For J

Jay,

Since you asked earlier today, I will be giving you an explanation of my thesis topic as clearly as I can. It is overly long, but I wanted to be sure that I am clear about why I am doing this, and why it interests me. Remember. I am getting a Phd in Sociology, but I am studying a lot of mathematics, computer science and physics because many of the same models that are used in these fields are also used in the social sciences. The goal of writing a dissertation is to demonstrate that you can perform a piece of research, and that you can prepare it a professional manner and in accordance with all the political correctness that this requires, yahdi, yahdi. Certain skills (especially mathematical skills) are more valuable for a PhD candidate to have than others, and so in order to work on these skills (which I will describe below)  I decided to focus on the mathematical aspects of a certain branch of sociology called “social network theory”.

Why social network theory you ask?

Practical Reason: Basically because it is the most fun thing that I could make a pretty “good” living in the sense of relatively high enjoyment/fulfillment and without sacrificing my scientific principles.  Also, I like the “aesthetics” of networks and diagrams, and doing the little visual maneuvers is kind of fun. (sort of like drawing football plays)  Also learning social network theory “forces” me (in a good sense) to learn all this awesome computer programming, and mathematical visualization stuff (Processing, Java, Wolfram Mathematica). I’m playing a bit of catch up since I missed out on the sciences as an undergraduate, so I worked extra hard to learn at least conceptually some important parts of theoretical physics, and I am now up to Calculus III, which is something of a game-changer– i.e. if you can make it here, the coolness starts to take off. In other words, Calculus I & II are like black-and-white TV, while Calc III is like color TV. A whole new dimension of opportunity opens up. There is little downside, only up. The hardest part is getting to that level III. That’s why I am so big on these mathematical visualization tools, and part of my dissertation will demonstrate how this works, since I believe that other people may find my particular method useful.

In a sense it is the opposite of mountain climbing a mountain. Let’s say I want to climb Mount Everest, and  so I train for 20 years and I make it. I am at the top of the mountain. Now, although I’ve never been to the top of Mount Everest myself, my sources tell me that it is a really unpleasant place to be a while. Its not Hawaii. So no one goes to Mount Everest for the stay, but rather because they can say they scaled the biggest baddest mountain on the planet. That in and of itself is a major achievement, but you can’t use that actual experience to scale an even bigger mountain. Once you’ve done Everest, you’re finished and that’s all. Math is more like climbing a mountain, and then realizing that the mountain you just scaled is even nicer than the realm you just came from. At least I found it is this way for me. Also, unlike Everest, you don’t really leave the place you were (i.e. you are still at the base of the mountain with your family and all your loved ones), but you just see more than you did before, and then you have a new base from which to understand old ideas in new ways. It is really nice, and once you pick up a new math skill, you don’t lose it. So in that way it is more like Yoga than mountain climbing. You never “master” Yoga in its entirety, but you can “master” the practice of Yoga, in the sense that it becomes something you do, rather than forcing yourself to do. Well I am at the level of “mastering” mathematics in the former sense, of having good control over certain problems than I hadn’t before. It is a nice place to be.

So, because I now have a variety of programming, mathematical and statistical skills, learned over the past 5-7 years or so (both in and out of class).  I’ve had something of a mathematical renaissance in my life of late. Remember in college and high school when I didn’t like math and science, well I’m like that, only the exact opposite. So right now, even though I am a sociologist, I am more interested in understanding the nuances and subtleties of mathematical reasoning right now than anything else, and I am doing this through the mathematical modeling of social networks.

Since I want to work in this field, I wanted to find the best thinker (i.e. the Yoda) in the field. In social network analysis we have Harrison White, who was Kontopoulos’ (another Yoda) teacher back at Harvard in the 1970′s, and is still teaching up at Columbia. His work is similar in some respects to that of Alex Pentland (who Jim Warren likes) on the topic of “signaling.” See the wiki:

http://en.wikipedia.org/wiki/Harrison_White

Notice the badass looking diagram on the old-school projector. That clearly identifies him as a master in the ancient arts. The “style” is called the “parameterizing” style, and it just makes you a much smarter problem -solver.  So I am doing the sorts of models you see on the board, but I have a couple of new twists on White’s models, mainly because of the way I am exploiting today’s advances in graphics. One of these models, which is called the W(y) model, is the focus of my dissertation, which I will explain below.

There is another great scientist who influenced me – an LA guy of all things!- Cal Tech’s Richard Feynman. He’s one of my new heroes even though he died 20 years ago. The only way I can explain him is that, for me, anyway, he is a cross between Doc Hamer  and Hugh Hefner. He kind of looks like Hugh Hefner he lived a relatively West Coast lifestyle, and he was known for being the coolest and funniest physicist, but still he was a physicist. He was really high profile, and probably the second most famous physicist of the 20th century behind Einstein, at least in the United States.  Sort of like being really cool and wicked uncool at the same time. But like Doc Hamer, he was a really good teacher with the classic “physics” sense of humor, and there is a lot of good Youtube footage of him and stuff. For instance:

Anyway, he invented these things called Feynman diagrams, and these were part of a major scientific project that won him a Nobel Prize and helped give a more intuitive short-hand for extremely complicated mathematical calculations. They look cool, and they are very minimalist/Zen looking…Mathematical Elegance:

http://en.wikipedia.org/wiki/Feynman_diagram

Well, I basically made something like a “Feynman Diagram” for social network analysis, even if not as great. This is a major achievement for me personally. Imagine writing a screenplay that you had been working on for years. The outlines are there, some of the connections are made, the plot is two thirds completed, and so forth. Then one day it is completed, even if every single word is not yet in place, you know that it is a legitimate piece of work. It may not be “Gone by the Wind” or “Dirty Work”, but it also isn’t “Dracula Dead and Loving It.” Well, I feel this way about the visual representation of a market that I just developed. I don’t know if anyone else will find this interesting, but I can assure you that I find this way of making calculations useful, and even more importantly, this will greatly help me to solve other problems later on. This may not sound particularly exciting to you, but believe me, when you have been working a conceptual problem for 3+ years, this is a great feeling.

The real test is that they should help me explain to my family the basic outlines of my project. I think I am at the point when I can explain it to my family and friends willing to make a small effort to understand it.

“White Flags”: A Visual Toolkit For Understanding Complex Social Processes (working title)

Translating from jargonese to English: “White Flag” is a little title I made up as a play on words- White for Harrison White (who developed the original model), and “Flag” because the shapes I use to explain the model look like little flags. A lot of times a great scientist (White) comes out with an interesting theory that very few people can understand. Often a graduate student will take it on him or herself to clarify aspects of the work for a larger audience, or fill in some of the missing details. That’s basically what I’m trying to do. In 2002, White wrote an amazingly challenging book called Markets from Networks, which provided a model for understanding production and financial markets, but it is very hard to get through, unless you are fully committed to understanding it. This was the book that I was constantly reading while at home with Mom & Dad, and scribbling out formulas and training my programming skills with.  Well it took me about 3 years of background reading, and 6 months of dedicated reading and model building on my computer,  I am now at the point where I think I can use the model in an effective way. Even more importantly, I have developed a visual toolkit (java applets) that allow people to develop an intuition about the mathematics taking place.

Now what’s great but also somewhat overwhelming about studying White is that by studying his work, you have to learn all of this other “more fundamental” science by necessity. (otherwise you won’t fully appreciate technical depth of his work) So even if some of insights are incorrect, he is reasoning at such a high level that figuring out the logic gives you such a good workout that makes you a better thinker in general. Since I’ve spent so much time figuring out the logic of the model and organizing many of the formulas into a more intuitive framework, I figured I would make this visual toolkit that I used available to the general public.

How did I get into this stuff?

Let’s go back to when we were kids. What did I do when I was bored– I did all that memorizing Presidents dates, football statistics, lotta math, looking at maps, right?  The math that I do when I was bored. Like calculating things and playing with numbers and calculators.  Well that’s sort of what I am doing, except that I am looking at the automobile industry as a case study.

I am focusing on the automobile industry for a number of reasons (roughly in order of importance):

1- Outstanding set of data- This is really important in graduate school, because sometimes you want to study something obscure, but if there is weak information available it can take too much time to make it worth your effort. So for instance, while I was thinking about studying the robotics industry, the field is too new and too small for there to be consistent long term data set that allowed me to perform the types of mathematical tests that I am interested in performing.

Four.

There are three ideal types of markets that we can distinguish. Reading across, we have volume, price, and revenue. We have:

Market A: Phi =1 (All Prices the Same)
32    10     320
26    10     260
24    10     240
18    10     180

Market B: Phi < 1  (Decreasing Returns to Scale)
32    8.5   272
26    9.0   234
24    9.5   228
18    10     180

Market C: Phi > 1 (Increasing Returns to Scale)
32   10     320
26   9.5   247
24   9.0  216
18   8.5   153

We will be playing around with these some more, so keep these figures in mind. Since the middle column is price, and is obtained by dividing the third column by the first, we actually can do away with these, and knowing this rule allows us to reduce our little equations even more, to:

A: CRS
32    320
26    260
24    240
18    180

B: DRS
32    272
26    234
24    228
18    180

C: IRS
32   320
26   247
24   216
18   153

There are a lot of things we can calculate from these basic figures, our observables. For ease, we can also give our markets numbers as well, which in our case is the market revenue. A is associated with 1000, B, with 914, and C with 936. This is merely a mnemonic to remember. Also, since we have fixed one of the columns as well, the [32,26,24,18] line, we can also get rid of that and identify each of the markets as follows:

A: 320, 260, 240, 180 – (1000)
B: 272, 234, 228, 180 – (914)
C: 320, 247, 216, 153 – (936)

Reverse these, so that they are in volume order:
A:  180,240,260,320 – (1000)
B:  180,228,234,272 –  (914)
C:  153,216,247,320 – (936)

This is an easier form to think about the market, since we can know transfer this over to the W(y) Graph Form.

Third.

Anyway, back to football. We are going to play around with identities related to the concept “NFL”. We can start at the top, and question exactly what the NFL is. The NFL is the National Football League, a professional sports league that produces “games” for the consumption of its audience. Now this is the official, or we might say later, “non-ambiguous” definition of the NFL.

This brings us to the idea of “renormalization”, which is a term borrowed from physics, and as a first approximation, we can imagine a process by which certain aspects of a phenomenon are brought into focus while others are not. Sometimes its useful to imagine a map as well, which can be viewed at multiple scales. On a political map we may draw in approximate boundaries (although remember that the represenatations of boundaries are much thicker on maps than they are in real life. For instance, the thin line separating states on a standard school map of the United States is often miles wide when scaled appropriately) A very long term goal of mine (following a suggestion from White (2000) is to help develop renormalization methods in the social sciences, which would be a methodology that would allow us to see the interconnections between social processes operating at multiple scales. We are still a long way off, but there are some good leads in the work of Mandelbrot on fractals, (Mandelbrot and Hudson, 2004) See Abbott (2001) for an good overview of the fractal or scale-free perspective in the sociology.

I actually wrote a paper a few years ago on this topic, which I will post on the side sometime. In this paper, I looked at Marx’s 18th Brumaire from the perspective of fractals, and the heterarchical class model described in (Kontopoulos, 1993). This is a good document to show the evolution of my thinking. See also my work on the Pharmaceutical Industry that I submitted for my Master’s Thesis in Geography back in 2005.

Anyway, we can think about the NFL in terms of multiple identities nested within each other in complicated ways. The term NFL is a marker for an extremely confusing amalgam of social process constantly reproducing itself. Levels and scale are very important, whether we are talking about temporal or spatial scale. Below I will list the various ways that we can carve up the “NFL”. Most of these are older examples, drawn from Leifer’s excellent book on the construction of professional sports. Notice how the “identity” of the NFL changes depending on the context in which the term is used.

A running theme of Leifer’s book is that the various games of professional sports are nested within larger games played out by businesspeople, political actors, and other power figures away from the game itself, and that often the levels demarcating the “official” game and the “unofficial” game are transgressed. A hint of this boundary crossing is in the title of the popular ESPN show, “Outside the Lines.”, in which ESPN explores human interest stories, or political analyses of events happening to people associated with sports in the Real World.

Stylized History of the NFL (draw from Leifer, 1995 throughout)

Leifer’s basic project is to provide a history of the construction of the industry of Professional Sports, with a focus on the “quiet efforts of the major leagues to construct a framework of competition in which players and teams can be distinguished.” Leifer focuses on the coevolutionary histories of the four major leagues in the United States, from baseball in the late 19th century, to the emergence of major multinational firms by the 1990′s.

Leifer argues that the NFL was a second tier league (behind baseball) until the mid-1950′s, when it was able to leverage the new technologies of the era– notably television– to move ahead of baseball in being the dominant league. Before the rise of television, sports teams needed to connect themselves with a local fan-base to generate enough revenue to sustain themselves. Sports teams make money by “producing” games for a particular public. Leifer seeks to understand how the huge organizations that we call the NFL, the NBA, MLB, and the NHL came about through the efforts of the “organizers who transformed children’s games into the stable industry of major league sports.” We will find that this industry is continuing to evolve, even if the labels demarcating the Leagues have been somewhat stable in recent years.

Television and the NFL

The rise of television co-evolved with that of professional sports. The rise of television is a good example of what social scientists call a network effect. In the early days (say pre-WWII) of television, TV sets expensive, and since there was such a low number of potential

Second.

Markets/Games duality could be another name for what I am exploring. Pro Football is a perfect example of the levels intersecting. Obviously, football is a sport, a competition with particular rules, objectives and so forth. In the spirit of Leifer’s analysis of the rise of the major leagues, as well as the analysis by Delaney and Eckstein on the generally insidious effects of big stadium projects on neighborhood communities in which they are formed, we can look at the intersection of multiple “games” through the lens of sports. The NFL is often considered the most socialistic of the major sports, but we need to be clear in what sense that it is considered “socialist”. Because of course there are many anti-socialist elements in the NFL as well, so is would be not be useful to label it as being one way or another. The main thing is to have a clear sense of what the organizational structure is, so that we can know what we are talking about. This is a common story, as this quote from Ocho Cinco indicates: http://mjyork.wordpress.com/2008/12/03/nfl-socialism/ Pretty funny. But it is a valid, or taken to valid story about the structure of the field. But is it? Has anyone checked about the socialistic nature of the NFL? We’ll find out… It seems that the general argument is as follows: The revenue sharing system of the NFL resembles a communist-command economy than Major League Baseball’s system in which certain firms (organizations) have enormous payrolls than other firms. The NBA also has a salary cap system, so this is another example that we can use. So I will compare the organizational structure of the three leagues, the NFL, the NBA and the MLB in terms of inequality. The nice thing about pro sports is that it provides a very visual way of conceiving of social processes playing out at multiple levels. On the one hand, we have the identities, the NFL, the MLB, and the NBA, which are competitors at one level, but also are united together in some contexts as well. Futhermore, inside each of the leagues are 30 or so teams, which each are identities at another level, which each consist of individuals, which as Burt, (1992) and White (2008,1992) have powerfully argued, are themselves of indentities within the person. I refer you to those works, as well as the work of Charles Tilly, Kyriakos Kontopoulos, Andrew Abbott, Mark Granovetter, Pierre Bourdieu, and the many other represeantitves of the transactional/ relational approach to social science. [should I add huge number of names?] (Tilly, 2008, Abbott, 2004, Bourdieu, 2005, Kontopoulos, 2009)

First.

What Kind of Machine is a Football Team?

“It’s a machine game, man, its a machine game.” I remember hearing this line from football players back in high school. There is a lot of truth in what they say, but this does not tell us what exactly the type of machine we are dealing with. Football will be used as a case study as a model for the type of game theory/ strategic action thinking that we are working on at Temple. This will be a primer to my friends and family as a way for me to explain our ideas, research approaches, etc.

Engineering
I have to give it to my Father on this one. This may be surprising to my family, but you may have noticed, or not, that I have been doing much more “engineering style” research than I had done in the past. Going from books & novels, to Mathematica code & stuff, I actually think I am getting closer to what I really enjoy doing, which is actually closer to engineering.(“conceptual” engineering perhaps). So part of what I am doing is using engineering-style models to understand the sustainability and structure of economic markets.

By sustainability, I do not mean the term in relation to the “environment” specifically, although there are applications of the model I use to environmental issues (Waechter, 1999). Instead, we are asking what social processes or social technologies hold complex markets together. This will be clarified below.

By structure of markets, we are looking at how markets are organized by people in the real world. We take a naturalist’s perspective: we try to find the common sense of an industry, the common language, the signals in the environment that send clear, if not always full conceived, clues.

Identities
To begin to understand a social phenomenon, you need to understand the different identities (something like interested actors, either individuals or social groups) that have a stake in the situation. There are a surprising number of these even in a simple situation such as a football game. It is best to demonstrate this by giving examples.

Specific players , The “West Coast Offense”, Teams, A Style of Play (up-tempo, bruising, etc.)
Historic Games, announcers, stadiums, just about anything that we can attribute meaning to. The term is general, and somewhat vague, but this abstractness is useful, which will be shown.

For instance look at the following Formation Diagram of a typical football team:

INSERT PICTURE

There are innumerable ways that this diagram can be partitioned, and that we humans do almost immediately, and sort of simultaneously. In a quick glance we can identify “objects” such as the quarterback, the offensive line, the defensive backs, the offense, the officiating staff, and nest and combine them in a variety of ways. This is one aspect of what is often called “embedding” in the sciences, which I may or may not get back to right now.

We can also look at the different time and spatial scales over which action happens. This also intersects with the notion of embedding. Start at Level 1: we are given an objective fact. We will compare a 3 yard gain against a 4 yard gain. On one level, a purely quantitative level, a 4 yard gain is always greater than a 3 yard gain. However, there are innumerable situations in which a 3 yard gain is better than a 4 yard gain– a three yard gain on 3rd and 1, for instance, is much better than a 4 yard gain on fourth and nine. Time may be a factor as well. A three yard gain that wastes enormous time off the clock may be better (or worse) than a four yard gain that ends in a time-stopping out of bounds push. The point of mentioning this is that when identifying a fact or making an inference, it does not make sense without being placed in its particular language or conceptual scheme or something along those lines. Depending on the context, a smaller gain may be better than a larger one.

A related term is “frame”, which relates to the idea of describing an object or event. This is also related to the idea that a situation or phenomenon can be described from multiple perspectives that somehow cohere around the situation.

These ideas are best demonstrated by the use of examples. Right now, I am listening to Philadelphia Sports Radio and we are talking about the identity, “Donovan McNabb”. Now, there is the individual, the flesh-and-blood person Donovan McNabb, who suits up to play football on Sundays, and has a family and so forth. But there is also the Donovan McNabb “brand”, which holds an enormous sway over the minds and hearts of the crowd.

There is also the “social construction” Donovan McNabb that has a reputation in the current pecking order of the legacy of the NFL. For instance, there is constant argument about what Donovan has to do to make it into the Hall of Fame. They place him against his peers, and is usually ranked somewhere below Brady, and perhaps at the level of Eli Manning or so.

McNabb is branded on us as fans. For instance, the signifier McNabb associates immediately in the minds of Philadelphia Sports Fans: the time he played on a broken leg; the time he threw up in the Super Bowl; a good family and community man; the time he was booed on Draft Day; an amazingly gifted athlete; 4th and 26; and melding of all of these things. We don’t really know McNabb the man, but we decide about who he is based on our hunches about these relatively simple signals.

Another identity associated with Football is the “Philadelphia Sports Fans”, supposedly the rudest and crudest fans in the country, with very little real empirical support, usually associated with the time that they threw snowballs at Santa Claus in 1968. Somehow, even forty years later, this still brought up. Never mind that in the time between there have been numerous issues of fans burning cars and performing all sorts of ugly behavior every week, the Philadelphia fans still get the label.

It is a stock cliche that gives the national media a chance to just fill up some space on the handful of times that they show Philadelphia’s game. Anyway, this demonstration was to show how the game of football is embedded within a larger context. No matter how “pure” we try to keep the game, there will inevitably be spillover effects from the frame outside which it is embedded. The game co-evolves with the business and the geographic landscape in which it is ensconced within.

Lets pull the fans back in. The following fan bases are more or less well known as distinct identities: Raider Nation, the Dawg Pound, Yankees Fans, Notre Dame fans, and so on. People of opposing “tribes” often have silly arguments over their teams, when in fact people are basically “rooting for the laundry”. Sometimes fan activity, supposed to be completely sealed off from outside influences, as when a person runs on to a field and is promptly tackled by the authorities and sent off the field, or an animal scurries onto the field.

Furthermore, with the advent of constant highlight shows and 24-hour streaming sports radio, the game outside of the game is astronomically larger than it ever was back in the “good ol’ days.”