Books to Read While the Algae Grow in Your Fur; Heard About Pittsburgh, PA; Scientifiction and Fantastica; Pleasures of Detection, Portraits of Crime; Enigmas of Chance
Posted by crshalizi at December 31, 2006 23:59 | permanent link
Leo Kontorovich was last seen in these parts when I plugged his recent paper on concentration of measure in mixing processes. He has just started a weblog, Absolutely Regular. As he explains in his first post, his aim is to discuss topics related to his research, which means ideas in math, computer science and learning theory. The fare ranges from accessible musing on subjects like what makes math "deep", through notes for "mathematically mature" audiences (like this, contrasting measure concentration and large deviations), to technical yet fascinating questions about the learnability of formal languages. (As for the rumors that he picked up the habit of assigning unsolved questions from his own research as student problems from this class, well, "You might think that; you might very well think that; but I couldn't possibly comment.") There is far too little of any of this online, never mind all of it, in one place, with a keen mind behind it. Leo and I regard each other's politics as unsound, to put it mildly, but I am very happy to have him posting from the next building, and hope he will long continue.
Posted by crshalizi at December 30, 2006 22:15 | permanent link
Much to my loss (and, less importantly, embarrassment), I had never read this before this week. It really is as brilliant as everyone says, one of Lem's best, and bleakest, meditations on intelligence and alienness, cosmic strangeness and human pain. Most science fiction, like most fiction of any kind, is crap. Of the rest, most is mere brain-candy (which I devour eagerly, see side-bar at left). Of the rest, most is the literature of the great transformation, of humanity's passage out of pre-industrial darkness (perhaps into a different kind of darkness). This is science fiction as a literature that goes beyond the confines of our species.
I will not attempt a proper review, but I do want to draw out just one thread — I'm sure it's an old story to those who actually study Lem. The novel seems to owe something to two classic American stories of alien contact in the Antarctic, Lovecraft's At the Mountains of Madness and John W. Campbell's "Who Goes There?", though I have no idea if that's even historically possible, and Solaris is unquestionably at a far higher intellectual level. (There are a few places where the passage from Polish to English via French has reduced technical terms to gobbledygook, though I think I can guess what Lem meant.) In fact, I can't help but wonder if Solaris wasn't, in part, Lem's response to the challenge Campbell, as editor, set to his authors: "Write me a creature that thinks as well as a man, or better than a man, but not like a man". All those writers failed. (I think Lovecraft wanted to do this, but his best efforts ran a-ground in sentiments like this: "Radiates, vegetables, monstrosities, star spawn — whatever they had been, they were men!"). Lem actually succeeded here in making his readers imagine something which is so orthogonal to any sort of terrestrial mentality that even terms like "mind" or "intelligence" seem dubious, but inescapable. That he achieves this effect through, in part, an even more extreme version of the literal anthropomorphism indulged in by Campbell, that is artistry.
There is artistry, too, in the way Lem's protagonist realizes he has had a profound encounter with the utterly alien, but what matters to him is the all-too-human hope its side-effects offer of a tormented emotional redemption. "I knew nothing, and I persisted in the faith that the time of cruel miracles was not past."
Merry Christmas.
Posted by crshalizi at December 25, 2006 10:00 | permanent link
From the Abandoned Places photo-group I posted about this summer:
The photographer, one Reik, helpfully notes that "It's near St. Petersburg, Russia"; once upon a time, rather too near.
Posted by crshalizi at December 10, 2006 14:10 | permanent link
The constancy with which the same crimes repeat themselves every year with the same frequency and provoke the same punishment in the same ratios, is one of the most curious facts we learn from the statistics of the courts; I have stressed it in several papers; I have repeated every year: There is an account paid with a terrifying regularity; that of the prisons, the galleys, and the scaffolds. This one must be reduced. And every year the numbers have confirmed my prevision in a way that I can even say: there is a tribute man pays more regularly than those owed to nature or to the Treasury; the tribute paid to crime! Sad condition of human race! We can tell beforehand how many will stain their hands with the blood of their fellow creatures, how many will be forgers, how many poisoners, almost as one can foretell the number of births and deaths.
Thomas Pynchon (to my admittedly-philistine mind, the one worthwhile passage in Vineland):
If patterns of ones and zeroes were "like" patterns of human lives and deaths, if everything about an individual could be represented in a computer record by a long string of ones and zeroes, then what kind of creature would be represented by a long string of lives and deaths? It would have to be up one level at least—an angel, a minor god, something in a UFO. It would take eight human lives and deaths just to form one character in this being's name—its complete dossier might take up a considerable piece of the history of the world.
Randall "xkcd" Munroe:
Posted by crshalizi at December 01, 2006 08:00 | permanent link
Posted by crshalizi at November 30, 2006 23:59 | permanent link
Attention Conservation Notice: Over 3000 words of technical commentary on a paper on the statistical analysis of networks. Does a poor job of explaining things to those without background knowledge of networks, statistical inference and Markov chains. Includes some geeky jokes and many equations.
Yesterday in the Statistical Learning for Networks seminar, we discussed the following paper; what follows are a mix of my notes from before and after the discussion.
It's perhaps not completely clear from the abstract that their method works for a particular class of network growth models, which they call "duplication-attachment" (DA) models. These are pure growth models, where the network only expands, and never loses nodes or edges. (The network is assumed to be undirected, without self-loops or multiple edges between a given pair of nodes.) At each time step, we add one node. This is randomly chosen, with fixed probability, to be either a duplication or an attachment. If it's an attachment, the new node attaches to an old one, chosen uniformly over the graph (possibly with some fixed probability < 1). If it's a duplication event, we pick an existing node to duplicate, and the new one gets a certain probability of copying each of its model's links (independently), and a different probability of being linked to its model. It is entirely possible that a new node is added with no links to any existing node. Notice that nodes (and edges) have no intrinsic properties in this model; their names are arbitrary. Any two isomorphic graphs should therefore be assigned the same probability.
(The motivation for such models is that gene duplication is apparently fairly common, at least over evolutionary time, which would duplicate the interactions between genes, or their proteins. Attachment, here, is supposed to summarize all the other processes of network growth. There are several models of the evolution of protein interaction networks, e.g. those of Sole et al., 2002, and Vazquez et al., 2003, which are basically of the duplication-attachment type, and yield networks which at least qualitatively match some features of real-world examples, like degree distributions. These papers are not cited here.)
From any starting graph, it is easy to run the model forward and generate
new, larger random graphs; the probabilities involved are all pretty simple
uniform and binomial things. In fact, the current state of the graph
completely determines the distribution of future graphs, so this is a Markov
chain. The transition probabilities are fixed by the duplication and
attachment parameters, collectively
, and
these, together with a distribution over starting graphs, give us
a fully-specified stochastic model.
Normally, statistical inference for Markov chains is fairly straightforward, because most of the classical conveniences which make inference for IID data tractable are still available. (This is, after all, what led Markov to his chains!) So why then does the paper not end on the second page, with a citation "See Billingsley (1961)"? Because normally, when we observe a Markov chain, we observe a sequence of values from the chain, and that lets us estimate the transition parameters. Here, however, we have only the end-state, the final graph, as our data. The Markov chain will let us assign likelihoods to paths, but we don't know where we started from, and we don't know where we went from there, just how we ended up here.
Suppose we did know where we started from, some graph of
size
,
. (Remember here that each step of the chain adds one node,
so t really counts nodes, not clock-time. This is why it's natural to
start at
, as opposed to 0 or 1. The paper does not seem to
explain this point.) If we knew our initial state, then in principle we could
figure out the probability of reaching our final state from it, as a sum over
all possible paths:
![\[
L(G_t,\theta) \equiv \mathrm{Pr}(G_t|G_0;\theta) = \sum_{G_{t_0 +1}, \ldots G_{t-1}, G_{t} \in \mathcal{G}(t_0,t)}{\prod_{s={t_0+1}}^{t}{\mathrm{Pr}(G_s|G_{s-1};\theta)}}
\]](http://bactra.org/sloth/wiuf-figs/wiuf-et-al-notes_4.gif)
is set of all growing sequences of
graphs which start at
and end
at
. This mathematical expression is a
mouthful, admittedly, but it's probably clearer in a picture.
to
the final, observed graph
. The chain tells us the probability
of each such path. Since we had to take one, and only one, of these paths, the
total probability of making the journey is the sum of the probabilities of all
the individual paths.
At this point, any physicists in the audience should be nodding their heads; what I've just said is that the likelihood, from a given starting configuration, is a sum over histories, or a path integral. Along with the authors, I'll return to how to evaluate this path integral presently, but first we need to figure out how to get that starting configuration.
If we had a known distribution over starting graphs, we could (in principle) just evaluate the likelihood conditional on each starting graph, and then take a weighted sum over graphs. This, however, is not what the authors do. (I'm really not sure where one would find such a distribution, other than another model for graph development. Bayesian practice would suggest picking something which led to easy computations, but this makes a mockery of any pretense to either modeling nature, or to representing incomplete prior knowledge.) Instead, they try to use the known dynamics of the DA model to fix on an unambiguous starting point, and do everything conditional on that.
They observe that you can take any graph, and, for each node, identify the
other nodes it could have been copied from. (If A could have been copied
directly from B, then A's neighbors must be a subset of B's [ignoring the link
between A and B, if any].) So, from any starting graph, you can recursively
remove nodes that could have arise through simple duplications. In general, at
each stage in this recursion there will be multiple nodes which could be
removed, and their choice is arbitrary. Remarkably enough, no
matter which choices one makes, the recursion always terminates at
the same graph. (More exactly, any two end-points are isomorphic to
each other, and so identical for statistical purposes.) The proof is basically
a fixed point theorem about a partial order defined on graphs through
deletion-of-duplicates, but they confine it to the supplementary
materials, so you can take it on trust (and they don't use
such lattice-theoretic language even there). This graph
--- the data, minus everything that could be pure duplication --- is what they
take as their starting point. This is the
to the data's
. Everything is then done conditional on
.
OK, we have our initial condition and our final condition, and we have our Markov chain, so all we've got to do so is evaluate the integral over paths linking the two.
Problem: There are too many paths. In the worst case, the number of paths is going to grow factorially with the number of nodes in the observed graph. Even though along each path we've just got to do some straight-forward multiplication, simply enumerating all the paths and summing over them will take us forever. (The authors discuss some algorithmic tricks for speeding up the exact calculation, but still get something super-exponential!) Thus, evaluating the path integral for the likelihood is intractable, even for a single parameter value.
Solution: Don't look at all the paths. Rather, sample some paths, say N of them, evaluate the likelihood along each, and average. Hope that this converges quickly (in N) to the exact value of the integral. This is, after all, how physicists approach many path integrals.
Problem: Even if N is fairly small, we need to examine
many settings of the parameter
. It could still kill us to
have to sample N distinct paths for each parameter value.
Solution: Use importance sampling. Draw a single path,
valid for all parameter values, and evaluate the likelihood in terms of the
value of an "importance weight" along this path. The weight has to be a
function of
, but it should be the only thing which is. We
do this here by writing the likelihood,
, as an
expectation with respect to a reference measure, which the authors write
. This reference measure is given by
another Markov chain, called the "driving chain"; despite its name, it
is not a member of the DA family of chains. The trick here is
that one sample of possible paths, generated according to this chain,
can be used to (approximately) evaluate the likelihood at all
parameter settings of the DA model.
The crucial equation is [3] on p. 7568
![\[
L(\theta,G_t) = \mathbf{E}_{\theta_0}\left[ \prod_{s=t_0}^{t}S(\theta_0,\theta,G_s,\nu)\right]
\]](http://bactra.org/sloth/wiuf-figs/wiuf-et-al-notes_9.gif)
![\[
S(\theta_0,\theta,G_t,\nu) = \frac{1}{t} \omega(\theta,G_t,\nu) \frac{\omega(\theta_0,G_t)}{\omega(\theta_0,G_t,\nu)}
\]](http://bactra.org/sloth/wiuf-figs/wiuf-et-al-notes_10.gif)
,
but this is wrong.) Let's unpack this a bit.
is the probability of producing the
graph
through the addition of the
node
, with parameter
setting
. (N.B.,
must be a "removable"
node, one which could have been added by duplication.)
is this transition probability, summed over all
possible
. The first two factors in S are what we
want, the probability we'd get moving forward along the path according to the
parameter
. The third term is the reciprocal of the
transition probabilities according to the driving chain. Its only job is to
cancel those probabilities out.
The algorithm for generating the ith sample path is then as
follows. Start with the observed graph
. Count backwards,
Pick a
node
to delete, with probability
proportional to
. (Once
again, this limits us to the "removable" nodes, the ones which could have been
produced by duplication.) Set
to be the result of deleting that node. Keep going
back until we hit the irreducible core,
. (We will always hit
this core, by the fixed point theorem proved in the supplementary results.)
Then
![\[
l^{(i)}(\theta) = \left(\frac{(t_0-1)!}{t!}\right)\left(\prod_{s=t_0}^{t}{\omega(\theta,G^{(i)}_s,\nu^{(i)}_s)} \right)\left(\prod_{s=t_0}^{t}{\frac{\omega(\theta_0,G^{(i)}_s)}{\omega(\theta_0,G^{(i)}_s,\nu^{(i)}_s)}}\right)
\]](http://bactra.org/sloth/wiuf-figs/wiuf-et-al-notes_20.gif)
.
So, to summarize: We can generate a sample of paths connecting the observed final graph to the unobserved initial graph, according to the driving chain, and then approximate the likelihood for any parameter value by multiplying the importance weights along those paths and summing over paths. (The importance weights themselves even factor nicely.) We have thus solved the problem of evaluating a path integral, when we've got only one end of too many possible paths.
The trick used here to pull this off depended on having a uniquely-defined
starting point for all parameter settings, namely the
defined
through undoing duplications. (According to the authors, they took this from
papers on the coalescent process in population genetics, but I have not been
able to track down their references.) Strictly speaking, everything is
conditional on that starting point. Of this, more below.
Left unaddressed by the above is the question of how many paths we need to sample. Remember, the whole point is to not have to look at every possible path! If it turns out that accurate approximations to the likelihood require us to sample some substantial fraction, then this is all for nothing. However, the authors' figures reveal something quite remarkable. Whether N is 10 or 1000, the approximate likelihood changes very little (at least on a log scale), even with real data. This suggests that we don't, actually, need a lot of paths, but why?
For each i,
is an independent
realization of a random variable, whose distribution depends
only
(holding fixed the driving chain, and the initial and
final graphs). Since they are IID, we can apply the central limit theorem,
which tells us that their mean should converge at rate
.
Since that's noticeably smaller for N=1000 than for N=10, it must be the case
that the variance of the likelihood along the individual sample paths is
already pretty small. Why?
The lame physics answer is, "the principle of least action". There will be
optimal, most-probable paths, and they will dominate the sum, the others
tending to make negligible contributions. With high probability, a random sample
will pick out the most probable paths. Q.E.D. This argument could, perhaps,
be made less lame through an application of large deviations results,
specifically conditional-limit-theorem- (or "Gibbs's conditioning principle"-)
type results for Markov chains, which roughly say that if something improbable
(a passage from
to
) happens, it does so in
the least-improbable possible way, and deviations from that trajectory are
exponentially suppressed. <televangelist>In the name of Cramér,
in the name of Varadhan, in the name of Freidlin and Wentzell, I call on you,
Brother Argument, to be healed! Arise and prove! And, cf. Eyink
(2000).</televangelist>
An information-theoretic answer is to invoke the asymptotic equipartition
principle, a.k.a. the Shannon-McMillan-Breiman theorem. This says that
if
are generated according to a (well-behaved)
stochastic process, whose distribution is
, and
is a sufficiently well-behaved model, then
![\[
-\frac{1}{t}\log{L(\theta,X_1^t)} \rightarrow h(\mu) + d(\mu,\theta), ~\mu-a.s.
\]](http://bactra.org/sloth/wiuf-figs/wiuf-et-al-notes_25.gif)
is the entropy rate of the data-generating process
, and
is the relative entropy rate
between the data source and the model, i.e., the asymptotic growth rate of the
Kullback-Leibler divergence. (For details, see Algoet and Cover, 1988, or
Gray, 1990). So
![\[
\log{L(\theta)} = - (h+d(\theta))t + o(t), ~\mu-a.s.
\]](http://bactra.org/sloth/wiuf-figs/wiuf-et-al-notes_28.gif)
The biggest unclarity of all, probably, is the role of
.
Recall that we reached this by removing nodes which could have been
added by pure duplication. There is, however, no particular reason to think
that the actual growth of the graph ever passed through this state. It has the
advantage of giving us a unique starting point for the chain, but there are,
potentially, others. One, of course, is the trivial network consisting of a
single node! Another possibility (which came up in the discussion, I think
mostly due to Anna Goldenberg) is to
first remove potential duplicates, as the authors do, and then remove nodes
which have only one link to them, as clear attachments. This process of
unwinding the attachments could potentially be iterated, until no "danglers"
are left. This, too, is a uniquely-defined point. We can then go back to
removing nodes which are, now, potential duplicates, and so on. Someone (I
forget who) suggested that this might always terminate at the one-node network;
it would be nice to either show this or give a counter-example. But if there
is some principled reason, other than tractability, to use
their
, I can't figure out what it is from this paper.
Only using a growing network, and in particular only focusing on growth through duplication, certainly simplifies the computational problem, by reducing the number of possible paths which could terminate in the observed graph. Deletion of nodes and edges is however going to be very important in more biologically-plausible models, to say nothing of models of social or technological networks. Presumably the trick of using a backward-looking chain which stops when it hits a unique starting configuration could still be used with deletions --- I think the authors are hinting as much in their conclusion --- but it's not clear to me that a unique starting point is appropriate. With biological interaction networks, for example, one might argue that, e.g., metazoans have been around for a long time, so the distribution of networks ought to be close to stationary, and so starting configurations should be drawn from an invariant distribution of the appropriate chain...
This raises two further points, which are not un-related: the asymptotics of the DA model, and the biological utility of such a model. Run for a long time, the DA model will produce graphs of unbounded size, but it's not immediately obvious what these graphs will look like. In particular, what will be their degree distribution? The Barabasi-Albert model (Albert and Barabasi, 2002) produces scale-free distributions, <boosterism>because it uses the same mechanism as Herbert Simon's classic paper</boosterism> (Bornholdt and Ebel, 2001). This relies on a rich-get-richer dynamic, where nodes with high degree are more likely to attract new edges. My initial thought was that this wasn't present in the DA model, because targets for attachment and targets for duplication are both chosen uniformly. However, someone in the discussion --- I think, though I may be mis-remembering, that it was Tanzy Love --- pointed out that while high-degree nodes are no more likely to be copied than low-degree nodes, edges into high-degree nodes are more likely to be copied than edges into low-degree nodes. This is because if a node has degree k, there are k other nodes whose duplicated could end up linking to it. It may even be the case that this is falls under the theorems in Simon... Presumably the asymptotics would only become harder to handle if we added events deleting nodes or edges.
As for the biological utility, I'll repeat that none of the nodes have any identity of their own; only their role in the network of relations represented by the edges has any bearing on the model. "If this be structuralism, make the most of it": by turning it into a neutral model for the evolution of biological networks. After all, there is no reason here to duplicate certain nodes or edges, it's all just uniform chance. One key use of neutral models is to provide a background against which to detect adaptation; how could we do that here?
References:
Albert, Réka and Albert-László Barabási (2002),
"Statistical Mechanics of Networks", Reviews of Modern Physics
74 (2002): 47--97 = cond-mat/0106096
Algoet, Paul H., and Thomas M. Cover (1988), "A Sandwich Proof of the
Shannon-McMillan-Breiman Theorem", The Annals of
Probability 16: 899--909
Billingsley, Patrick (1961). Statistical Inference for Markov
Processes. Statistical Research Monographs, vol. 2. Chicago:
University of Chicago Press.
Bornholdt, Stefan and Holger Ebel (2001), "World-Wide Web scaling exponent
from Simon's 1955 model", Physical Review E 64:
035104 = cond-mat/0008465
Eyink, Gregory L. (2000), "A Variational Formulation of Optimal Nonlinear
Estimation", Methodology and Computing in Applied Probability
(submitted) = physics/0011049
Gray, Robert M. (1990), Entropy and Information Theory.
Berlin:
Springer-Verlag. Full text
free online.
Simon, Herbert A. (1955), "On a Class of Skew Distribution Functions",
Biometrika 42: 425--440
Solé Ricard V., Romualdo Pastor-Satorras, Eric Smith and Thomas
B. Kepler (2002), "A model of large-scale proteome evolution", Advances
in Complex Systems 5 (2002):
43--54 = cond-mat/0207311
Vázquez, A. and A. Flammini and A. Maritan and A. Vespignani (2003),
"Modeling of protein interaction networks", Complexus
1:
38--44 = cond-mat/0108043
Posted by crshalizi at November 29, 2006 02:30 | permanent link
Speaking, as I was, of this course, I've just spruced up the course homepage in anticipation of the coming semester. Comments, particularly on last year's lecture notes, are most welcome. (Reader M.H. has already won a free copy of the book, if it ever materializes, for his very helpful suggestions.)
Also, I have made a promise to try to post at least once a week, so that certain people know I'm alive (or at least that one of my scripts is still running).
Posted by crshalizi at November 27, 2006 22:57 | permanent link
Posted by crshalizi at October 31, 2006 23:59 | permanent link
"Concentration of measure" is a phenomenon in probability theory where, roughly speaking, any set which contains a substantial fraction of the probability can be expanded just a little to yield a set containing most of the probability. Another way to say this is that, given any reasonably continuous function, the probability that it deviates from its mean is exponentially small, and the exponential rate does not depend on the precise function. This makes concentration of measure results extremely useful for questions involving the estimation of complicated and ugly functions. The classical work in this area proves concentration-of-measure for various kinds of sequences of independent variables, but for real applications in statistics, machine learning or physics you'd want to be able to handle dependence. The natural way to do this would be to look at mixing processes, which are at least asymptotically independent.
Leo Kontorovich, who was one of the students in my stochastic processes class this past spring, now has a paper summarizing his work on, precisely, concentration of measure for mixing sequences:
Since I'll be teaching stochastic processes again in the spring, I would very much like to claim that Leo wrote these papers as a direct result of having taken my class. But the truth is that Leo knew so much about this already that, so far teaching him everything he knows, I learned almost all I know about concentration from him. But this is one of the real pleasures of teaching...
Enigmas of Chance; Corrupting the Young; Incestuous Amplification
Posted by crshalizi at October 16, 2006 14:00 | permanent link
The Ninth European Conference on Artificial Life will be held September 10--14 in Lisbon. The "European" in ECAL just refers to the location. No matter where you are in the world, if you work on any of the following subjects (among others),
|
Origin and synthesis of Life: artificial chemistries, autocatalytic systems, pre-biotic evolution, self-replication, self-organization, molecular self-assembly; Information and Measures of Complexity; Networks and Complex Systems; Evolutionary Robotics and Autonomous Agents: exploitation and evolution of morphologies, 3D rapid prototyping printers, non-holonomic robot control, bio-morphic engineering, self-assembly, evolvable hardware, collective robotics; Models of Brain-Body-Environment interaction: the question of boundaries, the dynamical systems approach, agency, homeostasis and autopoiesis, sensorimotor coordination, action-perception loops; Morphogenesis and Development; Learning, Adaptive Behaviour and Evolution; Social Behavior: language, social interaction, communication, swarm intelligence, ant systems; A-Life Art; Epistemological Issues, Tools and Methodologies; Philosophical Issues; Ethical and Social Issues |
 |
Posted by crshalizi at October 15, 2006 19:45 | permanent link
These handouts are shamelessly ripped off derivative work,
amplifying and expanding those created
by Tom Minka when he
invented this course. (See his
originals here.) Posted
here in response to a number (> 1) of requests.
See here for the first three
weeks' handouts.
Note to students in 36-350: This page will not keep up to date with the handouts, or with other course documents; use Blackboard!
Posted by crshalizi at October 12, 2006 11:40 | permanent link
I am sure that I speak for all of us in the Statistics Department at CMU (especially my erstwhile fellow bloggers) when I say we're very pleased and excited to have Prof. Mark Liberman as our seminar speaker on 16 October, a week from tomorrow. Mark is coming to us not as the impressario of LanguageLog (though, in that role, his scourging of sloppy data analysis, whether socio-political or neurosexual, is a joy to behold), nor as the director of the Linguistic Data Consortium, nor even to speak about bibliomics. Rather, he'll be talking about some work which combines the stochastic linear learning models (of the sort pioneered by, among others, Frederick Mosteller) with agent-based modeling of cultural evolution. Which is to say, he's talking about aggregate behaviors of interacting stochastic processes which are more interesting than just the central limit theorem.
Monday, October 16, at 4:30 pm in Baker Hall A51; free and open to the public.
The Collective Use and Evolution of Concepts; Enigmas of Chance
Posted by crshalizi at October 08, 2006 13:45 | permanent link
Blog near-silence will continue until bootstrap testing results improve. In the meanwhile, it occurs to me that I haven't mentioned that I have a new paper.
Thanks — over and above the acknowledgments in the paper &mdash are due to Jörg Reichardt for help implementing his algorithm, and to Anna Goldenberg for very thorough (not to mention patient!) editing, resulting in a much better paper.
There are about a zillion possible extensions and applications, which is a good note on which to get back to work.
Posted by crshalizi at October 02, 2006 17:50 | permanent link
Posted by crshalizi at September 30, 2006 23:59 | permanent link
Paul "arXiv" Ginsparg, evangelizing in the pages of the latest issue of The Journal of Neuroscience, under the rubric "As We May Read":
The e-print arXiv (http://arXiv.org/), initiated in August 1991, has effectively transformed the research communication infrastructure of multiple fields of physics and could play a prominent role in a unified set of global resources for physics, mathematics, and computer science. It has grown to contain >375,000 articles (as of July 2006), with >50,000 new submissions expected in calendar year 2006 and >40,000,000 full-text downloads per year. It is an international project, with dedicated mirror sites in 17 countries and collaborations with United States and foreign professional societies and other international organizations, and it has also provided a crucial lifeline for isolated researchers in developing countries...
The arXiv is entirely scientist driven: articles are deposited by researchers when they choose (either before, simultaneous with, or after peer review), and the articles are immediately available to researchers throughout the world. As a pure dissemination system, it operates at a factor of 100-1000 times lower in cost than a conventionally peer-reviewed system.... This is the real lesson of the move to electronic formats and distribution: not that everything should somehow be free, but that with many of the production tasks automatable or off-loadable to the authors, the editorial costs will then dominate the costs of an unreviewed distribution system by many orders of magnitude. ...
The site has never been a random Usenet newsgroup- or blogspace-like free-for-all. From the outset, arXiv.org relied on a variety of heuristic screening mechanisms ... to ensure insofar as possible that submissions are at least "of refereeable quality." This means that they satisfy the minimal criterion, that they would not be peremptorily rejected by any competent journal editor as nutty, offensive, or otherwise manifestly inappropriate, and they would instead at least in principle be suitable for review. These mechanisms are an important, if not essential, component of why readers find the arXiv site so useful. ...
The arXiv repository functions are flexible enough either to coexist with the preexisting publication system or to help it evolve into something better optimized for researcher needs. Although there are no comprehensive editorial operations administered by the site, the vast majority of the 50,000 new articles per year are nonetheless subject to some form of review, whether by journals, conference organizers, or thesis committees. Physics and astronomy journals have learned to take active advantage of the availability of the materials before journal publication ...
On the one-decade time scale, it is likely that more research communities will join some form of global unified archive system without the current partitioning and access restrictions familiar from the paper medium, for the simple reason that it is the best way to communicate knowledge and hence to create new knowledge. Ironically, it is also possible that the technology of the 21st century will allow the traditional players from a century ago, namely the professional societies and institutional libraries, to return to their dominant role in support of the research enterprise.
Ginsparg's title is a riff on Vannevar Bush's "As We May Think"; hopefully it will not take 48 years for these suggestions to be widely implemented.
Posted by crshalizi at September 21, 2006 08:42 | permanent link
Well, it looks like I have some VIGRE-funded undergraduate research assistants for the semester; specifically, I have takers both for my idea about aggregated network data, and neutral cultural diffusion on assortative networks. The latter, however, leaves me with a puzzle.
The project makes sense (to the extent that it does) against a background assumption that culture is not neutral, but an adaptation to the physical or social environment. This is a pretty pervasive assumption on the part of social scientists, historians, ethnographers, cultural critics, etc., but I'm not sure that my students will have been exposed to this idea as such. So, I need background reading which will rapidly persuade a wholesome, technically-inclined Carnegie Mellon undergrad that a person's beliefs and values ought to be correlated with their status in society. "Rapidly" is important, because there is some technical research to get to, and recapitulating the whole history of the sociology of belief is not an option. Similarly, assigning The German Ideology and/or The Protestant Ethic and the Spirit of Capitalism seems like asking for trouble. (And, with Weber, I'd feel like I'd have to spend a lot of time unteaching the errors.) So, I invoke the collective wisdom of the Web for reading suggestions: please write me at cshalizi [at] cmu [dot] edu [dot] oryx, deleting the name of a genus of antelope.
Posted by crshalizi at September 20, 2006 16:20 | permanent link
Via Language Log, there comes this fun post on the distribution of the number of repetitions of "R" in strings of the form "AR+", as in, "Arrr, mateys!" These findings, like Mark Liberman's on "AW+", are in line with the results of the seminal paper in this area, Dennis Chao and Patrik D'haeseleer's "The Distribution of Variable-length Phatic Interjectives on the World Wide Web" (University of New Mexico Computer Science Department Tech Report TR-CS-2001-23). I eagerly await further results in this exciting pico-field.
Being what I am, however, I can't resist pointing out that looking for a straight line on a log-log plot, and even finding one with high r-squared, is simply not a reliable way of checking whether a distribution is a power-law. Please do not do this. (And yes, I should be finishing that paper on the right approach, rather than blogging.)
Posted by crshalizi at September 20, 2006 13:23 | permanent link
My copy of Michael Bérubé's What's Liberal About the Liberal Arts? arrived in the mail yesterday (thanks to the unionized workers at Powell's), only to coincide with the release of the graphic novel (4Mb PDF). As a left-liberal professor, I can proudly testify to the complete and utter accuracy of this document's depiction of our revolutionary praxis. (At least, when we are not teaching fluffy courses about enchiladas.) My students should take notes, because this will be on the exam, particularly the bits about camels.
However, What's Liberal About the Liberal Arts? The Graphic Novel shows me that I must also engage in self-criticism. I have been complacent about enforcing political correctness, behaving as though statistics and machine learning could be taught in a neutral manner, when in reality every classroom is a site of conflict. In particular, I have been insufficiently vigorous in struggling against my students' tendencies to embrace borgeois individualism, in the form of the theory of merely personal, subjective and idealist probability associated with a clerical ideologue of British imperialism. I see that I must double and re-double my efforts to indoctrinate them in the principles of frequentist probability, based as it is on collectives and the work of social democrats. Might I be permitted to hope that comrade Gonick (also cited by comrade-professor Burke) will produe a proletarian, graphic version of the great red book epitomizing Peircism-Popperism-Neyman Pearson Thought?
(Via Pharyngula, Crooked Timber and John Burke [in e-mail] more or less at once)
Learned Folly; Corrupting the Young; The Progressive Forces; Enigmas of Chance; Afghanistan and Central Asia
Posted by crshalizi at September 19, 2006 13:49 | permanent link
Posted by crshalizi at September 19, 2006 12:43 | permanent link
In honor of International Talk Like a Pirate Day, I bring you:
Posted by crshalizi at September 19, 2006 12:27 | permanent link
These handouts are shamelessly ripped off derivative work,
amplifying and expanding those created
by Tom Minka when he
invented this course. (See his
originals here.) Posted
here in response to a number (> 1) of requests.
Lecture 5 is also a shameless rip-off explication
of Aleks Jakulin's
"Quantifying and Visualizing Attribute Interactions"
(cs.AI/0308002).
Note to students in 36-350: This page will not keep up to date with the handouts, or with other course documents; use Blackboard!
Posted by crshalizi at September 16, 2006 12:56 | permanent link
Hey, kid! Interested in winning eternal intellectual glory and entering the glamorous world of scientific research? Interested in $500 for the semester? Are you an undergrad at Carnegie Mellon University? If so, the statistics department has no less than nine possible projects for you. (Some of them are mine; one began as a blog-post, another as a notebook entry.) Apply now!
Update, 29 March 2007: See here for summer 2007 offers — all the glory, and more money!
Update, 26 January 2008: and see here for spring 2008 semester.
Posted by crshalizi at September 09, 2006 22:30 | permanent link
In his writings on the theory of automata, John von Neumann defines a complex system as one where the best model is, in fact, the system itself, and specifically mentions cats as an example of such complexity (thereby demonstrating not merely sagacity but taste). Since then, I am sorry to say, there has been a sad lack of interest in feline behavior within complex systems theory; but no longer. Going to the pet store the other day, I blundered into an aisle of motorized cat toys. Mindful of Abbas Raza's post on 3QD, I actually looked at them; and of course when I came to one that boasted an Amazing Chaos Wand, I had to look at it; and of course I had to buy it when I read the following ad copy on the side of the box (my links):
Professor Nozawa
CHAOTIC TOYS FACTORY, LTD.The Cat Attack uses the latest research in chaos theory and complex systems to emulate the movements and personality of a cat's favorite prey. This "virtual mouse" technology utilizes algorithms based on a six-dimensional coupled nzmap system modeled on the neural network of a real mouse. What that all means is that the Cat Attack's "virtual mouse" will become your cat's new best friend!
Professor Shimada
NIHON UNIVERSITYDr. Nozawa has developed an amazing and practical use for "deterministic chaos". It was Norbert Wiener who pointed out the importance of random noise in the brain and in automatic control systems. However, Dr. Nozawa showed that is was possible to solve the difficult "Traveling Salesman Problem" of optimization faster by using nonlinear dynamics, rather than random noise. The "Cat Attack" toy developed by Dr. Nozawa's company operates using powerful nonlinear dynamics algorithms, and this leading edge of human knowledge is appreciated by, among others, the Nozawa family cats, Tal, Fu and Phi, who seem to think the "Cat Attack" is truly alive.
I have turned this apparatus over to a collaborator who specializes in these issues, and she reports good results while the batteries last.
Posted by crshalizi at September 08, 2006 11:24 | permanent link
Since everyone is going on about Leszek Kolakowski (starting with Tony Judt, and thence Jonathan Goodwin, 3QD, DeLong) or, separately, Althusser (Bérubé, McLemee), I bring you: Kolakowski demolishing Althusser. Read it and weep, or laugh, as hailed. And do read Main Currents of Marxism, now that it's out in one volume ("so handy for pocket or purse", in the words of a certain rootless cosmopolite).
This completes your moment of Marxist harmonic convergence.
Posted by crshalizi at September 07, 2006 09:09 | permanent link
Posted by crshalizi at August 31, 2006 23:59 | permanent link
This looks useful (via Fresh Tracks).
This is only too accurate.
Posted by crshalizi at August 24, 2006 09:09 | permanent link
Constant readers may recall
the advert for a workshop on the
evolution of complexity that ran here in January. Because of the way that
workshop went, the call for papers will be contined until morale
improves has been renewed, with all papers to appear in a special
issue of Artificial Life. I reprint the CFP below. Notice that
this time, the length limits are the ordinary ones of the journal (2000 words
for letters, 12000 words for articles), not the harder limits of the workshop.
This should be good.
Special Issue on the Evolution of Complexity
Artificial Life journal
Call for Papers
Guest Editors:
Carlos Gershenson
Centrum Leo Apostel, Vrije Universiteit Brussel
Krijgskundestraat 33. B-1160, Brussels, Belgium
Tom Lenaerts
SWITCH, Flanders Interuniversity Institute for Biotechnology
Vrije Universiteit Brussel, Pleinlaan 2, 1050 Brussels, Belgium
Motivation
As a result of the quality of the Evolution of Complexity workshop at ALife X last June in Bloomington and the interest of the attendants; we announce a call for papers for a special issue on this theme for the Artificial Life journal.
The evolution of complexity is a central theme in Biology. Yet it is not without ambiguity. Complexity has been used to refer to different things. For instance, complexification has been interpreted as a process of diversification between evolving units or as a scaling process that is related to the idea of transitions between different levels of complexity. Other meanings of complexity have been introduced, both inside and outside of Biology. In most cases, though, the central concern is to understand what produces complexity.
The focus of this special issue will be on biological interpretations of complexity and on evolutionary and related dynamics as driving mechanisms for producing complexity. Questions to be addressed in the special issue include:
- How could complexity growth be measured or operationalised in natural and artificial living systems?
- How can existing data from nature be brought to bear on the study of this issue?
- What are the main hypotheses about complexity growth that can actually be tested today?
- Are the principles of natural selection as they are currently understood sufficient to explain the evolution of complexity in living systems?
- What are the environmental and other constraints of the evolution of complexity in living systems?
- What is the role of developmental mechanisms in the evolution of complexity in living systems?
- What are conditions could reduce evolved complexity in living systems?
- How factors allow the evolution of complexity in living systems to be manipulated and controlled?
- What models are most appropriate for understanding the evolution of complexity in living systems?
Paper Submission:
Submitted articles and letters should follow the submission guidelines of the Artificial Life Journal, available at http://mitpress.mit.edu/ALIFE. Authors should also include a cover letter describing briefly the relevance of their article to the specific topic of this call.These articles and letters should NOT be submitted to the journal editor, but should be uploaded through the special issue website (single PDF files only, include cover letter as the first page of the paper).
Papers will be judged by members of the Program Committee on their relevance to the call for papers, originality, clarity of the presentation, and overall quality.
Important Dates:
Submission deadline: December 15th, 2006
Notification of acceptance: February 1st, 2007
Camera-ready papers due: March 1st, 2007Programme Committee:
Chris Adami
Lee Altenberg
Mark Bedau
Hugues Bersini
John Bonner
Dominique Chu
Jim Crutchfield
Bruce Edmonds
Carlos Gershenson
Mario Giacobini
Franics Heylighen
Tom Lenaerts
Juan Julián Merelo
Barry McMullin
Chrystopher Nehaniv
Charles Ofria
Jorge Pacheco
Tom Ray
Jon Rowe
Stanley Salthe
Cosma Shalizi
Richard Watson
Larry Yeager
Posted by crshalizi at August 23, 2006 18:00 | permanent link
Posting will be light as I gear up for teaching (36-350, data mining for undergraduates, based on this excellent course template by Tom Minka, and Principles of Data Mining by Hand, Mannila and Smyth), and try to finish some papers. I'd advise you to go outside and enjoy what's left of the summer, but since you're reading this, you're not the type of person to do that. Go read Three Quarks Daily instead: they've pre-empted my idle notions of writing posts on deep states and Jack Chick, and they have a better sense of humor and much better taste in art than I do.
The regularly-scheduled cursing of R, LaTeX, time, and an inadequate supply of ibuprofen will now recommence.
Posted by crshalizi at August 22, 2006 15:10 | permanent link
This is a joke that never grows old — just more bitter. (The latter via everyone in the known universe; provoked into posting by John Burke in e-mail.)
Posted by crshalizi at August 19, 2006 18:55 | permanent link
One of my friends in graduate school had an adviser with a gift for memorable expressions, at least for a theoretical physicist, especially when dismayed by some stupidity. Two of his put-downs which stuck with me were "I could go crazy tomorrow and find an appointment in the sociology department", and "I don't want to criticize you, but this is the way superstring people think". I was never sure which was supposed to be worse, but now I know. Sociologists have many faults, but they do know better than to try explaining a variable with a constant, while string theorists evidently do not. (Via CapitalistImperialistPig, who has better things to write about.)
The fact that Prof. Motl reasons so badly here that he'd fail my freshman stats class is, of course, infinitely less offensive than fact that he's a bigot (of the "we must squarely face the harsh light of my pseudo-scientific prejudices" variety). But I can't help feeling — hoping, even — that the two sorts of idiocy are linked.
Update, next day: Greetings, readers from Reference Frame and Brad DeLong! Just to correct some mis-apprehensions: my Ph.D. is in statistical physics, not sociology; I'm an assistant professor of statistics (not sociology) at Carnegie Mellon (not Michigan, where I was a post-doc); the closest I have ever come to "committing a social science" was drawing a map with some other physicists. If you're actually interested in my qualifications, you can look at my CV, or my research and teaching.
Second Update, 20 August: I'm afraid I was too elliptical above. The occasion for Motl's outpourings was this story in the New York Times on how the fraction of black and Hispanic students at New York's specialized high schools, like the famous Bronx High School of Science, has fallen over the last ten years. Fallen, as in, decreased, as in, changed over time, as in, been variable. To account for this, Motl pointed to the black-white IQ gap, which he proclaims one of the great invariant facts of human life, as in, nothing changes it, as in, constant. Even if one grants him his premise (which I would not), the IQ gap might, with a lot of other assumptions, explain why the number of blacks in these schools is low, but cannot explain why it has fallen. This is why I said he would fail my freshman stats class. A Marxist who tried to use the conflicting interests of capital and labor to explain the wage stagnation of recent decades would be guilty of exactly the same fallacy, and I'd fail them for the same reason.
I hope I have made myself clear.
Manual trackback: Nanopolitan
Posted by crshalizi at August 18, 2006 23:45 | permanent link
A cheerful comparison problem, in honor of the day:
Which analogy is more valid? Which one is more inflammatory?
Posted by crshalizi at August 15, 2006 13:15 | permanent link
Reading Billmon and Adele Stan reminds me of a question which has been bugging me for a while, but not so much as to actually investigate it. Namely: how much did traditional anti-Semitic stereotypes contribute to the stereotypes associated nowadays with conservative attacks on the "liberal cultural elite", "transational professional class", etc.? (I'm thinking of ideas like: Jews run the media etc. behind the scenes; Jews are clever but shallow; the bankers are all Jews; the Communists are all Jews; the Jews want to do away with our wholesome institutions and religion.) It would seem like a natural translation for someone to have made, but I don't know of any evidence that it did happen that way. Maybe, after all, there are only so many ways of disliking other groups that any pair of negative stereotypes is going to have a lot in common, if you look for it. (Of course, people who harbor or play to such stereotypes about liberals are not necessarily anti-Semites, even if those stereotypes historically developed out of anti-Semitic ones.)
Has anyone with some actual knowledge looked into this?
Update 17 August 2006: Edward Burns writes to point out that before the current fabricated outrage over the "war on Christmas", it was being pushed as a UN plot by the John Birch Society in the 1950s, and before that Henry Ford was warning that the Jews were trying to get rid of Christmas and Easter. (See this good story by Michelle Goldberg in Salon.) It's not clear, however, that there was any actual transmission of ideas from one episode to the next; if I were a historian I'd think it would be worth looking into, though.
Posted by crshalizi at August 14, 2006 20:43 | permanent link
Starting about a year ago, I have refused to referee papers for journals owned by Elsevier, since it sticks in my craw to provide free labor for people who turn around and gouge the academic community mercilessly. This reasoning applies, to some degree, to all commercial journal publishers, though Elsevier is unusually exploitative in its pricing. There is however a more substantial reason to dislike them: their — forgive the phrase — mercenary involvement in the international arms trade. Tom Stafford, who blogs at Idiolect, is organizing a petition of academics to try to get Elsevier to stop organizing arms fairs; it's worth signing.
Posted by crshalizi at August 12, 2006 17:24 | permanent link
Almost two years ago, I complained that there was no English e-text of Zadig, Voltaire's oriental Enlightenment detective fable. At the time, I thought this was my usual pointless whining into the void; but no. Through the good efforts of Barbara Tozier, and the rest of the people associated with Project Gutenberg and Distributed Proofreading, one of the most charming of M. Voltaire's literary productions is now available for free to the English-reading web, in both plain-text and handsome HTML versions.
You realize this means I'm only going to whine here more.
Posted by crshalizi at August 12, 2006 16:50 | permanent link
Cross-posted to Crooked Timber.
Kieran Healy's post about his book on organ donation gives me a hook to write something about the other end of the system, about organ recipients and the institutions which are supposed to match them up with donated organs. More specifically, how one such institution, the Kaiser HMO of Northern California, quite spectacularly failed several thousand people who were depending on them, by not matching them up. The story has been around since early May, when it was broken by Charles Ornstein and Tracy Weber in the Los Angeles Times (cached here), since confirmed by an investigation by Medicare/Medicaid. It doesn't seem to have gotten all that much attention among the blogs, but it's outrageous, and deserves, for that reason alone, to be better known.
Kaiser is a very large and old HMO, with a huge presence in the Bay Area and northern California. (In fact it was one of the very first HMOs, started by Kaiser Steel during WWII as a way of attracting workers to its foundries and shipyards when wages were frozen.) It actually consists of non-profit health plans and hospitals, and for-profit physicians' partnerships, the Permanente Medical Groups; normally, patients in the health plans have to go to physicians in the groups to have their medical expenses covered. One notable exception, up until 2004, was the 1500--2000 Kaiser patients in northern California who needed kidney transplants because of renal failure: those procedures were sub-contracted to the hospitals at UCSF and UC Davis, which also managed the patients' places on the waiting list.
That last bit requires some explanation. Once organs are donated, they need to be matched up to recipients. This is done by an organization called the United Network for Organ Sharing, which tries to trade off urgency, seniority (i.e., time spent waiting for an organ), proximity and compatibility (since the closer the match between the donor's immune system and the recipient's, the less problems from rejection). There is a heavy weight put on seniority, though especially close immunological matches can over-ride it. Each transplant center is responsible for keeping the network up-to-date about their patients who need organs, their immunological profiles, and their time spent on the waiting list.
What seems to have happened is that in 2002, a transplant surgeon named Arturo Martinez proposed to Kaiser that it could save money, and increase the utilization of its hospitals' surgical capacity, by bringing the kidney transplant program in-house, and Kaiser agreed, with Martinez becoming head transplant surgeon. (It would be unfair, at this point, to say that Kaiser did this because it meant more business for the for-profit Permanente Medical Group, but it's hard to imagine that counted against the proposal.) As of mid-2004, Kaiser patients on the waiting list were informed that they would no longer be covered for transplants at UCSF or UC Davis, though they were free to go ahead and have them if they could come up with the money (roughly $100,000).
So far, all this is maybe a little self-serving on Kaiser's part, but not, in itself, appalling. (It's certainly more than legitimate for health-care organizations to try to save money.) What happened, though, was that Kaiser completely screwed up the program. Remember that organs are allocated (basically) through the UNOS system. The patients were being removed from the listings under the university hospitals, and being added to the listings under the new Kaiser transplant program. Unless this was done correctly, this would mean that they'd look like new names on the list, and so all of their accumulated waiting time, one of the main determinants of priority, would vanish. This happened to a huge number of people on the list, basically reducing the chance that they'd get a kidney to next to nothing. This becomes less surprising when one learns that Kaiser never consulted UNOS about the massive transfer of patients it was planning, and "placed responsibility for submitting patient data ... in the hands of a single clerk who had one hour of telephone training on UNOS's database", though not any more excusable. Needless to say, patients were not told that by staying with Kaiser, they were losing their place on the lists, and thereby reducing their odds of survival. Some of them, at least, seem to have been assured that they were keeping their places, when that wasn't true, though this is less clear to me.
Losing seniority on the transplant lists wasn't the only problem. Kaiser did very few transplants, compared to the number of organs which were available. This happened in part because they just didn't have the capacity to keep up with their many patients (at one point they were down to a single nephrologist for the whole program, who was also supposed to be its medical overseer), and in part because of what seems to have been mis-placed perfectionism or caution. These combined to the point of repeatedly turning down "zero mismatch" kidneys, ones where the likely compatibility over-rode considerations of seniority. This happened several dozen times at least — twice for one patient alone. Again, needless to say, patients weren't told about this. In a "it's not a bug, it's a feature" moment, Kaiser initially attempted to defend its program by pointing out how few patients had died after transplants — since they'd done so few.
What strikes me as especially outrageous about all this is that the people being screwed over were people who needed new kidneys. To state the obvious, anyone who needs an organ transplant is very ill. It's maybe less obvious that being that ill is a full-time job. One of the vital parts of the body is no longer working; to substitute for it requires extraordinarily complicated, time-consuming and generally unpleasant procedures. People who need new kidneys are people who are kept alive by dialysis, which is, indeed, complicated, time-consuming, often painful, almost always exhausting, and carries a non-trivial risk of infections, possibly fatal. People who need new kidneys are also often people who are very ill in other ways, since it's not that common for both your kidneys to just stop working if nothing else is going on. (Kidney problems are, for instance, a not-uncommon complication of diabetes, and of high blood pressure. Dialysis, naturally, messes with blood pressure, adding yet another variable to monitor and regulate.) Simply staying alive, when you are multiply-sick person with organ failure, can pretty much demand all the time and attention you have to give, and a fair chunk of your loved ones' as well. (There are good reasons why the families of people in situations like this tend to fall ill themselves.) You are certainly not in a position to check up on whether your medical organization has, through incompetence, messed up your position on the transplant lists. (Some Kaiser patients actually tried to keep up with their place on the lists, but were given the run-around.) And as for switching to another medical organization, do please show me the company which will extend coverage to someone who needs a new kidney, at a price which can be afforded by someone who needs a new kidney.
Since the Times broke the story, there's been some improvement. The doctor who was medical head of the program, and apparently at least partly responsible for snafu of not transferring patients' time, Sharon Inokuchi, has been relieved of her administrative duties. (In fact, if memory serves, she left Kaiser, but now I can't find where I think i read that.) The program has been investigated by the Center for Medicare and Medicaid Services, which basically confirmed the newspaper reports, and forced it to promise major changes; it could still lose its eligibility for funding under those programs. The California state agency which regulates managed care is still, I believe, investigating. There's talk of large fines, and there will certainly be lawsuits. All of this is to the good; it's certainly better than nothing. But still, thinking about this makes me angry: Kaiser had a duty towards many very sick people, who were in a very poor position to look after themselves. It failed in that duty quite dramatically. In any organ transplant program, patients will die while waiting for a match. In most kidney transplant programs, though, about twice as many patients receive transplants as die while waiting; Kaiser managed to reverse that ratio. While it's hard, in the nature of things, to identify any one patient who's died and say "They would have lived, if only Kaiser hadn't done this", it's almost certain that more of these people have died than would have otherwise. I don't have a better remedy to propose than fines or lawsuits or institutional tinkering, but they all seem horribly inadequate.
Posted by crshalizi at August 04, 2006 14:49 | permanent link
Cross-posted to Crooked Timber.
Now this is what I call "filling the mind with ever new and increasing admiration and awe, the more often and steadily we reflect upon them".
(Via David R. in e-mail.)
Posted by crshalizi at August 02, 2006 11:46 | permanent link
Posted by crshalizi at July 31, 2006 23:59 | permanent link
Attention Conservation Notice: Over 1500 words on a wacky quasi-socialist economic scheme, from someone utterly lacking in credentials in economics. The scheme does not respect the sanctity of private enterprise, but at the same time would not reduce the alienation of labor one iota. Includes a lengthy quotation of a game-theoretic impossibility result. Also, you already saw it when it was cross-posted at Crooked Timber.
In the previous installment in this series of modest proposals, I looked at ways of making the incentives of the managers of large, publicly-held corporations align more closely with those of their long-term shareholders. This left alone the question of the beneficiaries of corporate value; assuming that the managers are busily working to maximizing their revenue streams, who benefits from their industry and diligence? Having just read Mark Greif's great essay on redistribution in n+1 (issue 4; sadly, not online), I would like to make a suggestion.
The text for today is Gary Miller's Managerial Dilemmas: The Political Economy of Hierarchy, an excellent book which I learned about from Henry Farrell. Ambitiously, Miller tries to explain why hierarchical corporations exist at all, why they take some of the forms they do, and how, in part, their form relates to their performance. Much of the book, especially the first part, is a partially-successful attempt to find good economic reasons for their features, i.e., efficiency-enhancing ones. (He does not seriously consider the option that enterprises are hierarchical for non-economic reasons, say that some people like bossing others around, which hierarchies let them do, and those people are able to select hierarchies over other, more efficient, forms. After all, it's hardly historically unprecedented for powerful people to prefer institutions which lower aggregate output but give them a bigger share of the product. See, e.g., here.) He also tries to explain why theories of corporate organization that rely solely on economic "mechanism design", i.e., structuring information and material incentives, will actually lead to sub-optimal results, for pretty basic game-theoretic reasons; getting beyond these impasses is fundamentally a political problem. This is potentially quite subversive in its own way, but it's really the first part of the work, about the economic justification of the hierarchical enterprise, that I'm going to twist and abuse.
One of the features of the modern corporation that Miller attempts to rationalize is the existence of shareholders who are passive and, in the overwhelming majority, utterly disconnected from the day-to-day or even year-to-year operations of the company. He does so by means of the following impossibility theorem, attributed to Bengt Holmstrom. Having tried to summarize Holmstrom's theorem better than Miller, and failed, I'll just quote Miller.
Holmstrom assumes that there are n agents whose actions determine a level of revenue x. The actions taken are unobservable and are costly to each of the agents. In particular, we assume the production function is a team production in which the productivity of each individual's action is determined by other individuals' levels of effort.
Holmstrom points out the desirability of three characteristics of an incentive system — and then shows that they are logically inconsistent. First, Holmstrom examines the Nash equilibrium outcome of an incentive system. At such an equilibrium, each individual will find that he or she could not do better by choosing a different effort level, as long as all others do not change their effort levels. Simple marginal analysis tells us that, in such an equilibrium, each person will find that his or her marginal cost of effort is exactly equal to the marginal gain; otherwise, the individual could be better off by working harder or not as hard. Second, Holmstrom stipulates that the outcome be budget balancing — that is, the incentive system should exactly distribute the revenues generated by the actors among the actors. Third, Holmstrom examines Pareto efficiency. This means that the outcome should be such that the individuals in the organization could not find a different outcome that would make them all better off.
Holmstrom shows that no budget-balancing system can create a Nash equilibrium that is also Pareto efficient. In other words, every budget-balancing incentive system will induce a social dilemma among its participants. The reason is that individuals will bring their own marginal costs of effort into equality with their own marginal gain. This means that each individual will not undertake an additional unit of effort that will produce less individual gain than individual cost — even if that extra unit of effort produces more gain for other individuals on the team.
As an example, suppose there is some individual who has a marginal revenue productivity of $12: Each unit of her own effort generates an extra $12 for the team. According to Pareto optimality, she should exert additional effort as long as the cost to her of that effort is less than or equal to $12; each such unit of effort generates more revenue for the team that it costs her as an individual. The only way to motivate her is to make sure that she gets all of the marginal revenue of her last unit of effort. In a team, it is impossible for this to be the case for every individual, as long as the incentive system is budget balancing. If everyone gets all of the last dollar produced, the team will have to pay out more in incentives than it generates. But if the individual gets only one-third of the marginal revenue from her actions, she will work only as long as her effort costs her less than $4 per unit. [pp. 129--130]
This suggests a rather unusual role for shareholders: they provide a money-sink, someplace money can go other than those actually involved in production. This means that the economic mechanism no longer has to be budget-balancing, which actually makes efficiency possible. Miller suggests that this is one reason why the modern public corporation, with its separation between legal ownership (by stockholders) and day-to-day control (by managers) can work, to the extent that it does. It is precisely because the shareholders are passive, with very limited influence over the actual running of the corporation!
Today's modest proposal — and I should make it very clear that Miller suggests nothing of the kind — is to take this separation of functions even further. Shareholders can use their legal ownership to intervene in the running of the company, though it is hard (and managers try to make it harder). By doing so, however, they become players in the team-production game, and lose their useful role as a money-sink. To limit this danger, while retaining the advantages of competitive markets for capital allocation and corporate control, I suggest the following. A substantial fraction — say three-quarters — of all profits of publicly-held corporations are to be paid to a new institution, which we might call the National Mutual Fund. (Closed corporations and partnerships are exempt.) Once a year, the Fund would pay out its accumulated profits as dividend checks, giving an equal amount to every adult citizen. And that's it.
Substantially reducing the flow of dividends associated with stock ownership should cause a large one-time shock to the level of the stock market. (Roughly speaking, shares should drop by about 3/4.) However, because the Fund collects uniformly, it should not distort relative prices, which are what matter for purposes of capital allocation. The net worth of stock-holders, likewise, will suffer a one-time drop, but this will be partially compensated for by their receiving payments from the Fund in the future. Anyway, lots of things affect the value of stock holdings; it's not like someone purchased their labor with a promise of future benefits, and then tried to back out of a freely-entered contract when it came time to pay up.
A further wrinkle would be to curb the practice of retained earnings. These account for a huge fraction of corporate capital formation, but they are also one of the ways in which managements escape market discipline. (For some figures on this, see Henwood's Wall Street, pp. 72--76.) I suppose one could make a Hayekian argument in favor of the practice, but, really, if management can make a good case that a pet project will earn at least a normal rate of return, it shouldn't be hard for them to raise funds on the open capital market, and if they can't make such a case, it's hard to see how they'd be discharging their fiduciary duties to shareholders by pursuing it anyway. This reform, I should add, is logically separate from that of instituting the National Mutual Fund. However, since corporations would pay more out in dividends, it would tend to increase the value of shares, reducing the shock to the level of the stock market.
It is hard to see why the actions of the National Mutual Fund could not be at least as rule-bound and de-politicized as those of a central bank run by skilled technocrats. Indeed, it would seem easier to reduce the discretion of the Fund's officials to the vanishing point, and to strictly keep it from meddling with the affairs of any corporation, which would be deeply counter-productive. For their part, the citizens receiving the dividends would get the benefits of "portfolio diversification in their income", but their incentives to meddle politically with individual firms, even quite large firms, would be quite muted. Moreover, they would have a direct and tangible incentive in the health of the corporate sector as a whole, making them less likely to support market-distorting measures to benefit particular firms, geographical regions or industrial sectors. We would move, in short, towards a true ownership society.
Posted by crshalizi at July 31, 2006 15:38 | permanent link
Cross-posted to Crooked Timber.
It's a hot, lazy Sunday, which seems like a good time for browsing through livejournal communities dedicated to photos of peacefully rusting machines, quietly crumbling buildings, and similar modern ruins:
The photographers are all amateurs, so the quality (to the slight extent I can judge) is quite variable, but many manage to capture the suggestion of sunset and sadness, of unhappy stories brought to a close, which fascinates me about such scenes. Some of these photos, in fact, seem as good as, say, those in Terry Evans's book on the former Joliet Arsenal, Disarming the Prairie, bringing to mind the words of the poet:
These are the halls of the dead, where the spiders spin and the great circuits fall quiet, one by one.— But I see I'm getting melodramatic, and it's just too hot and sticky and still to sustain that.
Update: John Burke (who needs to revive his blog) writes to point to Jef Poskanzer's great industrial archaeology page, with many fine pictures and links.
Posted by crshalizi at July 30, 2006 14:59 | permanent link
Cross-posted to Crooked TimberAs a good neoclassical, neoliberal economist, Brad DeLong is acutely aware that the market system is not natural at all, but a delicate historical anomaly. He is worried that it is so familiar to his students that they will find alternate modes of social organization almost incredible; accordingly he wants to mess with their heads:
Would making Berkeley's first-year economics Ph.D. graduate students this fall read short biographies of William Gates and William Marshall as a way of getting at the idea that there are non-market societies that work very differently from our own today--would that be a teaching idea of extraordinary brilliance or of total insane lunacy?The rest of the post is an extended excerpt from the New York Review of Books review of a biography of William Marshal (which goes on to my to-read list). The question I have is, what should DeLong make his students read, to give them a vivid sense of just how differently production and distribution could be and have been organized? Argonauts of the Western Pacific, perhaps? Gilgamesh?
And: those of us who teach things other than economics, what books do or should we hand out as ice-axes for our students' frozen seas? (This one is mine.)
Posted by crshalizi at July 29, 2006 17:43 | permanent link
Cross-posted to Crooked Timber
Via everyone in the profession: the statistician Frederick Mosteller has died. Mosteller was one of the great leaders of the generation of statisticians in which our field went from being an annex of mathematics (as it was when he attended Carnegie Tech) to an autonomous, institutionalized discipline. He had an astonishing range as a researcher, but is perhaps best known for his work on stochastic theories of learning theory and the authorship of the Federalist Papers. He was also a notable teacher, as his essay "Classroom and Platform Performance" suggests, and in the later part of his career tried to bring elementary inferential hygenie to educational research. More anecdotes are available from Tales of the Statisticians, or this brief sketch by his student Stephen Fienberg.
Posted by crshalizi at July 28, 2006 09:42 | permanent link
Cross-posted to Crooked TimberIn the comments to my post on Onsager, Maynard Handley explains why he finds himself somewhat unsympathetic, as Onsager apparently did not expend the effort necessary to make himself understood by others.
You, the author of the paper, have a responsibility to make your ideas comprehensible. If the first method you choose to explain them fails, then you listen to what people say about where they lost all track of understanding and write a new paper with NEW explanations, not the same explanations that failed last time only renumbered. ... [This is] not something that is drilled into young scientists; that it is YOUR responsibility to make your ideas clear to others, not their responsibility to try to figure out what you are talking about. As science grows ever larger and ever more complex, I think it is time for all scientists to be much more explicit and much more ruthless on this point.Whether this is really a fair criticism of Onsager, I couldn't say, but the general point is true, important, and a perfect hook for the next thing I wanted to post about.
Science is a social, collaborative process, so part of being a good scientist is effective communication. Scientific communication is overwhelmingly written communication (scientific disciplines are, in a sense, literary communities), so part of being a good scientist is being a good writer. Unfortunately, scientists get little training in writing, and much of that consists of being advised to follow the rules found in horrid little compendia. Fortunately, there is some actual research on effective written communication, that is, on how to arrange your words so that their readers tend to acquire clear notions of your ideas. The best practical guide here, I've found, is Joseph William's Style: Towards Clarity and Grace. However, I have just discovered (via Paradise Blogged) a fine essay by George Gopen and Judith Swan, "The Science of Scientific Writing", which gives a clear yet concise presentation of the work. (Gopen and Williams are collaborators.) Here is their own summary of how to be clear:
Posted by crshalizi at July 26, 2006 00:53 | permanent link
Cross-posted to Crooked Timber.
A staple of bad movies and trashy novels about scientists (i.e., the kind I read) is the neglected genius whose ideas are rejected with incomprehension by the scientific establishment during his life, because they are simply Too Far Ahead Of His Time to be grasped by lesser mortals, only for the scientific community to rediscover these insights decades later. This sort of thing can make for entertaining fiction (if dreary self-mythologization), but it simply doesn't happen all that often in real life, especially not when the hero is a part of the establishment, and indeed a much-honored one. It certainly doesn't show up, with documentary evidence, in the staid, reliable pages of Reviews of Modern Physics. Nonetheless:
Nobody outside of statistical physics (and maybe physical chemistry) has heard of Onsager, but he was indeed a great physicist, albeit in a very technical, non-flashy way. By the time he did this work on turbulence, he was already well-known in statistical mechanics for the analytical solution of the Ising model, his theory of phase transitions in liquid crystals, and, perhaps most importantly, a pair of classic papers from 1931 which basically founded modern irreversible thermodynamics, for which he would eventually win the Nobel Prize. (Eyink and Sreenivasan give a fuller discussion of his accomplishments, including the Onsager-Machlup theory of non-equilibrium processes, on which Eyink himself has done important work.) We're definitely not talking about some marginal figure cut off from the scientific community.
Nonetheless, his attempts to get people to pay attention to these ideas on turbulence were singularly unsuccessful. The reaction of Theodore von Kármán, a deservedly great name in fluid mechanics, was to describe it (in a letter to his student C. C. Lin) as "somewhat 'screwy' "; Onsager also corresponded with Lin, who replied in the classic manner of someone wanting to put an end to a conversation (quoted on p. 117): "I am sorry to say that I have not made much progress, except that I desire still more to see something done in this line to bring your ideas down to my level of understanding." As for the statistical physicists, Eyink and Sreenivasan describe their reaction as one of "polite incomprehension" (except on the part of von Neumann — in an unpublished report). The fact that one of Onsager's letters describing his ideas (reproduced as Appendix A in this paper) is headed "The little vortices who wanted to play", and begins "Once upon a time there were n vortices of strengths K1, ... , Kn in a two-dimensional frictionless incompressible fluid" probably didn't help, either. Most of all, a combination of discouragement over this reception, a tendency to be a slow and perfectionist author, and having scads of major research projects going simultaneously kept Onsager from even trying to publish any of this material.
The moral, I hope, is clear: statistical physicists who wander into other areas of science, and find their ideas dismissed by the best experts on those subjects, should nonetheless publish in Physical Review, in a "Fools! I'll show them all!" spirit, provided they are Lars Onsager.
(It's interesting that this paper was written by two physicists active in this area, rather than by a historian of science. It seems doubtful to me that a historian, reading the relevant materials in the Onsager archives, would have realized that there was a story here, unless they were familiar with modern work on turbulence at a deeply technical level — unless they had "contributory" as well as "interactional" expertise. And if anyone had gone over those archives around 1990, before these ideas were re-discovered, what would they have made of it?)
Manual trackback: In the Pipeline
Posted by crshalizi at July 25, 2006 15:20 | permanent link
Cross-posted to Crooked Timber.
Two of my more public-spirited fellow citizens have recently identified looming threats to our own Commonwealth of Pennsylvania.
Most scientists unfortunately, those that certainly are advocating for this [embryonic stem cell research], and many others feel very little moral compulsion. It's a utilitarian, materialistic view of doing whatever they can do to pursue their desired goals.
I, for one, will be happier voting on Mr. Santorum's re-election in November, knowing that my ballot will play a part in the age-old struggle between utilitarian materialism and deontological idealism, as well as the sagas of human-canine relations and Old Corruption.
More than a third of all Pennsylvanians are native speakers of a language other than English — and many of them have not even tried to learn English since immigrating, or at least prefer to carry out their daily lives in another language, living together in neighborhoods where their native language dominates. Some people worry that the majority status of English is critically endangered. 25 years ago, a major political figure warned that these "aliens ... will never adopt our language or customs, any more than they can acquire our complexion", and so far, his prediction seems to be right on the money.
And let's not forget what they've done to our cooking!
Posted by crshalizi at July 25, 2006 12:12 | permanent link
Cross-posted to Crooked Timber, hence the parting shot about comments.
Under the rubric "Can Blogging Derail Your Career?", the Chronicle of Higher Education has seven bloggers discussing Yale's decision to not hire Juan Cole as a professor of history, and the role, if any, played by his blog in that decision: Siva Vaidhyanathan, Dan Drenzer, Brad DeLong, Michael Bérubé (all: yay!), Glenn Reynolds and Ann Althouse (both: hiss), and Erin O'Connor (null result), with a "response" by Cole, which doesn't actually address the others' posts specifically, and reads like a separate essay on the same subject as the others. (Via De Long.)
(Some of the things which were written about Cole as part of the controversy (e.g.,) give the impression of a professor who attains incomprehensibility not through obscurity but through foaming at the mouth. As it happens, though, I sat in on his seminar on millenarian movements when I was a post-doc at Michigan, and nothing could be further from the truth. I suppose I could have missed all the sessions which degenerated into hours-long rants about Zionist Entities... Of course, I don't know why Yale didn't give him the job, but if it was because they thought he was too spittle-flecked to be presentable to parents and alumni, they were misinformed.)
The fact that this post is not filed under "Middle East Politics" isn't going to stop anyone in the comments, is it?
Posted by crshalizi at July 24, 2006 22:01 | permanent link
Attention conservation notice: 1500 words on psychophysics and the statistical mechanics of disordered excitable media. Also, it was cross-posted to Crooked Timber, where I am guest-blogging this week, so you've seen it already.
First off, I should thank Henry and the rest of the Timberites for the kind invitation to guest-post, and that very warm introduction. In exchange, I'm going to blog more or less as I usually would, only here. This means some big bricks of posts about "complex systems", so called, which is or was my scientific field, more or less; and also any miscellaneous outrages which catch my eye this week. Mounting my usual hobby-horses on this stage is a poor exchange for their generosity, but mounting hobby-horses is why I started blogging in the first place, and anyway I'm big on conscienceless exploitation of cooperators.
Today I want to talk (below the line) about some recent work in the statistical mechanics of disordered systems, which might help explain how our sense organs work, and actually involves some good uses of the self-organized criticality and power laws; tomorrow or the day after I'll get to the smoldering question of "Why Oh Why Can't We Have Better Econophysics?"
Folklore says that the dark-adapted human eye can detect a single photon; this isn't quite true, but we can consciously detect a few tens of photons, and some species are that sensitive. Of course, we can see not only in the dark but also during broad daylight, but then the number of photons falling on every part of the retina is huge; the eye isn't overwhelmed and saturated, though now one or ten photons more or less makes no discernible difference. In the jargon, the eye, and the other sensory organs, have both a large "dynamic range" (we can see in the dark and in the daylight), and "nonlinear response" (changes which are noticeable in the dark aren't against a high-intensity background). Some version of these facts, including the basic (power-law) form of the relationship between physical stimulus intensity and perceived sensory magnitude, have been known since the nineteenth century. This makes it all the more puzzling that sensory neurons show a linear response over a narrow dynamic range, beyond which they saturate.
You could evade this difficulty by having lots of neurons with different operating ranges, so that raising stimulus intensity saturated some but activated others. The problem is that there don't seem be that wide a spectrum of operating ranges for individual neurons. In a recent paper, Osame Kinouchi and Mauro Copelli (who blog together at Semciência) offer another way, which has to do with the way sensory neurons interact with each other in a network.
Neurons, like muscle cells, are "excitable", in that the right stimulus will get them to suddenly expend a lot of energy in a characteristic way — muscle cells twitch, and neurons produce an electrical current called an action potential or spike. Kinouchi and Copelli use a standard sort of model of an excitable medium of such cells, which distinguish between the excited state, a sequence of "refractory" states where the neuron can't spike again after it's been excited, and a resting or quiescent state when the right input could get it to fire. (These models have a long history in neurodynamics, the study of heart failure, cellular slime molds, etc.) Normally, in these models the cells are arrayed in some regular grid, and the probability that a resting cell becomes excited goes up as it has more excited neighbors. This is still true in Kinouchi and Copelli's model, only the arrangement of cells is now a simple random graph. Resting cells also get excited at a steady random rate, representing the physical stimulus.
Kinouchi and Copelli argue that the key quantity in their model is how many cells are stimulated into firing, on average, by a single excited cell. If this "branching ratio" is less than one, an external stimulus will tend to produce a small, short-lived burst of excitation, and there will be no spontaneous activity; the system is sub-critical. If the branching ratio is greater than one, outside stimuli produce very large, saturating waves of excitation, and there's a lot of self-sustained activity, making it hard to use a super-critical network as a detector. At the critical point, however, where each excited cell produces, on average, exactly one more excited cell, waves of excitation eventually die out, but they tend to be very long-lived, and in fact their distribution follows a power law.
(People who teach courses on random processes are very fond of branching processes, because the basic model can be solved exactly with hundred-year-old math, but there are endless ramifications, and some of the applications are very technically sweet. Like most mathematical scientists, Kinouchi has certain tools he tends to return to, and critical branching processes are one of them.)
As Kinouchi and Copelli say in their abstract, the idea that the critical point, where things are just about to go unstable, is a useful place for processing or transmitting information is a persistent theme of complex systems. (You could, arguably, even trace a version of the idea back to William James's Principles of Psychology.) It has also, before this, been one of the weakest of our ideas. The original work from the 1980s on "evolving to the edge of chaos" has proved impossible to replicate, I would even say experimentally refuted. (Why the phrase and idea continue to propagate is another question for another time.) Stu Kauffman's studies of models of gene regulatory networks certainly suggests that information moved through these most easily near their critical point, but I don't think anyone has done a careful information-theoretic analysis of that. In any case, E. coli doesn't care about the bandwidth of its regulatory network: it cares about reliably making lactase when it only has lactose to eat, i.e., specific adaptive functions. Prior to this, I can only think of one situation where the idea has been made precise and has strong evidence to back it up (namely, this paper), but that's a purely mathematical exercise of no biological relevance.
What Kinouchi and Copelli have done is very different: they've actually identified something biologically important which is maximized at the critical branching ratio, namely the dynamic range. The network as a whole responds to the stimulus, and its dynamic range can be many orders of magnitude wider than that of its component cells. It is this enhancement which is maximized at the critical branching ratio, and falls off sharply for networks which are even a little sub- or super- critical. As a bonus, the shape of the response function is of the correct power-law form, though, in their model, the exact exponent isn't right. Modifying the network structure, or some model details, changes the exponent, but the dynamic range is still sharply peaked at the critical branching ratio.
There are a lot of other nice things about this paper, which I won't get in to least I repeat it all, but I will point out one thing: while their central qualitative results are pretty robust to small tweaks, there are some details of their model which make it a fair caricature of some excitable media, but not all. These are quite deliberately matched to properties of the olfactory system and the retina, but wouldn't work in, say, the cortex, where the dynamics of excitation are different. So this isn't an "over-universal" model, but one of particular phenomena produced by particular mechanisms. In fact, looking at olfaction, they are able to make a prediction about the effects of knocking out specific genes which are involved in the fast, symmetrical electric couplings they assume. Nobody seems to have done those experiments yet, but, at least to this non-biologist, it seems feasible, and, now, very interesting.
*: Here's an anecdote illustrating how broken academic publishing is. Kinouchi and Copelli work at the University of Saõ Paulo, which doesn't, for reasons of economy, subscribe to Nature Physics. To get an electronic copy of their own published paper, they were forced to write correspondents at other universities. I couldn't help them, because my school doesn't feel like it can afford to subscribe to Nature Physics either.
Posted by crshalizi at July 24, 2006 16:20 | permanent link
Attention conservation notice: 1600 words of pedantic whining about how a book on architecture didn't meet my parochial expectations. Also, it was mostly written and then abandoned to the gnawing criticism of the mice over a year ago.
I give up; it's got me beat.
I asked the good people at the MIT Press for a review copy of this, this thing, years and years ago, back when I was still regularly writing book reviews, because it sounded cool.
We humans owe an immense architectural debt to many other species. Indeed, the first hexagons humans saw may have been in honeycombs, the first skyscrapers termitaries (termite high-rises), and the first tents those of African weaver ants. In The Monumental Impulse, art historian George Hersey investigates many ties between the biological sciences and the building arts. Natural building materials such as wood and limestone, for example, originate in biological processes. Much architectural ornament borrows from botany and zoology. Hersey draws striking analogies between building types and animal species. He examines the relationship between physical structures and living organisms, from bridges to mosques, from molecules to mammals.Insects, mollusks, and birds are given separate chapters, and three final chapters focus on architectural form and biological reproduction. Hersey also discusses architecture in connection with the body's interior processes and shows how buildings may be said to reproduce, adapt, and evolve, like other inanimate or "nonbiotic" entities such as computer programs and robots. The book is both learned and entertaining, and is abundantly illustrated with fascinating visual comparisons.
It would have been cool, too, if Hersey weren't an ignorant idiot. Oh, I'm pretty sure he's OK when it comes to purely architectural matters — though how would I know if he wasn't? What drives me up the wall every time I try to write about this book is that he gets everything else wrong.
Let's take history and languages first. Hersey is a professor of art history, and so I don't think it's unfair to expect him to get these straight. But we are talking about a man who can instance a spiral design from a Byzantine church as an example of an "Islamic spiral", whatever that may be (p. 47). He doesn't seem to realize (pp. 28–29) that the early Greek architects who first defined the classical orders wouldn't have used a Latin word (capitulum) to refer to the top of a column. I'm not even sure he realizes (pp. 7–8) that Hermes Trismegistus was a Hellenistic myth. For that matter, after presenting a fanciful analogy (pp. 17–18) between the ground-plan of Lemba, a Chalcolithic village in Cyprus, c. 3900 B.C., and cross-sectional diagrams of biological cells, he writes:
Certainly the builders of these dwellings would have known similar forms in their immediate surroundings — things that, unlike true body cells, were visible to the naked eye. One prototype would be the egg, which begins as a contained for a single-cell embryo embedded in the nourishing matter it will need in order to reproduce and grow. ... And then there are cell-like beehives, birds' nests, and plants. To the Greeks, moreover, and therefore maybe even to the Chalcolithic residents of Lemba, the word for cell (kutos) also meant uterus, and even the whole human body. So we must not relinquish the thought that the Lemba cells are the extended phenotype of builders whose own bodies, though they did not consciously know this, were put together similarly.Let me try to extract everything that's broken in these sentences, and see what's left.
Bad as he is on history and languages, Hersey is worse at science and mathematics, and the history of science. He has no idea what "a topology" is (p. 51; at best this is a garbling of a curved manifold). He is capable of writing about distances "increasing at a fixed angle" (p. 45; he seems to mean rate), and of "steel molecules" (p. 13). He thinks sharks are not vertebrates (p. xvii). He literally does not know what a virus is (p. 15). (He also doesn't know when they were first discovered, nor when their shapes were first determined [pp. 15–16], and so his suggestion that illustrations of the shapes of viruses influenced some of Gaudí's designs on the Sagrada Família [p. 16] is just wrong.) He doesn't realize that DNA molecules don't actually look like the simple diagrams people draw of double helices, but are bent, folded and twisted, and so resemble spiral staircases not at all (pp. 6–8). And so on, and so forth.
Let me give a last example of the kind of thing which irritates the hell out of me; it comes from very early in the book (pp. xviii-xix), but it's central to whatever attempt at an argument Hersey makes.
Homo sapiens shares something that I don't yet dare call a gene sequence for building — shares it, perhaps homologously, perhaps convergently, with other constructing creatures such as birds, crustaceans, ants, termites, and bees. I will also be claiming, as a corollary, that the shapes of our monumental shelters, whether bicycle sheds or cathedrals, reflect and often derive from the shapes first created by these other species — species that, like us, are subject to the monumental impulse. ...This isn't a paradox for his idea — it's a refutation. The last common ancestor of humans and termites lived before the Cambrian explosion, presumably in the oceans; whatever bizarre wormy thing it may have been, it assuredly didn't build. Even if the genes "for" building in humans and termites are both descended from the same set of genes in that remote common ancestor, they are no more homologous than flight is homologous in birds and pterodactyls, because they both independently modified vertebrate forelimbs into wings. A little reading on comparative methods, and how homologies are actually established, would have kept Hersey from wasting his and his reader's time. (Similarly for the chapter on the reproduction and evolution of architectural designs, which is completely innocent of all actual work on, say, the evolution of technology, or even on the cognitive processes of architectural representation.)
But now comes a paradox: certain ants, termites, honeybees, and birds build elaborate structures. So do humans. But, as humans, we are anomalous in doing this. Only a few other mammals build — most obviously beavers and badgers. Worse still, our own closest cousins, the other primates, hardly build at all. An African termitary might remind us of Wright, of a Gaudí spire, or of a skyscraper by Hermann Obrist. But no such thoughts come to mind when we look at the rudimentary retreats of chimps and gorillas. Thus any genetic homology that brackets us with the other builder-species will have to be very ancient and, also, will have to have bypassed our immediate ancestors and cousins.
The whole book is like that — a series of conceits which a little thought or research would've shown don't work, presented as real scholarship. To be fair, Hersey sometimes allows himself a certain levity of presentation: in chapter eight he claims (basically) that people like domes because they remind them of breasts, which he illustrates by juxtaposing a picture of the Taj Mahal with one he attributes to "D-Cup Superstars, February 1992". But even then, he concludes, on no basis whatsoever, that the Taj is "an architectural thernody to the queen's breasts" (p. 155), and means us to take that seriously.
I won't say that Hersey's book is bullshit, because Hersey buys it. But I will say it's crap. It's crap in the same way that much too much of what I read by scholars in the humanities is crap: Hersey doesn't think carefully and critically, he tries to use ideas he doesn't understand, he's sloppy about facts, and he thinks he's establishing reliable conclusions when he can't argue his way out of a wet paper bag. Lest by saying this I call up the wrathful wraith of Chun the Unavoidable, I hasten to add that (1) many scholars in the humanities are, indeed, excellent and careful scholars, who do not suffer from these debilities, and (2) I think this cannot in the least be blamed on any value of post-*ism, or or "theory" or anything of that sort. Certainly Hersey is not a post-*ist, and I have no reason to believe this sort of crappiness has become more common among humanists in recent years. (If anything, I'd guess that the causal arrows point from crappiness to post-*ism, rather than the other way. For this, too, however, I have no evidence.)
— But, you see, this is what always happens when I try to write a proper review of The Monumental Impulse: I end up wandering hopelessly off topic, in order to avoid having to think of all the ways the book vexed me.
Do not read this book.
Posted by crshalizi at July 20, 2006 00:45 | permanent link
The Xanadu region of Titan has rivers:
No images, yet, of "caverns measureless to man", or a "sunless sea" of liquid methane.
(Via Beyond the Beyond.)
Update, 20 July: I should have read the press release first (via Uncertain Principles). More importantly: Venus! (via The Daily Llama).
Update, 21 July: The Quantum Pontiff wonders whether Einstein's work on the physics of rivers will hold on Titan.
Posted by crshalizi at July 19, 2006 22:00 | permanent link
I wrote this about a year ago; I'm cleaning out my drafts folder.
As a paid-up member of the Viridian movement, I it would be a Very Good Thing for industrial civilization to find a power source which will let it run and grow without choking on its own waste. (I'm no good at ranting about this, so if you're curious I refer you to the master.) But it would be foolish to pretend that non-fossil-fuel power sources will not carry their own costs, including the possibility to alter the climate, and something worse than foolish not to consider those costs. After all, one of the Viridian design principles advises us to "Look at the Underside First":
Legions of people are paid large sums to promote the positive aspects of commercially available products. Very few people earn their daily bread by pointing out malfunctions, bugs, screw-ups, design failures, side-effects and the whole sad galaxy of trade-offs and failings that are inherent in any technological artifact. To counteract this gross social imbalance, a wise designer and a wise critic will make it a matter of principle to look at the underside first.
In which spirit, I bring you the following.
There are basically three channels through which wind power would influence climate. The first is direct increase of friction in the vicinity of the turbine, which dissipates kinetic energy in the wind into heat. The second is that the increased drag produced by the turbines will change the speed and direction of prevailing winds, and since these winds carry heat and moisture, can potentially alter the climate over large areas. The third, and most indirect, channel is that increasing use of wind power may reduce the amount of fossil fuel consumption, and interact with climate changes produced by the existing load of greenhouse gases.
The present paper is a first cut at considering all three channels, using two standard global climate models and a variety of different assumptions about where wind-turbines will be situated, how efficient they will be, and the manner and magnitude of the resulting increase in surface-layer drag. There are plenty of crude approximations made here (for instance, that the increase in drag is uniform over the affected area), but they're recognized as such. The results thus need to be treated with caution, but they are interesting. The second channel (changing atmospheric transport) has a much bigger impact than the first (direct friction); together, under plausible assumptions, they give a near-zero impact on the global mean, root-mean-square change in seasonal means of about one twentieth of a degree centigrade at one point, and peak changes of half a degree. Under further plausible, but of course more arguable, assumptions, the third channel (reduced carbon emissions) swamps these effects, too, by about a factor of five. Interestingly, the configurations for wind power they consider tend to cool the poles and warm the lower lattitudes, while carbon dioxide warming has the opposite effect. This suggests (though the authors don't go there) that we might consider massive wind farms as a pure climate-change moderator, even if they weren't a practical power source from an engineering point of view.
It should probably be noted that the first two sponsors listed in the acknowledgments are British Petroleum and the Electric Power Research Institute.
Posted by crshalizi at July 16, 2006 05:07 | permanent link
I wrote this about a year and a half ago; I'm cleaning out my drafts folder.
There are reasons why one might think that Turkey should not be admitted to the European Union, but surely the silliest must be that Turkish is not an Indo-European language. Following Phersu, I can just imagine the consequences of taking this seriously. First, the Basque-speaking provinces of France and Spain leave the EU, along with Hungary, Finland, Estonia and Malta. But then, of course, India and Pakistan will submit rival applications to join, closely followed, no doubt, by the Iraqi Kurds. The whole idea is so stupid that I can't believe it was meant seriously, or even guess what Giscard d'Estaing thought "Indo-European" meant.
That said, Turkish does have features which are absent or attenuated in (most) Indo-European languages. (Disclaimer: I do not speak Turkish.) For instance, it's highly agglutinative, forming new words by adding suffixes to roots, and doing so recursively. (German does this too, but to nowhere near the same degree.) This leads to words like yapabilecekdiyseniz, "if you were going to be able to do". (Readers may amuse themselves by analyzing this example using the Turkish Suffix Dictionary.) Moreover, these words are not oddities, like "antidisestablishmentarianistic", but in everyday use. I once heard a talk by a computational linguist specializing in Turkish — Gerjan van Schaaik, who oddly seems to have no web presence — where he mentioned that if one studied the corpus of Turkish daily newspapers, one could easily build a lexicon of 500,000 entries, and still cover only 95% of the words in the corpus. (I can't tell, from my notes, whether van Schaaik was talking about something that had actually been done, or just making a rough estimate.) This property of Turkish becomes very important for a number of technologies, including one without which the modern world would simply grind to a halt: spam filtering.
Özgür et al. do not report on the ability of their classifiers to discriminate between spam, and weirdly pseudo-learned pronouncements from former presidents of France.
Posted by crshalizi at July 16, 2006 04:59 | permanent link
Speaking of air travel, as we were, Kara dreams of traveling to the Beijing Complex Systems Summer School.
Alas! She will not be gracing the Fragrant Villa with her presence. Twenty hours in planes and airports would not agree with her temperament, nor would jet-lag be pleasant for one so distressed by any interruption of her accustomed nap cycle.
As for me, I have cleverly worked on my three lectures in reverse order, so the last two are finished...
Posted by crshalizi at July 07, 2006 10:00 | permanent link
Reading this piece in the New York Times about Farecast, Oren Etzioni & co.'s attempt to forecast airline ticket price movements (through the power of machine learning!) leaves me with three reactions.
First, it's a relief to read something about data-mining and airlines which isn't Yet Another Unconstitutional Step Towards a National Surveillance State. In fact, this would be cool if it works.
Second, I'm professionally curious about how well Farecast's predictions, with over 100 independent variables, would compare to simple alternatives, like low-memory hidden Markov models, or throwing out all the variables except the time remaining until departure. (Since I'm teaching data mining in the fall, I'm also professorially curious.) I suspect that, even if there is some real improvement, it is small. Come to that, the trivial predictor which always forecasts a price increase is going to set a pretty high baseline accuracy...
Third, I'll be surprised if does work, not on technical grounds, but because I don't see how it makes sense for airlines to cooperate. The ideal airline pricing scheme is one which gouges you just enough that you're indifferent between taking the flight and not going at all (or taking some alternate mode of transport, etc.). This is why flights at ungodly hours are cheaper than those on the same route at decent times: by showing up at five in the morning to have your luggage prodded, etc., you signal to the airline that they really can't get any more money out of you. [1] Now suppose that you want to take a certain flight, and there's a maximum amount you'd pay for it. As things currently work, you look up the price and see what the airline is currently charging. If that price is less than its value to you, you buy the ticket, and the difference is your "consumer surplus". Now Farecast comes along and says, in effect "sure, you could do that, but the price is going to drop --- hold on and you'll do even better." So you buy when the price hits its trough, and are better thereby. (Yes, some people act like this now, I'd guess not many, and not very successfully.) From the airlines' point of view, however, every dollar by which your consumer surplus grows is a dollar they could have had. ("And I would have gotten away with it, too, if it hadn't been for you meddling KDDs!") Consumers and airlines are engaged in a zero-sum competition over the potential surplus, and this doesn't help the airlines.
Which, again, makes me very puzzled about why they would cooperate with it. The smart move on their side, I think, would be to systematically undermine the reliability of Farecast. This could be done very simply, without even attempting to reverse-engineer the predictor: monitor its forecasts of your own flights, and, all else being equal, do the opposite. It's true that a reliable forecast of a price increase isn't so bad, for the airlines, as a forecast of a price decrease, but systematically jamming and confusing Farecast should be easier than selectively doing so. But I defer to real economists about the importance of this wrinkle.
The larger moral ought to be a familiar one: in strategic interactions, you have to assume that the other side will adapt to you. This doesn't mean that statistical methods have no place in studying strategic interaction (see, e.g., the second paper here), but it does mean we should be very dubious about the ability of simple data mining to give us an advantage over an opponent as smart and determined as a commercial airline.
(Thanks to K. for sending me the article, and discussing it.)
1: If you want to understand the logic of airline pricing, among much else, a great read is Carl Shapiro and Hal Varian's Information Rules: A Strategic Guide to the Network Economy. [I have been sitting on a draft review for seven years now, and am not about to stop.] Despite the very late-1990s title, this is really about the general economic principles involved in any industry where high first-unit costs and low marginal costs give you positive economies of scale, or where there are strong positive network externalities. Airlines are in the first category, because the cost of getting a jet from New York to LA with 100 passengers is almost the same as getting it there with 101 passengers, and is mostly the cost of getting it there empty. Alas, appreciating the rational essence of the process does not help make the lived experience any more endurable.
Posted by crshalizi at July 06, 2006 22:00 | permanent link
Nature, in its wisdom, has compiled a list of the fifty most popular weblogs by scientists. I am more than a bit astonished to see this blog on the list, but my faith in the reading public is bolstered by seeing that it's only in the fiftieth place, and everything ahead of it that I recognize definitely deserves to be. (Via Aetiology [#7] and Pharyngula [#1].)
Posted by crshalizi at July 05, 2006 16:05 | permanent link
I wrote this about a year ago; I'm cleaning out my drafts folder.
As every schoolchild knows, what became the Internet was at first ARPANET, one of the many projects by which the Pentagon's Advanced Research Projects Agency nurtured the development of computer science and technology in the US. ARPA eventually became DARPA, but for a long time retained its character of a patron of basic and curiosity-driven research. Lately, however, it seems to have lost its touch, what with the whole terrorism futures markets debacle, "total information awareness", and so on. (I myself was for several years sustained, as a graduate student and post-doc, by my adviser's DARPA grant, familiarly known as cooperative agreement F30602-00-2-0583, part of the TASK program. Of course, it's not for me to say where our work fell in the spectrum from foundational to flaky.) The sad but predictable response has been to demand that DARPA de-emphasize basic academic research in favor of working with private-sector contractors for short-term military payoff.
All of which is by way of lead-in for this post to the connectionists mailing list:
Postdoctoral position in neurobiology / engineering in Woods HoleA 4-year DARPA research project, funded annually, to steer the behavior of sharks in the natural environment through stimulation of selected sensory brain areas. Expertise in brain stimulation, multi-electrode recording and neural data analysis most desirable. Interfacing with wireless data transmission and stereotactic electrode positioning.
A year earlier, a Boston Globe story had more information, but lacked the admirably matter-of-fact tone of the job-ad.
I don't see much by way of follow-up, but I haven't looked very hard. For all I know, this work is already well on its way to giving us a beloved childrens' classic.
Posted by crshalizi at July 05, 2006 09:55 | permanent link
You make me want to quote the Medium Lobster's cost-benefit analysis of pre-emptively blowing up the moon in my report.
I hope you appreciate what it costs me to resist this temptation.
Posted by crshalizi at July 05, 2006 09:30 | permanent link
From John Hall and Charles Lindholm's Is America Breaking Apart? (pp. 83--90, omitting footnotes):
One thing that has often been held to characterize Americans is the ambiguity, confusion, and "contagious vagueness" of their understanding of political theory. Americans may know, for example, that citizens have rights, but are extremely unclear about what those rights might be; they know Americans are supposed to be free, but not how freedom is limited, or what freedoms are permitted; they know that "all men are created equal," but cannot reconcile that precept with the protection of property. In other words, most Americans are very proud indeed of the principles that their country is built upon, but for them those principles consist primarily of abstract notions, such as liberty, justice, and equality, rather than a systematic set of specific precepts or practices.They go on to talk about why we are so friendly and nice, and why believe that love is the only legitimate bond between people, but I'm skirting the bounds of fair use as it is, even in the interest of patriotic display.The major sources of "contagious vagueness" are to be discovered in the priority Americans have always given to pragmatic experience over philosophical system-building. Under the fluid circumstances of American life, ambivalence and woolly abstraction have certain advantages. ... While remaining faithful to nebulous abstractions of "freedom," "individualism," and "equality," Americans can still be pliable in action without betraying their integrity or finding themselves immobilized by contradiction. Ideological vagueness thus allows Americans to feel a sense of unity without the trouble of actually considering exactly what that unity is based upon.
The abstraction and ambiguity of taken-for-granted foundational principles also allows Americans easily to "hold contradictory ideas simultaneously without bothering to resolve the potential conflict between them." This, too, is not necessarily a bad thing in a pluralistic society, where central authority is relatively weak. The blurry quality of American assumptions about their shared creed allows them to accept innovations easily, so long as the innovations are metaphorically bathed in the aura of tradition, and to react according to circumstances without too much concern about agreement with prior positions. Most important, an ability to ignore contradictions permits Americans to overlook disputes that might tear a more ideologically consistent society apart.
Corresponding to American abstraction and vagueness in the realm of political philosophy is a positive can-do approach to ordinary problems. ... It is no surprise that the predominant American philosophy is pragmatism.... However, what pragmatism takes for granted as "common sense" is actually a culturally constructed perspective, based in large measure on what has recently been called modular thinking. This is a strategy for instrumental action which assumes that complex wholes can be broken into elementary parts; these parts can then be efficiently recombined according to need. Modular thinking is American to the core: it is an atomistic, flexible, anti-organic, and anti-authoritarian view of the world — one which dispenses with tradition in favor of efficiency, and places all alternatives on an equal footing, subject to personal evaluation by the active innovator, who decides which combination is best.
Modular thinking has had a successful history in America. It is responsible for the development of the assembly line and Taylorist innovations in scientific management, and it provides the foundational principles behind everything from the construction of shopping malls to the planning of school curricula. ... [T]he pervasive pragmatic modular approach to life permits Americans to avoid divisive ideological issues by visualizing the world around them as a machine that can be retooled, or taken apart and rebuilt, in order to achieve maximum efficiency. ... Disagreements are not over principles, but over design. Though this mechanistic instrumental worldview may remove much of the magic from the cosmos, and though it certainly does not grasp complex social realities, it is not likely to arouse great passions either — and so is conducive to social peace.
It is especially striking that for Americans even the self is considered to be a kind of modular entity, capable of being reconfigured to fit into preferred life styles. This malleability is often decried as indicating American shallowness, or else praised as the postmodern triumph of the signifier. But the American emphasis on perpetual self-transformation also serves the cause of unity, though perhaps not in the way Protestant moralists would prefer. This is because the search for identity is a notoriously solipsistic pursuit: such quests do not lead to revolution, but to harmless participation in the therapeutic, self-help, and twelve-step groups that have so mushroomed in America. At the very worst, the search for an authentic self draws the most perplexed seekers towards immersion in the multitude of sects and cults that have always sprouted on American soil. Occasionally, it is true, these groups spiral into psychosis ... but generally these new religions are akin to the "healthy-minded," "once-born" faiths that William James found so characteristic of America. They typically affirm the goodness of all creation and preach accommodation with the world as it is, stressing mental discipline, while applying the optimistic American "can-do" attitude to spiritual uplift and practical self-betterment. Membership in them is no more harmful than membership in any local PTA.
American faith in the power of individuals to change themselves is quite understandable as a product of the immigrant experience in combination with the Protestant ethos. Protestant sects believe that individuals can be spiritually transformed through disciplined, virtuous action in this world. For most of the original settlers immigration to America was just such a transformative action, a voluntary pilgrimage in search of the City on a Hill. In secular garb, this model continues to hold: becoming an American is a kind of conversion experience. The newcomer "is not required to learn a philosophy," Daniel Boorstin notes, "so much as to rid his lungs of the air of Europe." This point is not invalidated by the fact that more recent immigrants, male and female, rid their lungs of the air of China, India, and Africa. For all these newcomers, past and present, America has been the "Mother of Exiles. From her beacon-hand glows world-wide welcome." The content of the glowing welcome offered by the Statue of Liberty is not a dogma, but an opportunity. America presents itself as a place where newcomers can achieve their dreams, free at least from the chains of tradition, class, and history...
For the zealous believer of colonial times, the end sought through migration to America was a passage into heaven.... For the modern entrepreneur, the goal is likely to be far more mundane: owning one's own business and acquiring a house in an exclusive suburb. Whether what they sought was spiritual or material, immigrants to America have worried little about conceptual consistency or a systematic organization of principles. Central instead is a belief that individuals have the capacity, through personal effort, dogged discipline, and creative innovation, to leave the past behind, to pursue happiness, and to become whatever their potential allows. Only in America would the Army call on its recruits to "be all you can be."
We can feel the heady appeal of this transformative aspect of American life in a letter sent by a French migrant to California during the Gold Rush:
In the mist of this world of adventurers, who change their occupations as often as they do their shirt, egad, I did as the others. As mining did not turn out remunerative enough, I left it for the town, where in succession I became a typographer, a slater, plumber, etc. In consequence of thus finding out that I am fit for any sort of work, I feel less of a mollusk and more of a man.For such adventurous souls, America indeed offered — and continues to offer — an opportunity for taking on a new and better identity, for making a mollusk into a human being.
Posted by crshalizi at July 04, 2006 17:00 | permanent link
Posted by crshalizi at June 30, 2006 23:59 | permanent link
A year and a half ago, I commenced a major purge of my book collection. A year ago, when I left Ann Arbor for Pittsburgh, I consigned thirty-odd boxes of used books to Corners Bumped, a.k.a. my friends Bill and Barbara Tozier. (This tells you something about the number of books I did end up shipping here.) Recently, they have been refurbishing their online book-selling presence, listing new stuff from my boxes and their own stock, and musing (1, 2, 3, 4) on used books and the trade therein. Go buy something, will you? It will make all of us — you, me, Bill and Barbara, and not least the books — better off.
This concludes today's crass commercial plug.
Posted by crshalizi at June 27, 2006 15:45 | permanent link
Paradoxes and fallacies are fun teaching tools, and elementary courses in probability theory are well supplied with them. I have long thought that more advanced probability classes would be more palatable if we presented our students with more opportunities to go "Wait, that can't be right", and sink their teeth into something really just-plain-wrong. Happily, we now have about ten more such morsels to offer them:
Anyone taking 36-754 from me next spring should expect to see sections 2 and 3 as assignments.
Posted by crshalizi at June 27, 2006 14:00 | permanent link
Kara has a charming habit of secreting herself behind some corner and landing a devastating swipe of her paw on the calves of passers-by. This would be very effective at crippling us, if only she had not been cruelly declawed at some point before we adopted her from the shelter. Today's post, however, will not be about the irreducible intensionality revealed by her desire to bring down prey much larger than herself, nor about the qualia of her phantom claws (which I am convinced she experiences). Rather, I want to talk about the mechanism which brings her paw — and with it her fore-arm and shoulder and the rest of her body — to move just so as to effectively ham-string us. This mechanism is accessible to experimental investigation, and, as it turns out, pretty nearly linear.
To elaborate a little on the experimental procedure: the cats were anesthetized with ketamine, which allowed for surgery to attach sensors measuring electrical activity to eight muscles, as well as brain surgery opening up the motor cortex. They also attached a sensor to the paw, tracking its position in space. Then, maintained on a steady flow of ketamine, the "body of the cat was laid on a cushion with its forelimbs hanging perpendicular to the ground and free to move in all directions against gravity". At this point, they began small-scale, low-current stimulation of the motor cortex, until they identified a number of points each of which, when stimulated, produced a repeatable and distinct motion of the paw and fore-limb. They recorded both the displacement of the paw, and the total activity, over the course of the movement, of each of the eight muscles. Thus, each point in the cortex corresponded to both a three-dimensional vector, in ordinary space, and an eight-dimensional vector, in muscle space.
In a linear system, if you add two inputs, you also add two outputs; this, and nothing more, is what "linear" means. Vectors add according to the parallelogram rule, so if the cat motor system is linear, if we stimulate two points simultaneously, the movement of the paw should be the superposition of the movements produced by either point on its own. I wish I could build some suspense at this point, by harping about how neurons are notoriously nonlinear devices, so it's madness to expect any sort of linearity here, but Ethier et al.'s title rather gives the show away. When they simultaneously stimulated pairs of points, they got paw motions which were almost perfect linear sums of the individual movements. This was true of both the paw-displacement vector, and the muscle-activation vectors. (See especially their figures 2 and 5, and accompanying text.) It didn't matter whether they electrically stimulated both points, or stimulated one point while chemically reducing the inhibition at the other. This is very nice, but what I like even more is the experiment summarized in their figure 7, where they took two cortical points, which produced nearly perpendicular movements on their own, and by varying the magnitude of the stimuli at each, got a sequence of movements which smoothly interpolated between them, exactly as one would hope for a linear control system.
Now, I should say that the linearity of response wasn't perfect. The largest systematic deviations from linearity occurred when summing the individual motions would have produced the largest displacements — in a word, the muscle response saturated. To avoid this effect, Ethier et al. first established an input-output relationship for each cortical point on its own, and kept the stimulus magnitude low enough to avoid saturation there. They suspect the place where the response became sub-linear was in the spinal cord, but they don't, that I can see, really establish it.
There are two different larger morals to be drawn from this story. One has to do with the functional anatomy of the motor cortex (a larger, long-running story nicely presented in an older paper of Capaday's). There is clearly a great deal of localization of function there — this point produces a swiping motion of the paw, that that one pulls it back towards the chest, neither makes the tail twitch — but of a peculiar sort. One might well imagine that each point in the motor cortex would correspond to a particular muscle or group of muscles; instead, at least in the part Ethier et al. worked with, they seem to correspond to motions involving many muscles to varying degrees, overlapping from one cortical point to another. Linearity means that a reasonably small set of motions could serve as a basis for a vast range of coordinated actions, without all of those having to be separately stored in the motor cortex.
The other moral has to do with the general principles of neural representation and computation. Neurons are, indeed, horribly nonlinear little things, so it would be entirely reasonable to suppose that neural codes are too; but that would be too quick. One of the few efforts in this area that is general, abstract and predictive enough that it seems to me to be worth calling a theory, the "neural engineering" advanced by Chris Eliasmith and Charles Anderson in a book of that title, takes as its first principle "nonlinear encoding and linear decoding". That is, while the mapping from input to output is hairy and nonlinear, for typical outputs you can recover the input, to high accuracy, using a linear rule. This is especially easy to arrange in neural systems where excitation and inhibition are neural balanced, so Ethier et al.'s findings on dis-inhibition fit in nicely.
Nonlinear encoding and linear decoding is not just an assumption of Eliasmith and Anderson, but, e.g., features quite prominently in Spikes, and is implicit in the now-standard "reverse correlation" method. While I am not, usually, one to argue with scientific success, I have reservation about this. William James used to decry, as "the psychologist's fallacy", the "confusion of his own standpoint with that of the mental fact about which he is making his report" (Principles of Psychology, ch. 7). Something similar (the "computational neuroscientist's fallacy", perhaps?) seems to me involved here. Neural representations do not exist to be decoded by scientists, but to be used by other parts of the organism, and ultimately to produce adaptive actions. What is lacking, in most of these studies, is evidence that linear decodings of neural activity are in any way biologically relevant. (One of the nice things about Eliasmith and Anderson is they see at least part of this, since their second principle is that other parts of the brain use a neural representation by applying alternately-weighted linear transformations to it, i.e., biased linear decodings. But they present less evidence for this than for their first principle.)
In this case, however, I don't find much room for doubt: the points in the motor cortex represent actions, and those representations are, when the paw meets the calf, linearly decoded. It's still not clear to me that linear decodings and transformations are any easier for the brain to implement, but at least in this case that's what's going on, and it's an empirical fact we will have to incorporate in our models, or ideally explain in our theories.
And now, if you will excuse me, I'm being attacked.
Posted by crshalizi at June 23, 2006 23:40 | permanent link
The importance of coffee-houses in the Enlightenment, and the rise of the public sphere, is a historical common-place. But it's also puzzling: historians can say a lot of sensible things about how, as a social setting, the cafe was conducive to the give and take of (more or less) rational argument, and (relative) indifference to social standing in favor of persuasion. But I've never heard a good story for why coffee houses had to be run that way, nor that (say) taverns weren't, or couldn't have been, run that way. So, while not denigrating the social factor, it doesn't seem to explain why this connection took hold. Now, at last, scientific proof that Enlightenment had a sound material basis (via Mind Hacks):
I should perhaps add that the leap from their findings to the rise of modern rationalism is entirely my own.
Manual trackback: Stephen Laniel; Brad DeLong
Update, 13 June: On the basis of my correspondence about this post, I feel like I have to add that I was not serious. "Differential diagnosis, people" (to quote a great sage and eminent junkie): both coffee and the coffee-house were imported into Europe from the Levant, where the coffee-house developed as a recognizable social form, without triggering a local version of the Enlightenment. For that matter, all the physiological studies point to the influence of caffeine as such, not just coffee, so why not tea? (Though, come to think of it, didn't the proto-scientific and industrial development of the Song dynasty coincide with the rise of tea houses?) No doubt patterns of caffeine consumption have had some effect on culture, and it would be nice if historians could study them, but not like this. I'm a reductionist, but when I toss out simplistic biological explanations for complicated, ill-defined social phenomena, I'm joking, unlike some people.
Also: Ruchira Dutta writes with news of a learned investigation into related questions, A. A. Reade's Study and Stimulants; or, the Use of Intoxicants and Narcotics in Relation to Intellectual Life, as Illustrated by Personal Communications on the Subject, from Men of Letters and of Science (Philadelphia: Lippincott, 1883). As the subtitle suggests, it largely consists of letters from various eminences of the day on their own experiences of using drugs, and thoughts on whether and how drugs are of use to intellectuals. Some of them are quite charming, in a rather prim way. Thus H. H. Bancroft's letter, in its entirety: "In my opinion some constitutions are benefited by a moderate use of tobacco and alcohol; others are not. But to touch these things is dangerous." Or, speaking of the rise of rationalism, Mr. W. E. H. Lecky: "I am not a smoker, and am therefore unable to give you any evidence on the subject." Other correspondents were not similarly inhibited by their lack of first person data, such as Keshub Chunder Sen ("The problem you have undertaken to solve is, indeed, one of intense importance and interest, and all who can ought to help its solution in the interests both of science and morality") or Mr. Ivan Tourguéneff.
Minds, Brains, and Neurons; The Collective Use and Evolution of Concepts; The Great Transformation
Posted by crshalizi at June 08, 2006 17:49 | permanent link
Posted by crshalizi at June 04, 2006 21:30 | permanent link
Posted by crshalizi at May 31, 2006 23:59 | permanent link
Or rather, from Ernest Gellner's Language and Solitude: Wittgenstein, Malinowski and the Habsburg Dilemma (pp. 108--109):
Imagine the conversation of a few Viennese characters, in the Cafe Central, on the assumption that the Tractactus is a correct account of the human condition.[Thanks to Wolfgang for checking my transcription of German titles!]CHARACTER A: High up on the left hand of my visual field, I note a fact in which a 9-value predicate links the appropriate number of things... I don't think I have had this one before, I'd like a snapshot for my collection.
B: I have a much more interesting one right in the middle of my field, a variable with 127 things attached — it has a lot of tentacles, holding those things. I've counted them.
C (to A): Don't you believe him. I have known him for years, he is invariably given to exaggerating the complexity of his facts, just to make himself interesting.
D (to C): I don't think he is deliberately lying, he just drinks too much and then imagines things.
B (furiously, to both C and D): What you have both said is extremely offensive and I have no option but to call you out! My seconds will call on you. That is, assuming you have honour: my fraternity has decreed that Jews have none and we may not duel with them. Is either of you at least half Aryan? That is all one can hope for in Vienna these days.
A: Gentlemen, gentlemen, please calm down. May I remind you first of all that dueling is forbidden by law and, secondly, death not being an event in life, is totally pointless anyway.The above conversation is not copied out of Die letzten Tage der Menscheit or Der Weg ins Freie or Der Mann ohne Eigenschaften or even Radetzky Marsch. It is all my own work and it is copyright.
Posted by crshalizi at May 22, 2006 03:45 | permanent link
Hopefully, it's just jet-lag, but seeing highway signs marked "Wien", "Praha" and "Budapest" makes me feel much the same way one marked "Minas Tirith" would, that something from known only from books has become unsettlingly real.
Posted by crshalizi at May 21, 2006 12:00 | permanent link
Kara has Views about humans working on Friday nights:
Posted by crshalizi at May 12, 2006 17:58 | permanent link
I'm afraid I was a bit premature in announcing my return to posting, since I find my time being taken up by actually doing some science, and being, for the first time, on the sending rather than the receiving end of a qualifying exam. In the meanwhile, let me enthuse about Far from the Madding Gerund, a selection (and annotation) of the best of Mark Liberman's and Geoffrey Pullum's posts from Language Log. Doing a proper review, or even justice to their weblog, is really beyond what I have time for, but this book seems to capture quite perfectly their mixture of whimsy, skepticism, accessible scholarship, and pure good-natured zeal for their subject. If you have been reading them, then you will find these little essays as good as you remembered, if not better, and you'll wonder how you forgot about some; if you have not been reading Language Log, then their book should convince you to start. Either way, reading it will make you better and happier. (Disclaimer: I got an unsolicited review copy of this book this week, which didn't help my productivity any. Also, when I gave a talk at Penn on April Fool's Day last year, Mark was kind enough to let me crash in the hospitality suite at One Language Log Plaza.)
Posted by crshalizi at May 12, 2006 09:40 | permanent link
Two hundred and fifty pages later, it's the last day of classes, and my last lecture in advanced probability is done. (I still need to tex up the one lecture I gave from hand-written notes, but there's no rush.) Looking over the tome, I didn't get to a lot of stuff I wanted to (easily enough for another semester!), it's far from self-contained, and it almost certainly contains mistakes, but I think it's not bad for a first draft. It also took an order of magnitude more of my time than was wise. I'll be teaching the class again in the spring, and hope I'll have the strength of will to leave it alone, rather than succumbing to the temptation to do something.
Posting about science and outrages against common decency will recommence shortly.
Posted by crshalizi at May 05, 2006 15:00 | permanent link
Posted by crshalizi at April 30, 2006 23:59 | permanent link
Posted by crshalizi at March 31, 2006 23:59 | permanent link
Posted by crshalizi at March 24, 2006 12:51 | permanent link
As a member of the program committee for the workshop Statistical Network Analysis: Models, Issues and New Directions, part of the 2006 International Conference on Machine Learning, I urge you to submit your best work by 28 April; you can send us the bad stuff after that. (That, in response to hearing endless variants on "First prize, a trip to Pittsburgh; second prize, two trips", which was old in my grandfather's day.)
CALL FOR PAPERS
Statistical Network Analysis:
a workshop at the
Models, Issues and New Directions23rd International Conference on Machine Learning
Thursday, June 29, 2006, Pittsburgh PA, USA
(ICML 2006)Overview:
This workshop focuses on probabilistic methods for network analysis, paying special attention to model design and computational issues of learning and inference.
Many modern data analysis problems involve large data sets of artificial, social, and biological networks. In these settings, traditional IID assumptions are blatantly inappropriate; the analyses must take into account the structure of relationships between the data. As a result, there has been increasing research developing techniques for incorporating network structures into machine learning and statistics.
Network modeling is an active area of research in several domains. Statisticians have mostly concentrated on models of static networks. These models are concerned with the existence of edges between individual nodes, but do not attempt to model aggregate properties. In contrast, physicists have addressed global properties of large complex networks. Their models describe average statistics of the network, or properties of typical networks in large ensembles; the links between particular nodes are less meaningful.
This workshop aims to bring together statistical network modeling researchers from different communities, thereby fostering collaborations and intellectual exchange. Our hope is that this will result in novel modeling approaches, diverse applications, and new research directions.
We wish to clarify that in this workshop, the word "relational" carries a different meaning from the usual sense of the word in Probabilistic Relational Models (PRMs). For example, in real life, any two random people maybe connected through a complex web of friendships; estimation of interpersonal connections thus cannot be done independently of the rest of the network. We focus on modeling statistical properties of the network, as opposed to different types of probabilistic relations. This differentiates us from the co-located ICML workshop on Statistical Relational Models.
Online Submissions:
We welcome the following types of papers:
We encourage authors to emphasize the role of learning and its relevance to the application domains at hand. In addition, we hope to identify current successes in the area, and will therefore consider papers that apply previously proposed models to novel domains and data sets.
- research papers that introduce new models or apply established models to novel domains,
- research papers that explore theoretical and computational issues,
- position papers that discuss shortcomings and desiderata of current approaches, or propose new directions for future research.
Submissions should be limited to a maximum of 8 pages, and adhere to ICML format. Please email your submissions to: edo [at] cmu.edu.
Deadline for Submissions: Friday, April 28, 2006
Notification of Decision: Friday, May 5, 2006Format:
This is a one-day workshop. It will consist of several themed sessions targeting methodological and application issues (e.g., estimation in static models, network evolution modeling, and statistical modeling of large scale networks) with talks (invited and contributed) and moderated discussion. Discussions at the workshop will facilitate exchanging of research ideas and help identify other challenging problems in the area. At the end of the workshop, a panel of statisticians, physicists, and computer scientists will discuss the points arising throughout the day and identify the most promising and challenging directions.Publication:
Accepted papers will be distributed on a CD and made available for download.Organizers:
Edo Airoldi, Carnegie Mellon University
David Blei, Princeton University
Stephen Fienberg, Carnegie Mellon University
Anna Goldenberg, Carnegie Mellon University
Eric Xing, Carnegie Mellon University
Alice Zheng, Carnegie Mellon UniversityProgram Committee:
David Banks, Duke University
Peter Dodds, Columbia University
Lise Getoor, University of Maryland
Mark Handcock, University of Washington, Seattle
Peter Hoff, University of Washington, Seattle
David Jensen, University of Massachusetts, Amherst
Alan Karr, National Institute of Statistical Sciences
Jon Kleinberg, Cornell University
Andrew McCallum, University of Massachusetts, Amherst
Foster Provost, New York University
Cosma Shalizi, Carnegie Mellon University
Padhraic Smyth, University of California, Irvine
Josh Tenenbaum, Massachusetts Institute of Technology
Stanley Wasserman, Indiana University
Posted by crshalizi at March 18, 2006 15:06 | permanent link
Appearances to the contrary notwithstanding, I did not actually spend all my time in February reading about fascists. In fact, most of my reading was in these books, though I didn't go cover to cover:
Posted by crshalizi at February 28, 2006 23:59 | permanent link
I occasionally dabble in mathematical aspects of neuroscience. My brother does the real thing:
Also check out the accompanying "perspectives" piece.
Posted by crshalizi at February 19, 2006 14:50 | permanent link
will be held at Oxford, 25--29 September. Since I'm on the program committee, I ought to point interested parties to the call for papers (deadline 7 April) and the call for workshop proposals (deadline 5 May).
Posted by crshalizi at February 17, 2006 11:45 | permanent link
Posted by crshalizi at January 31, 2006 23:59 | permanent link
I seem to have locked myself into writing five pages of math textbook three times a week between now and the end of the semester. If I am to pull this off while still doing research and have something like a life, I can't spend any time posting here, or even really reading weblogs. So I'm putting this on hold until after May 5th, and deleting my RSS reader for the duration. (I will keep updating the book log in the side-bar, though.) Regular service will resume once school's out, and in the meanwhile you can get along without me for three months.
(There, that should be sufficiently emphatic to discourage backsliding.)
Posted by crshalizi at January 30, 2006 20:24 | permanent link
Attention conservation notice: Over 6000 words of dubious value. Written as a contribution to the Valve event on Franco Moretti's Graphs, Maps, Trees. Contains advice to literary scholars from someone utterly unqualified to give it, hypothesis testing, rastergrams, many long quotations, and ruminations on materialism and rational history. If this is the sort of thing you're interested in, you'd really be better off reading Moretti yourself.
Cross-posted to the Valve, where there is a comments section. I can't promise to reply...
A few years ago, I wrote a review of Moretti's Atlas of the European Novel, in which I presumed to tell him how to go about his business. When he ran across it, his reaction was not (as mine would've been, had our situation been reversed) to tell me where to get off, but to invite me to a workshop he was organizing at Stanford on new interdisciplinary work on the novel — its motto, the quotation from Brecht about "questions that appear to us completely unsolved", is recycled for this book — where I had a great time. Reading these essays as they came out in New Left Review, I enjoyed them greatly, and recall thinking that Moretti could hardly have done a better job of appealing to my prejudices if he'd tried. (Said prejudices are those of someone almost equally fond of The Extended Phenotype and Main Currents of Marxism.)
With this kind of background, it comes as no surprise, I trust, that I really like this book, and finding objecting to what he actually proposes here highly wrong-headed. In what follows, I want to say a bit about "graphs" and a bit about "trees", and explain why this sounds so promising to me. I am not going to say anything about "maps", because I don't think I have anything to add to that discussion, but I will, for the sake of getting an M in there, end with some remarks on "materialism". At no point can I pretend to be competent to evaluate the originality of Moretti's work within literary scholarship, to say how much of a departure, say, the trees really are. In a feeble attempt to pretend that my price is higher than a weekend in California and a review copy, I will make some criticisms, most about tedious extra stuff I wish Moretti had also done. I'd like to think that what I say will also have some value for those who don't share my rather haphazard intellectual trajectory, but my experience with trying to communicate across disciplines means I'll get a warm glow if I'm even comprehensible, never mind persuasive. I am accordingly very grateful to the Valve, and especially to Jonathan Goodwin, for letting someone with my credentials (viz., none) participate in this event.
Let's be a little more precise about what we'd mean by "chance" and "coincidence" here. One natural possibility is that new genres appear at a constant rate over time, utterly independently of one another. Every year, then, there would be a constant probability of a new genre forming, but whether it did or not would have no bearing on whether the next year saw a new genre. This is our null model — the one which says what things should look like if we're just fooling ourselves, and there are no clusters. To get slightly technical, the distribution of intervals between genre-arrivals should have what's called a geometric distribution. Assuming, for the sake of argument, that that's true, we can use the average time between genre-appearances (3.44 years) to estimate the most likely value for the probability of a new genre appearing in any given year (about 29%).
Once we assume that the inter-arrival distribution is geoemtric and find the parameter, we can simulate from it, and get examples of what Moretti's graph would look like, if only chance were at play.
|
| The top line shows the appearance dates of Moretti's 44 genres; the next two lines give the results of simulating from a model of uniform random appearance, with the same mean time between genres as the actual history. |
Is there more clustering in reality than in the results of the null model? I couldn't say, by eye, but I don't have to. I can calculate the probability of generating Moretti's history from the null model: it's somewhat less than 1 in 10^45. This in itself isn't decisive, since any particular history becomes less and less probable as one considers longer and longer intervals of time (cue Stoppard), so we need to know what fraction of all histories of that length are at least that unlikely. I could work this out exactly, if I were willing to do some actual math, but I'm lazy, so I just had the computer simulate a million histories and evaluated all of their likelihoods. If the null model were actually true, we'd see histories like Moretti's only about 0.4% percent of the time. [1] So this is actually pretty good evidence that the null model is not true, and Moretti's history does show the kind of clustering he thinks it does.
Of course, this only underlines the question of why Moretti's data is clustered. I can think of a couple of deflating explanations (maybe the clusters match the periods more intensely scrutinized by historians; maybe they tend to adjust when they report genres appearing towards certain focal dates). Or it could be due to some sort of exogeneous influence, from war, politics, economic shifts, etc. (I did not try removing the obviously-topical genres, like Chartist novels, and repeating the analysis.) Or it could be due to some sort of endogenous mechanism within the system of literary production and consumption — generational turn-over of authors, of readers, of editors and publishers (suggested by my friend Bill Tozier). Or: maybe there's some space of things-people-like-in-novels, which the popular genres at any one time partition up in various ways; if one genre dies out or another appears, this might destabilize all the others as well. I don't think Moretti's time series, by itself, is enough to begin to let us decide among these mechanisms (some of which are compatible), but I do think it lets us see that some mechanism is called for.
Here is my first reproach: Moretti should have been the one to do this analysis, not me. If testing hypotheses is too banausic and mechanical for the pages of New Left Review, then it should either be in another article, or in the book. Moretti is a shrewd man, and in this case his intuitive analysis of the data was right, but there is no reason to rely on intuition alone for something like this. And, if one is going to go to the trouble to collect quantitative data, one ought to use it quantitatively. Mathematical abstraction (quantitative or otherwise) is not valuable for its own sake, but for the inferences it lets us make, when the proper tools are applied. In this case, those tools are pretty easy to bring to bear. They should be.
Here is Moretti at the end of "Graphs":
For most literary historians ... there is a categorical difference between 'the novel' and the various 'novelistic (sub)genres': the novel is, so to speak, the substance of the form, and deserves a full general theory; subgenres are more like accidents, and their study, however interesting, remains local in character, without real theoretical consequences. The forty-four genres of figure 9, however, suggest a different historical picture, where the novel does not develop as a single entity—where is 'the' novel, there?—but by periodically generating a whole set of genres, and then another, and another... Both synchronically and diachronically, in other words, the novel is the system of its genres: the whole diagram, not one privileged part of it. Some genres are morphologically more significant, of course, or more popular, or both—and we must account for this: but not by pretending that they are the only ones that exist. And instead, all great theories of the novel have precisely reduced the novel to one basic form only (realism, the dialogic, romance, meta-novels...); and if the reduction has given them their elegance and power, it has also erased nine tenths of literary history. Too much.
On the one hand, this seems to me to be obviously correct. On the other hand, I wonder very much why Moretti stops here. If we look within any one of those forty-four genres, I think we have every reason to suppose that we'd find it composed, in its turn, of sub-genres, and so on, and ultimately of a shift succession of individual texts. "The" Bildungsroman (to pick one of the forty-four, not entirely at random) is a short-hand way of referring to the most common and enduring features of a historically-changing and always-various population of books, just as "the" bottle-nosed dolphin is an abbreviation for the leading tendencies of a certain population of organisms. What Moretti hints at, in the paragraph I quoted, is that "the" novel is itself a population, either of genres, or of texts structured into genres. But he doesn't say outright what seems very plain to me, and so I'd like to know why, and specifically whether he thinks it's actually wrong, or unhelpful.
The assumptions of population thinking are diametrically opposed to those of the typologist. The populationist stresses the uniqueness of everything in the organic world. What is true for the human species—that no two individuals are alike—is equally true for all other species of animals and plants. Indeed, even the same individual changes continuously throughout its lifetime and when placed into different environments. All organisms and organic phenomena are composed of unique features and can be described collectively only in statistical terms. Individuals, or any kind of organic entities, form populations of which we can determine the arithmetic mean and the statistics of variation. Averages are merely statistical abstractions, only the individuals of which the populations are composed have reality. The ultimate conclusions of the population thinker and of the typologist are precisely the opposite. For the typologist, the type (eidos) is real and the variation an illusion, while for the populationist the type (average) is an abstraction and only the variation is real. [2]
This makes salient the question of how we mark off different populations as distinct. The usual biological criterion is through common descent, and the possibility of inter-breeding —- Mayr's "biological species concept". (There is a vast controversial literature on the details.) Ruth Garrett Millikan has a closely related notion of "reproductively-established families", which doesn't lean so heavily on the details of biology, and which would seem to fit the case of genres of novels. One could also define classes of texts purely morphologically, which might include many unrelated lineages (just as one might consider all streamlined marine predators which live in the water all the time, a class including dolphins, killer whales, sharks, tuna, ichthyosaurs, etc.). Just as such organic forms have appeared in several lineages, morphologically-defined categories could appear in multiple places and periods, the way novels arose, apparently quite independently, in both the Hellenistic world and in China (and elsewhere, for all I know). Historical populations, however, are unique.
One could ... take evolutionary bibliography as the prototypical evolutionary science and think of biology in terms of bibliographic analogies... [3]
In his comments on the links among capitalism, Protestantism, and Catholicism Marx set a disastrous precedent for many later writers who have attempted to find "structural homologies" or "isomorphisms" (two fancy terms for "similarities") between economic structures and mental products. Because virtually any two entities can be said to resemble each other in some respect, this practice has no constraints other than the inventiveness of and ingenuity of the writer: There are no reality constraints and no reality control.
Marx suggests two inconsistent lines of argument. One is that there is a strong connection between mercantilism and Protestantism, the other that there is an elective affinity between mercantilism and Catholicism. He was confused, apparently, by the fact that money has two distinct features that point to different religious modes. On the one hand, money (gold and silver), unlike credit, can be hoarded. Hoarding easily turns into an obsession, which is related to the fanatical self-denying practices of extreme Protestantism. On the other hand, money can be seen as the "incarnation" or "transubstantiation" of real wealth. In that sense the money fetishism associated with mercantilism is related to the specifically Catholic practice of investing relics and the like with supernatural significance. Both arguments are asserted several times by Marx, each serving to show up the essential arbitrariness of the other. Later attempts to explain the theology of Port Royal, the philosophy of Descartes, or the physics of Newton in terms of similarities with the underlying economic structure are equally arbitrary. Like the analogies between societies and organisms that flourished around the turn of the century, they belong to the cabinet of horrors of scientific thought. Their common ancestor is the theory of "signs" that flourished in the century prior to the scientific revolution inaugurated by Galileo — the idea that there are natural, noncausal correspondences between different parts of the universe. What Keith Thomas refers to as the "short-lived union of science and magic" maintained a subterranean existence of which the doctrine of ideology, in one of its versions, has been one manifestation. [4]
Even if we shutter and lock the Cabinet of Horrors, and go to look for
explanations of trends in such cultural products as novels (which is, after
all, what Moretti wants), I'm afraid we will find most of them in the capacious
Closet of Mildly Appalling Objects. There is no shortage of attempts to give
such changes meaning as signs of something else, some aspect of the social or
economic structure, of the way we live now (or the way they lived then), but
very, very few of them are convincing. In his great book on changing
fashions, A
Matter of Taste, the sociologist Stanley Lieberson looks at some of
the reasons why these attempts at ad hoc explanation are so often bad.
(He puts things more politely; I paraphrase.) First, the facts are often just
screwy, both about the developments to be explained: non-existent trends,
non-existent causes, weirdly mis-characterized trends, trends being explained
by events which happened long after the former began, etc. (In fairness, such
"scholarly
misconstruction of reality" is a lot more common than we academics like to
think.) Second, the mechanism connecting the explanatia to the
explananda is left totally obscure. Third, no attempt is made to test
the explanation, by checking that it can account for the magnitude of the
observed change, by ruling out alternative explanations, or by much of anything
else. The result is a steady stream of claims about how culture works which
are advanced with what is, under the circumstances, an astonishing degree of
assurance. Lieberson's
book provides many fine examples of such cavalier just-so story-telling for
names, the decline of hats, etc. [5]
Checking hypotheses about causation, and still more about adaptation, is really hard with just one case, arguably hopeless. What you need is the ability to reliably detect departures from the hypothesis, if they are actually present — "power", in the statisticians' jargon. It is hard to get much power when n=1. If you want to claim that certain aspects of 19th century British novels were the way they were because those features fitted with ideologies of British imperialism — a fairly strong hypothesis about adaptation — I don't see how you can do it just by interpreting Mansfield Park, no matter how subtle and sophisticated your reading. On the other hand, if you look at lots of contemporary novels, and the ones which (say) depict Great Britain's relations with its colonies in the same way as Mansfield Park does are systematically more successful, on average, than those which depict it differently, well then I don't see how that couldn't be good news for your idea, though even that would really only be the beginning of backing it up.
Biologists have given a lot of thought to checking hypotheses about adaptation, and developed many means of doing so. Mutatis mutandis, many of these means could also be applied to literature, or other aspects of culture. Eric Rabkin, Carl Simon and their collaborators have started doing just this with their Genre Evolution Project, looking at short stories from 20th century American science fiction, and no doubt there are others doing this kind of thing too.
One way of checking adaptive hypotheses, especially relevant here, is the "comparative method", or rather methods, which work much, much better when combined with good phylogenies. I think a literary historian who wants to study the evolution of genres and devices would be very well advised to look at the comparative methods biologists employ to study the evolution of qualitative characteristics of organisms. (The major issue would be that literary phylogenies will not be trees but more complicated lattices. But this is analogous to the effects of lateral gene transfer, common among bacteria, and so I'd suspect not only solvable but solved, someplace in the literature. Whether inheritance is by means of discrete-valued, particulate factors, i.e., genes, is not a crucial issue for such methods.) What I really want to see from Moretti (or someone) is a study along these lines of clues in the detective story; I'd be even more interested in one of free indirect discourse.
A crucial aspect of testing hypothesis about adaptation is a contrast with the outcome of a well-crafted neutral model — a way of saying what to expect if no adaptation were present, or not that adaptation anyway. These often have surprising consequences; for instance, neutral genetic drift will tend to fix some version of a gene in a given population, even if it confers no fitness advantage. (This is described in any book on population genetics.) So I wonder about things like whether we should expect, under a reasonable neutral model, that some formal device should become universal within a genre? If so, did clues take over detective stories any faster than neutrality would predict? (It's hard to imagine a successful genre where every story relies on confessions found by accident, but whether that's intrinsically weirder than actually existing detective stories, I can't say.)
The foregoing shouldn't be taken to mean that comparative literature should slavishly imitate comparative biology. There are people who have thought about the application of evolutionary ideas to social and cultural change in ways which are much more sophisticated about psychology, social organization and human interaction than (most) advocates of memetics; I am thinking particularly of David Hull, W. G. Runciman, Dan Sperber, Stephen Toulmin's great The Collective Use and Evolution of Concepts, and even the fragmentary MS. of Adam Westoby. As the economist Richard Nelson writes, we should expect our ideas of general evolution to change as we learn more about cultural evolution. We should also expect to have to develop different methods of data analysis. But, as always, we start with what we already know how to do.
I share Moretti's hope for a "materialist sociology of literary form"; Hell, I'd like a materialist sociology of culture generally. But I suspect it won't be able to do everything he wants it to.
When Moretti quotes D'Arcy Thompson on how the form of an object is a diagram of the forces which produced it, I'm happy to go along, and even happy to agree that this gives us some ability to work backwards, from form to force. But this sort of inverse problem generally doesn't have a unique solution, especially if some of the forces were transient and highly contingent... Less metaphorically, something Lieberson argues very convincingly is that we often have to distinguish between the social forces causing there to be a change in some taste, and those which shape the content of the new taste. Often the latter mechanisms are more or less internal to the bit of culture in question, like ratcheting. Or: culture doesn't have to express or reflect the social order. I suspect Moretti would be disappointed if this were the case for, say, genres of novels. Well, so would I. But this needs to be checked. One way would be to try to develop good neutral models, and see whether, and where, they break down
Dan Sperber has a great essay, in his Explaining Culture, on "how to be a genuine materialist in anthropology", where he complains about treating Capital, the World-System, cultural symbol-systems, mentalities, etc. as reified causal forces, if not self-interested foresightful agents, forgetting that human history, society and culture are actually "real individuals, their activity and the conditions under which they live" (to appropriate a once-famous line). It seems, at least to this interested outsider, that the study of literature in society suffers from this, too. And I think what Sperber advocates there should go here, too: give actual causal accounts of how macroscopic patterns emerge from the interaction of many material bodies (notably, people and books), of the sort we know to exist, endowed with the kinds of abilities we know them to have.
This commitment may sound harmless, because contentless, but it does actually have implications. It means that you have to do a lot of work to justify functionalist explanations (though it's not impossible). It should make you very dubious about ideal types. It should make you more interested in exploring variation, and not dismissing it. It should make you very dubious about "practices" and other shared mental objects, at least as ordinarily conceived. And it suggests a lot of productive directions, investigating communication, cognition, and the collective patterns they produce.
In Graphs, Maps, Trees, as in his Atlas, Moretti is basically looking at the communication end of things. He doesn't say much about cognition, or individual thought more generally. Elsewhere (see e.g. Signs Taken for Wonders) he has dabbled in psychoanalysis, but I hope that's past. A materialist theory of literary form will ultimately have to concern itself with the organic processes of reading and composition, but the way to do this is through empirical study of readers and writers, not more interpretation of texts, or armchair ruminations (whether those are on the primal scene, the environment of evolutionary adaptation, or conceptual blending). Of course literary scholars have been making stabs in this direction at least since Richards's Practical Criticism, but with the advent of cognitive psychology this can be done in a much more systematic way, combining modeling of cognition with experimental tests of the models. [6] Again, many people (e.g., Jerry Hobbs, Herbert Simon) have been proposing this for some little while, but it's only recently, with works like Bortolussi and Dixon's Psychonarratology, that people have begun to actually do it, taking the predictions of various theories of narrative, which say that changing stories in certain ways should affect readers' responses, and seeing whether that's actually right. This, and not desk-bound speculation about analogies, seems to me the proper way to start on a cognitive psychology of literature. It is obviously complementary to what Moretti wants to do, and (this is the sweet part) the two enquiries can be pursued in parallel; neither has to wait for the other.
One thing Moretti does not do, anywhere, is construct models linking interacting individual behavior to aggregate patterns. Economists and sociologists already make such models, and anthropologists are starting to do so. It may be premature here, but ultimately it will be vital. If different social groups have different beliefs, is that because those beliefs express their relations to the mode of production, or is it because they tend to talk more with in the group than across group boundaries? Adaptationist theories of culture tend to go for the first choice, but we don't really know whether the latter could account for the specific patterns of cultural difference and change that we see.
What I said above about not mindlessly imitating biology deserves some amplification.
Evolution ought to have a bad name in the study of literary history. Reading Rene Wellek's "The Concept of Evolution in Literary History" (or his article for the Dictionary of the History of Ideas) is actually quite depressing. (It brings to mind Kurt Vonnegut's line "they deserved to fail, because they were all so stupid".) The many post-Darwinian ventures in this direction went, essentially, nowhere, at least as far as understanding literature better goes. It surely didn't help that their understandings of biological evolution were often very bad, generally some kind of Spencerian or even Lamarckian belief in tendencies of progressive development — perhaps inspiring, but hopelessly un-explanatory. (This has vitiated far too much evolutionary theorizing about social processes; cf. Toulmin's chapter 5.) As for the more recent wave, since the 1980s, the people who seem to think that literature exists because humanity craves dramatizations of Daly and Wilson's Sex, Evolution and Behavior drive me up the wall. (Their idea makes no sense even if you are very sympathetic to evolutionary psychology, which I am.)
Which said, this is not at all what Moretti is proposing, and I don't see the harm in trying to make this all fit together as another instance of a general pattern, alongside biological evolution, because they have similar causally-relevant features, and so similar mechanisms are at work. Many people have pointed out, in some detail, that explaining biological processes through the joint action of variation and selective transmission in populations is one instance of a general pattern of historical explanation; Toulmin is particularly clear on this [7]. There is a demography of businesses, of interest groups, even of medieval manuscripts of classical works, and so why not one of literary texts? Inheriting discrete, particulate hereditary factors from a small, fixed number of immediate ancestors is not the sine qua non of this form of historical explanation, though the details of the process of inheritance will very strongly affect the character of the resulting dynamics. It might be that theories of literary change cast in this form are too complicated to be useful, or that we just don't know enough yet to find the useful ways to formulate them. But it wouldn't hurt to seriously try, and we'd learn a lot, no matter the eventual outcome.
One way to take the bit from Braudel about "a more rational history" that Moretti adopts as a motto is simply to hope that literary history will be a rational enterprise. There are various aspects to this — the accumulation of knowledge, a desire to give explanations, a realization that more than one explanation might be possible and a desire to check which one is right, and so on. To do all this, it's important to develop, use and refine reliable methods of inquiry — ones which are unlikely to lead you into error, and where errors are apt to be self-correcting. You want to be able to persuade others, and you want to know that you're not just persuading yourself. As a statistician, my job is to help with that bit, so it looms large for me. I think this is more or less what Moretti has in mind when he talks (elsewhere) about wanting "falsifiable" literary history — for ideas which have enough content that they can not only be communicated from one person to another (without tripping Liberman's detector), but checked. Which said, I wish that here, as in his Atlas, Moretti had done a more systematic job of checking his conclusions. Would it be unfair to suggest that, while he sees the need for data analysis, it will be left to a successor generation to put it into routine practice?
If you want to say that asking literary history to be communicable, testable and reliable is asking it to be scientific and that's icky, well, it's a free country (at least for now). The more I think about what makes something a science, the less that seems like an important question. But whether something is a rational enterprise of inquiry matters. I'm sure it's possible to object to wanting history to be more rational in this sense, but I find that thought so alien and pointless I won't even try to engage it.
Another take on "rational history" is that the vast mass of details in small-scale history are essentially random, or, more exactly, the connections among them are as convoluted and involved as the details themselves. (This is one way to define randomness, mathematically.) But looking at larger scales, the randomness averages out, leaving regularities which are simpler and more nearly comprehensible by finite minds, and more reliable. As a statistical physicist and a statistican, I am the last to disagree: "In fact, all epistemological value of the theory of probability is based on this: that large-scale random phenomena in their collective action create strict, nonrandom regularity." [8] The small-scale details of literature and of human life have an intrinsic interest and value that is missing from the small-scale detail of molecular chaos, so there is certainly all the room in the world for what Moretti would like to do and close reading, and even essayistic appreciation. (But there is not, I am afraid, room enough in the world for Harold Bloom.) Whether there is room in an academy organized around the production of peer-reviewed research findings for all of them, is fortunately not a question I need to have an opinion on.
Finally, you might be tempted to go from the last sense of "rational" to supposing that large-scale history must be the working-out of some scheme which is "rational" in that it's really deterministic, or even teleological. This would be a mistake. It is not at all hard to give examples of stochastic processes which combine random evolution and feedback, which converge on very nice large-scale regularities, but which regularity they converge on is completely random and indeterminate. [9] Brian Arthur, among others, argues that processes like this are important in the evolution of technology. Is literature like that? I have no idea. But I don't see any reason it can't be, and this needs to be borne in mind.
Let me close by quoting the same paragraph twice, once from the version in NLR, and then again from the closing pages of the book. In both cases, he is enumerating themes which stretch across his chapters.
First, a total indifference to the philosophizing that goes by the name of 'Theory' in literature departments. It is precisely in the name of theoretical knowledge that 'Theory' should be forgotten, and replaced with the extraordinary array of conceptual constructions, —theories, plural, and with a lower case 't'—developed by the natural and by the social sciences. 'Theories are nets', wrote Novalis, 'and only he who casts will catch'. Theories are nets, and we should learn to evaluate them for the empirical data they allow us to process and understand: for how they concretely change the way we work, rather than as ends in themselves. Theories are nets; and there are so many interesting creatures that await to be caught, if only we try.
First of all, a somewhat pragmatic view of theoretical knowledge. 'Theories are nets', wrote Novalis, 'and only he who casts will catch'. Yes, theories are nets, and we should evaluate them, not as ends in themselves, but for how they concretely change the way we work: for how they allow us to enlarge the literary field, and re-design it in a better way, replacing the old, useless distinctions (high and low; canon and archive; this or that national literature...) with new temporal, spatial and morphological distinctions.Whether this pragmatic message is what Novalis meant, I have no idea; I only know the line because Popper used it as the epigraph for The Logic of Scientific Discovery. But that's what Popper meant by it, and I think it's right, and I look forward to seeing the coelacanths and tube-worms and giant squid which will be brought up from the deeps in years to come.
[1]: More on testing the null model of genre appearance, for those into that kind of thing: Really, of course, the most suitable null model for random appearance would be a continuous-time Poisson process. Since the data are discretized by years, however, I'm faking it by using a geometric distribution of inter-arrival intervals. (I also tried simulating from a Poisson process and then discretizing the result; the results weren't much different.) The only parameter of such a process is the mean inter-arrival time, or equivalently the "intensity", the probability per year of producing a new genre. Simple maximum likelihood estimation gives this as 0.2905405, which implies a log-likelihood for the original data of -103.9498. To evaluate the significance, I generated 1,000,000 sample paths, of the same length as Moretti's, and then for each one re-estimated the intensity and used that to evaluate the log-likelihood. (This sort of "bootstrapping" should account for the fact that I fit that parameter to the data in the first place. It wouldn't be appropriate if, say, Moretti had advanced the conjecture that the mean inter-arrival time should be 10 years on independent grounds.) Of the 1,000,000 sample paths, only 3,802 had log-likelihoods as small or smaller than the original data. That is to say, if the null model were correct, we'd see results like this only about 0.38 percent of the time. So we can certainly reject the null model at the conventional 5 percent significance level, or even the 1 percent level, and in fact this is a considerably more severe test than that.
[2]: Ernst Mayr, What Evolution Is, p. 84, quoting a 1959 paper of his own.
[3]: This is from Sidney Winter's article on "Natural Selection and Evolution" in the New Palgrave Dictionary of Economics (1987), where he works out the analogy in some detail.
[4]: An Introduction to Karl Marx, pp. 183--184.
[5]: "Adventures of a Man of Science", Elif Batuman's wonderfully-titled review of Graphs, Maps, Trees in n+1 magazine, is a quite nice essay, but it also provides what looks like a typical example of the kind of mere plausibility I have in mind:
Perhaps the Holmes stories are not half-baked versions of the "correct" mystery story, but a different kind of mystery story, wherein the nondecodability of clues is not a bug, but a feature. Conan Doyle was writing during the conquest of England by industry and rationalism; perhaps his readers wanted stories about the kinds of magic that are possible within the constraints of science. Holmes categorically rejects the supernatural, not in order to show that the new, rational rules preclude magic, but in order to show that you can still have magic even if you play by the rules. Decodable clues came a "generation" later, with Agatha Christie and the first World War, and became more rigorous after the second—by which time readers wanted to be reminded that the world was still rational. [pp. 146--147]First of all, it seems bizarre to say that Britain was being conquered by "industry and rationalism" in the 1890s, long after the scientific revolution, the Enlightenment, the Industrial Revolution and all its social consequences, utilitarianism, etc. (Indeed, Mr. Lecky might want to have a few words...) Second, Batuman gives us no reason to think that contemporary readers saw what Holmes did as (pardon the phrase) magic within the bounds of reason alone. Third, even if she were right about the social situation and the cultural product, the hypothesized causal connection is really just another arbitrary analogy, of the sort Elster complained about. Suppose Conan Doyle had been better about using decodable clues than Christie. Would it not then sound just as plausible to say this expresses the triumph of rationalism, followed by a post-war weakening? As it is, Batuman's account seems to appeal, implicitly, to a desire to hang on to older ways of thinking. Either the whole reading public of Britain in the 1890s is being treated, in a grossly anthropomorphic fashion, as a single person, with such a desire, or she is making a quite specific prediction about which readers Conan Doyle appealed to, one which does not seem especially plausible, though it might be tested. (It is utterly unclear whose purposes or needs are invokes by the in-order-to's — Conan Doyle's? his original readers'? society's? — but I fear the worst.) Finally, no attempt is made to check that this is the source of the appeal, nor that the later strict decodability of clues really was caused by the World Wars, for the reasons given. I don't know enough to say that this suggestion is false, or that checking it would be impossible. I don't even want to suggest that a book review in a little magazine would be a good place to do such tests. But it doesn't seem to worry Batuman that there is no support for this idea (yet). — Let me repeat that I like the essay.
[6]: Incidentally, thinking that cognition is computational, and even that its computational architecture is strongly constrained by organically-evolved developmental processes, in no way commits one to denying that thought is also profoundly cultural and historical. Sperber is very good on this, but also see Frawley's Vygotsky and Cognitive Science, or the papers collected in The Elements of Reason.
[7]: Of course it isn't the only pattern of successful historical explanation. Even within the natural sciences, geology and astronomy provide very different ones.
[8]: Gnedenko and Kolmogorov, Limit Distributions for Sums of Independent Random Variables, p. 1.
[9]: More exactly, there are stochastic processes ("urn schemes") where the relative frequencies of different outcomes are guaranteed to converge, with 100% probability, but the ratio at which they converge is itself a random variable, not determined by the initial set-up in any way. The models of lock-in developed by Brian Arthur and his collaborators in the 1980s are urn models, but actually less indeterministic than the classical ones.
Manual trackback: Reprieved; Crooked Timber; Pedantry; Three Quarks Daily; Idiocentrism; An Unenviable Situation ("deeply offensive").
Update, 7 February: Seth Edenbaum has more on why he dislikes this post so much — and why he dislikes me (or at least my online persona; I don't believe we've ever met). I think he's wrong, both about this and about me, but it's only right to point to criticisms.
The Commonwealth of Letters; Writing for Antiquity; Biology; Enigmas of Chance
Posted by crshalizi at January 24, 2006 16:20 | permanent link
I've started putting the notes for my lectures on stochastic processes (36-754) online at the course homepage.
In the staggeringly-unlikely event that anyone wants to keep track of the course by RSS, this should do the trick.
Posted by crshalizi at January 18, 2006 12:00 | permanent link
The last time I did one of these things, my weblog broke, resulting in a several-month hiatus. But, since you asked, and since this lets me procrastinate working on my lecture notes, my research, my house and my contribution to the Moretti event at the Valve all at once...
Posted by crshalizi at January 17, 2006 10:49 | permanent link
My father-in-law passed away last month. Here is his obituary.
I wasn't lucky enough to know Jim before his illness; even so, he was one of the most vital people I've ever known, eager to embrace all life's possibilities. He was a man of considerable talents in many directions, of curiosity and accomplishment. A holder of strong opinions, he respected them in others, even when he disagreed. His love for those who mattered to him was sincere and profound. If I had to bear the same burden, I hope I would have it in me to do so with as much fortitude.
That burden has, at last, been lifted from him. I miss him. I'm going to keep missing him.
Posted by crshalizi at January 05, 2006 10:00 | permanent link
... is a fascinating area of inquiry, containing a small quantity of outstanding work, surrounded by a vast expanse of rubbish. This is your chance to help improve the ratio, if you can fit your contribution into six pages by February 28th.
Workshop on the Evolution of Complexity
June 3rd, 2006, Bloomington, IN, USA
as a part of the
Tenth International Conference on the Simulation and Synthesis of Living Systems: ALife XThe evolution of complexity is a central theme in Biology. Yet it is not without any ambiguity. Complexity has been used to refer to different things. For instance, complexification has been interpreted as a process of diversification between evolving units or as a scaling process that is related to the idea of transitions between different levels of complexity. Other meanings of complexity have been introduced, both inside and outside the realm of Biology. What concerns most researchers is to get insight into the mechanisms that produce their notion of complexity.
The focus of this workshop will be on biological interpretations of complexity and the driving mechanisms: primarily we want the focus to be on evolutionary and related dynamics as mechanisms for producing complexity. Furthermore, we want to bring together historical and novel research in this context.
Questions to be addressed at the workshop include:
- What are the environmental constraints of complexity growth in living systems?
- What is the origin and role of developmental mechanisms in evolution?
- Are the principles of natural selection, as they are currently understood, sufficient to explain the evolution of complexity?
- What are the limits at different levels to the evolution of complexity, and which conditions could reduce evolved complexity?
- <Which models are | What language is> more appropriate to <understand | speak about> the evolution of complexity in living systems?
- How could complexity growth be measured or operationalised in natural and artificial systems?
- How can data from nature be brought to bear on the study of this issue?
- What are the main hypotheses about complexity growth that can actually be tested?
- Is it possible to <direct|manipulate> the evolution of complexity, or which benefits would bring its understanding?
See the full call for papers for more information about submission, publication, peer-review, etc. (I am on the program committee, which means I will be one of the reviewers.)
Posted by crshalizi at January 03, 2006 17:52 | permanent link
