Some preliminary thoughts on “ultra-networked” politics: the 1984 anti-Hillary ad in perspective

Mar 22, ’07 12:20 AM

The identity of ParkRidge47, the heretofore anonymous author of the anti-Hillary advertisement which riffed on Apple’s “1984” commercial, was revealed today as Phil de Vellis, a former staffer for Sherrod Brown and ex-employee of political web design firm Blue State Digital. Naturally, this whole episode has the media endlessly repeating the truism that “candidates have lost control over their message,” and pondering the shape of the 2008 Presidential race as a consequence.

I have no well-reasoned wisdom to offer on this particular issue, only my immediate impressions. It seems to me that political candidates have been steadily losing strong control over their message for a long, long time. Never, in the history of our republic, have candidates had exclusive control over their message. Pamphleteering and broadsides were augmented with whistlestop train tours, which were largely replaced by radio, now talk radio and cable TV, which was supplemented by — and now is growing to peer status – the Internet. By the 2004 election the blogs made it clear that the Internet was going to serve as more than a pure advertising medium, or organizing tool. It was perfectly clear, except possibly to a few of the campaigns, that the chaotic nature of the Internet was going to express a multiplicity of voices: some “ruly”, some unruly, some claiming attribution, others hiding behind aliases and seeking to agitate anonymously. Much early thinking on this phenomenon was fairly utopian: the Dean campaign and the contributors to “Extreme Democracy” are cases in point. More discussion, more voices, is automatically a good thing in a democracy.

But is it?

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Apple Knows Best…

Mar 19, ’07 4:22 PM

Last week my 17″ MacBook Pro, now only a year old, suffered the “expanding battery problem” and I took it in for repair, and ended up replacing it because Apple’s diagnosis and repair service is so backed up (they quoted 200+ machines to service at the University District store) that they couldn’t tell me how long I’d be without a machine. Since basically everything I do is on the computer, this wasn’t going to work for me, and since I religiously back up my data, new hardware can easily get a “brain transplant.” So after an evening of playing Dr. Frankenstein and bringing the new machine to life (Target Disk Mode rocks, by the way), I took the old machine in the next day for repair.

Since the expanding battery was pressing the logic board up onto the keyboard, I figured a bit of refurbishment wasn’t a bad thing. In addition, my machine had a manufacturing defect where the right-hand speaker was soft unless you wiggled the mag-safe power adapter (who knows why THAT worked). So might as well fix that at the same time, since the machine will be in the shop for awhile. Once it’s back, I’ll probably sell it on eBay as a refurbished model, recouping some of my costs.

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Updates to RandomCopyModel simulation code and new TransmissionLab model

Mar 9, ’07 8:06 PM

Bandwidth has returned here at the house, so I’m catching up on a backlog of things that needed reasonably comfortable internet connectivity. The Canopy wireless service off Mt. Constitution has been having problems with a power supply and some other stuff for a couple of days, so I’ve been relying on my low-speed backup DSL link, which I have to say lets me get email but otherwise feels more like “super dialup” than “broadband.” Oh well.

I’ve been busy on the simulation modeling front this week, coming out with a “final” version of the RandomCopyModel from an upcoming paper by Alex Bentley, Carl Lipo, Harold Herzog, and Matthew Hahn. I didn’t work on the original model or paper, but Alex graciously allowed me to use the original code as the basis for some future experimental models we’re working on, as well as simulation setups I’ll need for my dissertation research. In return I refactored and made the original simulation a bit clearer to follow in terms of the code, so we’re providing version 1.3 of the RandomCopyModel under the terms of a Creative Commons-GPL license for non-commercial use.

In the meantime, I’ve also been planning the next “version” of the model, which is now a separate codebase managed by Google Code under the name TransmissionLab.

The goal of TransmissionLab is to accurately represent theoretical models of CT (e.g., random copying, prestige-biased transmission, frequency-biased transmission) within a variety of population structures (e.g., complete graphs/well-mixed, sparse random graphs and social networks of varying topologies, spatial lattices), and using a variety of update algorithms (e.g., Moran processes, Wright-Fisher processes, various other birth-death processes). TransmissionLab seeks to also make data collection and “observation” of simulated populations simple, with modules which are completely separate from the simulated population itself thus preventing observational “side-effects” on the model. Analysis flows from data collection, and can be done in a variety of ways.

Naturally we’re not the first people by any means to do agent-based simulation models of cultural transmission, imitation behavior within populations, or the diffusion of innovations. Heck, this isn’t even the first simulation of these sorts of phenomena I’ve been involved with. Where I hope that TransmissionLab differs is that nearly all of my previous simulation models have proven fairly special-purpose, expedient models for working on one particular question or problem, and I’m trying to make TransmissionLab a common platform that can span projects both for myself and my research group.

This is important for a number of reasons:

  1. Stable, well-used models tend to be well-structured, well-tested models. The issues of whether the simulation is showing us artifacts of writing software or the theoretical behavior we’re trying to describe can only be solved by deep investment in design, coding, and testing.
  2. Relating the results of one study to another when each uses different simulation code is a difficult one, for obvious reasons. To the extent that we use the same code framework and models to perform multiple studies, we can make arguments (and even measurements) which relate the results of several research studies to each other.
  3. The relationship issue mentioned in the previous item could span multiple research teams if the model is well-structured and tested enough that others adopt it for research.

Thus, I’m putting some reasonable effort into developing TransmissionLab, and if you have an interest in agent-based modeling and cultural phenomena, I hope you give it a look in a version or two. Right now I’m moving from the older RandomCopyModel to a new set of development tasks, which will be outlined shortly at the googlecode wiki for the project. Once these are checked in, there will be some interesting elements beyond the earlier model to explore. I’ll post when that happens.

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Research website

Mar 5, ’07 12:38 PM

I’ve made my University of Washington website live this morning, as a location for discussing my research, distributing software and publications, and so on. The site isn’t finished yet: publications and research areas still need to be filled in. The immediate impetus of putting up the site was to create a distribution point for the agent-based simulation software I’m working on with Dr. Alex Bentley. I’m getting ready to make another release of it, which generalizes it for use beyond Bentley’s original experiments, so when it’s ready I’ll post a notice and description here.

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A clear day on the northwest border

Feb 23, ’07 6:25 PM

This morning I had a good long conversation with my friend L, made special and unusual because we no longer live in the same city, and the fact that he’s one of my “partially-connected” friends. I mean this in the sense that he and I exchange email and IM, but as a means of connecting for those moments where we talk by phone, and even more rarely these days, meet in person. He doesn’t share my obsession with being online and part of the “flow” of information, so I don’t talk to him as much as I’d like.

L just spent a bit of time in the Bay Area, and while he was there his home in New England received a big snow dump, a commonplace in years past but a rarity this year. He said today, “I wish I could transport you there, to share the 5 feet of snow we’ve gotten.” Naturally, I wish I could be there as well — his house and the countryside are incredible even without snow, and I only imagine what it’s like thickly blanketed with white snow, sound muffled by the falling snow in the air.

When I was young I read Farmer Boy, one of the Laura Ingalls Wilder books, and the one which chronicles the boyhood of Laura’s future husband, Almanzo. The book made a deep impression on me in many ways, too many to discuss here, but in particular the descriptions of deep winter were a revelation to a Northwest boy, growing up in a climate where winter meant rain, grey skies, unwilling trips at 6am to fish for steelhead in cold Northwest rivers, and dominant colors of dark green and all the possible shades of grey, from light to deep steel — usually the color of the clouds while standing in the middle of the river fishing.

So I’m always captivated by the New England version of winter. And L’s wish to share the deep snow with me resonates strongly. But not quite strongly enough. Today was a gorgeous day here in the islands — blue skies streaked with high, fluffy clouds, light winds keeping the temperature crisp, but not so crisp that one couldn’t enjoy coffee on the deck with a sweater and long underwear.

Soon I’m headed down to Seattle for a short visit, and to spend some time with Carl Lipo, working on some papers we’re writing and projects deeper in the pipeline. I always hate leaving to travel — even down to Seattle. Each day I spend up here, surrounded by the water and clouds and wind is special — a destination I was apparently aiming for all this time, whether I knew it or not. Once I hit the mainland and start my trip it’ll all be fine, but I always go through this same feeling, no matter how often I commute back and forth. Few of us, I think, are lucky enough nowadays to know where home is. L does, and now I do as well. And that makes us both immensely fortunate.

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Darwin Day 2007: Darwin’s Impact on the Social Sciences

Feb 12, ’07 4:02 PM

In addition to being Lincoln’s birthday today, it’s also the 198th birthday of Charles Darwin, celebrated around the world as “Darwin Day.” In recognition of the day, I thought I’d share some thinking on Darwin’s contribution to the social sciences, because these are potentially as powerful as his direct effect on biology, if much less well developed. What follows is necessarily a sketch, since (a) much of it is reprising other sources, and (b) fully justifying and documenting this would turn it into an article or book, rather than a blog posting.

Ernst Mayr, the great biologist and architect of the Modern Synthesis, wrote in a 1959 essay that Darwin’s great contribution to biology was anti-essentialism, or what Mayr called “population thinking.” By this, Mayr meant that Darwin was one of the first biological thinkers to offer a theory of the evolution of species which did not rely upon changes to, differences in, or transformation of the “essence” of a species. In the older view, which goes back to Aristotle (at in terms of codifying this view; the origins of this view are much more ancient and are likely bound up in the cognitive science of “natural kinds”), each species is characterized by an “essence” or definition, which tells us what characteristics an animal, plant, and so on must have in order to belong to that species. The fact that each individual in a species is unique, and that often many individuals lack one or more essential characteristics, but are still considered part of the species, is explained away in Aristotelian essentialism as simply noise or reproductive error that causes the real world to be an imperfect reflection of the species’s underlying “reality.” Variation is thus explanatorily unimportant when species are viewed as characterized by pre-Darwinian biology. And the evolution of one species into another, over time, seems to run up against a massive gulf between two “essences.” One sees echoes of this “problem,” for example, in the objections of many contemporary anti-evolutionists when presented with what biologists believe is the abundant empirical evidence of evolution: the key words “intermediate forms” pop up as tell-tale signs, even though such a notion really arises only if one thinks a species has an “essence” between which a form could be “intermediate.”

Darwin’s great contribution, at least according to Mayr and others, was in founding modern evolutionary biology on a firm basis of anti-essentialism. In this case, what Mayr originally meant by “population thinking” (philosophers will recognize it as a variety of anti-essentialism) is that variation among individuals is not “noise,” nor is it meaningless error — variation among individuals is both the cause of evolution, and the great engine that powers the development of successive adaptations through the continuous (if occasionally roundabout) process of selection. Variation isn’t just important for selection, variation is critical for selection. No variation, no selection, as pointed out by the great mathematical biologist and statistician Ronald Fisher. In fact, selection might simply be the statistical consequence of having variation, some of which makes a difference of our life chances, in an environment where there aren’t enough resources, or enough room, or enough time, for every individual to succeed equally. Selection almost comes naturally when you think about the world through the lens of Darwin’s population thinking.

What has this got to do with social science and Darwin’s contribution to the human sciences? Potentially everything.

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