of Everything?

A new journal in biology called Life has published an unusual article in its inaugural edition: a paper by Erik Andrulis titled the "Theory of the Origin, Evolution, and Nature of Life." You can find the paper here. At 105 pages and 800 references, his paper seems Sokal-like, except it apparently is not a hoax at all. As a result this paper is unusual, but especially so for two reasons: first, Andrulis is apparently a well-respected biological scientist who has done important work on RNA, and second, Life appears to have all the trappings of a well-respected, peer-reviewed scientific journal, including a well-respected editorial board.

In essence, Andrulis outlines a theoretical framework  that (supposedly) unifies the microcosmic and macrocosmic realms, validates predicted laws of nature, and explains the origin and evolution of cellular life. Like most non-biologists encountering this paper, I've only skimmed it, but apparently reality consists of geometric entities "gyres." Sounds good, except Andrulis provides no evidence (as far as I can tell) that these gyres exist.

It's easy to criticize this paper, if only for ambition of his theory. In one section he purports to unify all laws of nature, while in another he addresses the meaning of life. Even more astounding is the offhand way he presents his theory. For example, on page 55, Andrulis briefly remarks: "Please note the unity of reality and life as revealed by this theory." Can the unity of reality even be "noted"? However, my favorite part of the paper is on page 61, simply because of the sheer grandiosity of his assertion: "I refer the reader to the Theory section for a complete presentation of theoretical answers to many of science’s most challenging questions."

Questions abound how this paper was published despite peer review (perhaps it was a publicity stunt for the journal), and about the sanity of Erik Andrulis. From the position of a sociologist of culture, however, the more interesting question concerns why this paper was so heavily criticized, and whether or not papers such as these have a place in scientific journals. Andrulis' paper, I suspect, is filled with flaws and inconsistencies, but I contend there is often insight from theoretical frameworks that we "know" are generally wrong. Thus, the problem, from my perspective, is not that Andrulis wrote this paper, but rather that there is not a biological journal (to my knowledge) where scientists can publish speculative or half-formed theories that are probably "wrong" but nonetheless help us think about the world in a different way. (Sociology, in contrast, in part because of our methodological pluralism and historical connections with philosophy, has a number of journals in which theories, even those that are highly speculative, can be developed and publicized.)