idiolect

Stephen C. Stearns provides Some Modest Advice for Graduate Students which is punchy and useful:

?When you first arrive, read and think widely and exhaustively for a year. Assume that everything you read is bullshit until the author manages to convince you that it isn?t. If you do not understand something, don?t feel bad ? it?s not your fault, it?s the author?s. He didn?t write clearly enough.

?Nothing elicits dominant behavior like subservient behavior. Expect and demand to be treated like a colleague. The paper requirements are the explicit hurdle you will have to jump, but the implicit hurdle is attaining the status of a colleague. Act like one and you?ll be treated like one.

?To learn to think, you need two things: large blocks of time, and as much one-on-one interaction as you can get with someone who thinks more clearly than you do.

?Describe your problem as a series of subproblems that can each be attacked in a series of small steps. Devise experiments, observations or analyses that will permit you to exclude alternatives at each stage. Line them up and start knocking them down. By transforming the big problem into a series of smaller ones, you always know what to do next, you lower the energy threshold to begin work, you identify the part that will take the longest or cause the most problems, and you have available a list of things to do when something doesn?t work out.

And my favourite bit

?Pick a date for the presentation of your thesis and work backwards in constructing a schedule of how you are going to use your time. You can expect a stab of terror at this point. Don?t worry ?it goes on like this for awhile, then it gradually gets worse.

He also recommends the excellent style guide by Strunk (rather forcefully: Buy and use a copy of Strunk and White?s Elements of Style. Read it before you sit down to write your first paper, then read it again at least once a year for the next three or four years.) which is available here

Notes on Critical Mass: The Physics of Society by Philip Ball (2004, William Heinemann).

Also informed by his appearence on at the ICA on the panel debate Dying of Consumption and lecturing at the Royal Institution.

Philip Ball’s massive tome is full of ideas, but I can’t but help but feel that he’s not saying anything radically new. This might come from having lived with Dan and hence being happily privilaged in my available head-food.

Anyway, he’s a very British writer. Unlike those other guys (Gladwell, Buchannan) he doesn’t read like someone who spends half their time in business consultancy seminars. He reads like someone who is too well read for their own good. The historical and philosophical context he gives to the ideas is a joy, although not really as motivating as the high-octane brashness of the New World science writers on the same topic). His deconstruction of conventional economic theory (more of this at the NEF debate than in the book perhaps) is classic and convincing.

The material is what you might expect, but done by someone with a rigourous background in the hard sciences. Self-organisation, phase transitions, emergent dynamics (slime moulds, flocking behaviour), chaos, attractors, bifucation points (and hightended senstivity to noise at the same), power-laws (aha, a Power Law, i hear you say, the signature distriubtion of mutual influence amoung sub-units of a system), small worlds, preferential attachment (DLA) networks, evolutionary game theory…

There’s a nifty demo of crowd dynamics at
http://www.helbing.org/Pedestrians/corridor.html
and
http://angel.elte.hu/~panic/

An interesting observation: the tension between predictive scientific social models and individual free will has a historical ancedent in the nineteenth century discovery of statistical regularities in population statistics. If we can predict from census records that the number of suicides in a parish in a year will be around seven, where does that leave the free will of those who choose (or don’t choose) to kill themselves there? The use of such statistics was deeply controversial at the time, in a way that’s hard to fully appreciate now.

The important point
The value of a physics of society is that it is an attempt to understand how global phenomena can arise from local actions. Philip Ball is saying that, yes, there is a kind of intelligence to the group (but not that it is sublime).

Thinking about the studies that inform Critical Mass, and Dan’s thesis, what other lessons are there from CAS? (I’m going to adopt Dan’s term and use CAS – Complex Adaptive Systems – to subsume a whole managerie of theories dealing with dynamic, iterated, evolutionary, chaotic and/or computational models of both the cellular and agenic types).

– non-linearity. Don’t always look for [simple] causation, don’t say small things can’t have big effects and don’t always expect big things to cause large changes .

(see the discussion of, e.g., ‘broken windows theory’ in Gladwell’s The Tipping Point)

– theory won’t do the work for you. You must investigate each system and establish it’s workings

– we need to recognise that markets are constructions and, alhtough they operate in complex and adaptive ways, we inevitably play a role in defining the framework within which they operate.

(as if buying and selling are acts divorced from culture! As if culture isn’t a political construction! Ha!)

– level crossing. There is reciprocal causation between individual and group behaviour (Remember mamet on polls)

I think – and I should credit many hours squabbling with ralph for this – the use of CAS in politics and postmodernism are grappling towards a way to express the same kind of ideas, to talk about the same kinds of, non-intuitive, systems. There is the same deconstruction of agency, the same willingness to cross levels of analysis, to recognise the the validity of multiple similtanous views rather than stick dogmatically to one paradigmatic/ideological view.

Another observation by PB(in response to a question on catastrophe theory at the RI lecture): Catastrophe theory ‘came and went’ because it was a phenomenological theory.
(reminds me about the stuff in my thesis about explanation. What constitutes an explanation? A theory which connects a phenomenon to the behaviour of more fundamental elements. Catastrophe theory just posits a dynamic without an attempt to investigate the instantiation of that dynamic. Sounds familiar…).

Two miscellaneous quotes:

By developing mathematical and computer models of the spatial patterns of communities ranging from traditional villages to modern towns, Hillier and Hanson have shown that urbanisation tended to increase and diversify people’s interactions up until the time when new templates for planning were introduced during the Industrial Revolution
– p173 (see Hillier & Hanson (1984) The Social Logic of Space. CUP, p266).

Batty and Longley calculate that between 1820 and 1962 the fractal dimension of London increased from 1.322 to 1.791
– p186

Notes on Dan Olner’s Do We Need Nature? Master’s Thesis; 2004. Department of Politics, University of Sheffield. (basic topic: Complex Adaptive Systems and political economy).

The point for me was:
Both the left and the right utilise CAS to justify a faith in the self-organising nature of either markets and/or social movements. Further, it is astounding that the left don’t appear to realise that they are echoing the traditional rational of the right. And it’s astounding that both sides appear not to question the assumption that spontaneously emerging outcomes will be desirable.
– the leftist view, says dan, is characterised by the belief that ‘right’ action will crystallise into the world directly .

(in my thesis I made a contrast between emergent explanations and transparent explanations – ie those in which the functionality of the sub-units is directly manifested in the functionality of the whole. It seems analagous).

(i think the Axelrod stuff on evolution of altruism / iterated game theoretic approaches to ethics is relevant here. As an example, we might instinctively asign absolute pacifism a kind of moral superiority, but if we take a (socially) wider view, immediate retribution is kinder to everyone because it discourages future law-breaking)

– the rightwing view, in my opinion, is characterised by the failure to acknowledge that markets are willful creations of culture, not an independent realm resting outside of culture.

We’re still a long way from absorbing this way of thinking and truely moving to the next level in our thinking. To wit, to quote Dan (p12)

Presuming that such dynamics did exist, what do political actors do about it?

What indeed. I think we need to understand CAS, not so we can stand in awe at their function (although we should do that too), but so that we can develop laws, institutions and habits which work with physics of society rather than against them (this was how Philip Ball concluded last week’s lecture at the Royal Institution. I thought it was platitudinous at the time, but now I think he’s spot on. This is the area where we need to focus our attention).

On the political theory side of things, Dan discusses the way political ideologies define what is natural and use that to say what can and cannot be interfered with legitamately. He also makes an observation that seems the complement of one of Philip Ball’s. Dan says: political ideologies always try to recruit science to legitimise their claims – so we should be wary when listening to political claims involving science. Philip says that, historically, those who attempt to use the scientific method to derive political convinctions usually end up merely deducing the conclusions that they were theoretically pre-disposed prefer – so we should be wary when listening to scientific claims involving politics.

Dan also observes that CAS-style thinking is taken to indicate the bankruptcy of carterian rationality. ‘Yes!’ I’d say. And i think this comes through from Critical Mass as well. There is no ‘utopia theory’, in the sense of a theory which will provide your solutions in advance. If there’s any way to use CAS politically it is in the rejection of grand-narratives (how postmodern), a skepticism of ideologically-led prescriptions. We can use these concepts in understanding complex systems, but they aren’t going to do the work for us. Each complex system will be different and we will need to do the work ourselves in finding out how. Don’t theorise – investigate!

Perhaps one moral. Evolution has done quite well with designing complex systems. Evolution is a tinkerer. Let’s tinker.

Further to this, there was an interesting In Our Time a few weeks ago about Lamark. The panel discussed the strands of evolutionary theory which connected with Lamark (and his famous fallacy). Seems Lamarkianism is part of a deep vein of evolutionary thought which emphasises organism-environment interaction to a greater extend than individually, and intra-individually, focussed neo-Darwinian orthodoxy. Something to be aware of.

I’ve been thinking about how you find out the facts – the scientific facts – on a topic. As an academic you develop a set of prejudices, almost unconsciously at times, which help you deal with the riddle of too much information. You know what kind of paper makes it into Nature, from your field. You know how much to trust something published in Trends in Neurosciences compared to Perceptual and Motor Skills (for example). You’re also plugged in to a structure (the Academy) which provides easy access to colleagues, journals, conferences and hence filters and recommends information. You’re immersion lets you develop a judgement for how plausible new information is – you can spot bullshit.

Move out of the University, or move fields, and you lose some or all of that. If you’ve never worked as a professional academic, then you don’t even know what you’re missing. Do you even know that publication in peer-reviewed academic journals is the gold standard for any data? That for many scientists, evidence can in some way be said not to exist until it is peer-reviewed?

Anyway, I wrote some notes for the BBC intranet (research.gateway > science for anyone able to look there) which i’ve also put here. Anyway, if anyone can think of things that should be known by documentary researchers who don’t have a scientific background, but who are researching scientific topics let me know.

From psychology/neuroscience i’ve realised that Behavioural and Brain Sciences have a free on-line archive and so does CogPrints. Both potentially useful if you’re looking for papers to get started on a topic and you don’t have library access.

Over at The Edge‘s World Question Centre John Brockman has asked a bunch of interesting people to contribute a new scientific laws:

There is some bit of wisdom, some rule of nature, some law-like pattern, either grand or small, that you’ve noticed in the universe that might as well be named after you. Gordon Moore has one; Johannes Kepler and Michael Faraday, too. So does Murphy.

And it’s a good excuse to gorge yourself on quotable titbits. On ourselves:

Pinker’s First Law
Human intelligence is a product of analogy and combinatorics. Analogy allows the mind to use a few innate ideas?space, force, essence, goal?to understand more abstract domains. Combinatorics allows an a finite set of simple ideas to give rise to an infinite set of complex ones.

– Stever Pinker

On science:

Warwick’s Second Law
Art tells the jokes that science insists on explaining.

– Henry Warwick

Sapolsky’s Second Law
It’s okay to think about nonsense, as long as you don’t believe in it.

Sapolsky’s Third Law
Often, the biggest impediment to scientific progress is not what we don’t know, but what we know.

– Robert Sapolsky

And reason:

Kai’s Example Dilemma
A good analogy is like a diagonal frog.

– Kai Krause

Harari?s Law of Science Education
The faster Science and Technology advance?the more important it is to teach and to learn the basics of Math and Science and the less important it is to teach and to learn the latest developments.

– Haim Harari

If you visit also check out P?ppel’s Universal and Ogilvy’s Law. The prize for insightful brevity is shared between Andy Clark and Steve Grand. Enjoy