I think I've probably finished the reading the internet now. Eyelids peeled back, unable to look away, scratching the wallpaper off to get at whatever thoughts or feelings might help shift this... matter through my digestive tract without rupturing something. It's ongoing. In the meantime, as for so many others, dream and reality are in some godawful state of twizzler. Panicked braincells scramble to hide behind each other, desperately straining to avoid the incoming signals.
Which is of course all angel delight to the right-wing maw. As a friend once said after they inflicted a vicious chess defeat that I'd poured everything into: "I wear your pain like a crown."
Well fuck them, obviously. (Not the friend - they're quite nice really.) Paul Ryan's vacant little Mona Lisa smile as he refuses to acknowledge that an appointed 'chief strategist' is clearly Voldemort - that's pretty much all we need to know about these people. "Evil overlord, you say? Hmm. Will this get me more power? Mmmmm."
I've been shocked into doing something. Pretty messed up that it should take this, but there's some comfort knowing exactly the same thing must be happening to thousands, millions of others.
There are a bunch of luxuries we no longer have. We don't have the luxury of much self-doubt. Or rather, it'll always be there - everyone has it - but you're not allowed to let it stop you. Them's the rules now. Do something. Anything from contacting people you haven't in a while, hugging a friend, donating, volunteering, painting, singing, plotting, inventing an entire utopia. Don't make a utopia in your spare room all alone though, and don't be silly and try and do it all on the internet. Come out and play. Bounce that stuff off other people - the one thing we need more now than ever is to connect with others in every way we can.
Sure, your mind may scowl: "you Walter Mitty peabrain, what the hell makes you think you can make any difference to anything? Remember all those things you fucked up? That's the real you. Drink your effing beer, stuff this Netflix into your eyeballs and SHUT UP." But... your mind can fuck off as well. And notice just how useful that bit of your mind is to those aforementioned power-mad eejuts. They want you to do nothing. Fuck them also. I said that already.
Because there are really very sound reasons why you should do the thing and not not do the thing. Jane Jacobs nailed it: anything good that ever happens or gets made is just accident fuelled by intention. It's a lot of people with ideas and bits of stuff they're making and trying, doing the thing - and usually finding out the thing doesn't turn out anything like how they thought. But then this other thing happens - Jacobs realised, in fact, that it happens without fail when we get together to do stuff. It's what humans do. Some magic mix of evolution and artistry: person A goes - hey, that thing you just did? What if I just bodge that in with this other thing? Oh sweet Christ, we've discovered a better way to organise the city! How did that happen?? Accident fuelled by intention, ladies and gentlemen.
But it needs the intention. You need to turn up, do the thing and - this bit is especially important - not not do the thing. Not doing the thing: that's self-doubt's job description. Spotting little green shoots of maybe doing the thing and yanking them up before you have a chance to get out the door.
And you do at least sometimes need to get out the door: do the thing where other people are doing things too, or take the thing out for a visit now and then.
So - for myself - I'm fucked if I'm gonna let some colossal tango-faced bullshit queen, centre of a venn diagram made from a blow-up sex doll and an obese geriatric ginger tomcat, mess with everyone else's amazing work on stabilising carbon output. It should probably have been obvious this couldn't be done without one or two countries going the full man-toddler on us. A puncture on the road is predictable enough - you've just got to roll your eyes, fix the damn thing and press on, even if you can see the little shits who threw the tacks laughing their asses off.
Put aside any eensy niggles about nuclear obliteration - as Nick Fury so wisely said, "until such time as the world ends, we will act as though it intends to spin on". The planet's future is somewhere on a distribution and, like these poor lushes trying to get to the pub across a bridge over a terrifying ravine of certain-ish doom, there is no point at which it's OK just to say: ah sod it, let's just stumble forward unconsciously and hope for the best. The odds are worsening with every year, but there are - for a good while yet - always odds worth taking. Here's Alex Steffan:
It’s a fight for every 1/10th of a degree. If we fail to hold to 2ºC, we have to fight for 2.1º; failing that, we battle on for 2.2º. With millennia of impacts at stake, we never get to give up, even if we end up in 4ºC. For future generations, 4º is still better than 4.1º. "Game over" is neither realistic nor responsible.
And there isn't a shortage of other stuff to get stuck into. At the root of it all, connecting with others is the prime directive. For anyone who believes every person of any sex/gender/skin-colour/age/wealth/size/shape/geolocation/dress-sense deserves our deepest fucking respect and our care, that we all owe that to each other - that act of connection is the most fundamental and sacred thing we can do. Fucking cliché, I know, but you know that cliché about things being clichés for a reason? That.
1. Fuck them. (Obviously.)
2. Do the thing. Do not - and I really want to be clear on this point - not do the thing.
3. Be excellent to each other.
Now get on with it.
p.s. sorry I was rude about you Donald. I'm really cross with you right now.
Reading Mark Blaug on Pareto efficiency was a lightbulb moment. As he says, Pareto's idea was a 'watershed moment' in arguments about utility. From a distance, the outcome can seem pretty meaningless but it's an important political fork in the road - and one that shines a light on how the abstractions of economic theory get tangled with power politics. There's a story about Pareto himself to be told, too - I'm not going into that. This is about where his idea went after that.
Benthamite utilitarianism hadn't been going badly. But it was premised on the idea that different people's well-being could be compared - after all, there's no other way of knowing if you're increasing or decreasing the general welfare.
This seemed intuitively straightforward at the time. But, perhaps as the study of utility as an economic concept developed, that began to change. Attempts to actually track down a scientific measurement of people's utility got underway. Folks got upset about the obvious problems in trying to define what utility really was.
Pareto offered a way out of this. I'd known the concept before but not understood its significance until reading Blaug. Pareto efficiency: you've reached an optimal state when it's not possible to make anyone better off without making someone else worse off. Sounds innocuous enough. But notice that it sidesteps comparability. As Blaug says:
"The beauty of Pareto’s definition of a welfare maximum was precisely that it defined the optimum as one which meets with unanimous approval because it does not involve conflicting welfare changes."
It rules out the possibility that one could -
" - evaluate changes in welfare that do make some people better off but also make other people worse off" (Blaug / economic theory in retrospect/ 1997 p.573-4).
So it can say absolutely nothing about inequality. Or rather, it implicitly says that it doesn't matter: you cannot, for example, assess whether taking money from one person and giving it to someone else will improve welfare overall. Bentham schmentham.
Pareto optimality, unsurprisingly, became very popular and is essential to most general equilibrium models. I don't understand those - I'm only familiar with Krugman's spatial GE stuff, which is not the same (they're driven by explicit utility differences across space). But I'm not surprised models that, by default, exclude inter-personal comparisons should form the inner sanctum of modern economics. A model that can, by design, exclude any discussion of redistribution was always going to thrive.
Which is not to say there aren't plenty of approaches that do analyse the differences between rich and poor. But... and I'm not on solid ground with this point at all... the kind of economics that sits in rooms with ruling elites don't generally use those.
I want to make two little points about this. The first comes from having actually used utility as a concept in my modelling work and found it extremely valuable. I spent far too long listening to the siren-calls of agent modellers telling me to go towards 'realism', then in the process of slowly solving my problems, realising I had ended up back at basic micro-economics.
So first: if you're going to use utility at all, you'd better accept it's a silly idea that lets you do useful things. People are not actually utility maximisers, but the concept is a superbly effective way of thinking about how people react to cost changes in certain situations. (This is all very Friedman [pdf].)
So all that pursuit of the actual foundations of utility in our meat-brains is, somewhat, beside the point. Given that, we should use the idea in ways that are useful. Ruling out utility comparisons is just a little bit too convenient a result, politically. There isn't really any reason to, and the angst about utility's epistemological status makes about as much sense as rejecting traffic models because they don't use gravity equations. (Er, at least I think they don't...)
Second, one of the most powerful ideas that utility gives us is diminishing returns. It's easy to forget how much of a puzzle this was - the whole water/diamond problem thing. It should be blatantly obvious to anyone who thinks for a few seconds that money itself has diminishing returns. Say a 7% drop in income forces your family to eat less well and you to have to skip meals sometimes. It shouldn't be beyond our economic theory to see this as more severe than having to compromise on the Land Rover you had your eye on by buying a Mondeo.
This is kind of paragraph that sets the flying monkeys off, though. Particularly since the 2008 crash, particularly in the UK - the story that's been slowly pushed through all media channels is solidifying into political reality: such talk is the politics of envy, rather than - as it actually is - a perfectly sensible way to think about wealth.
These days I generally end up thinking "it's all about the middle way". The same applies here - effective economic comparability could imply deep intrusion in people's lives, the state charged with measuring and judging what forms of spending were more worthy than others, creating a kind of state-sanctioned Maslow hierarchy. But it doesn't need to - if one is capable of accepting the basic premise that severe poverty makes people's valuation of money much higher than for richer folk, it just implies the need for policies that reduce inequality.
And there isn't necessarily anything wrong with Pareto efficiency. The problem here is what happens when powerful abstract ideas interact with powerful political forces. Things get warped to Wizard of Oz proportions. Other perfectly sensible ideas can't get their shoe in the door. But it's foolish to use Pareto efficiency to exclude distribution thinking, just as it would be idiotic to ban its use because it was too right-wing.
I wouldn't want to live in a world where political schools had their own paid-for economic theorists. I do still believe in the pursuit of actual social-scientific truths. But Pareto efficiency is one of those ideas that hammers home just how hard it is to pull economics and politics apart.
The point: as far as possible, your economic/mathematical models shouldn't rule out one particular political way of thinking. The choice of how we balance wealth in society - that's a political issue. There's no easy way to keep an unbreachable line between positive and normative - modelling methods will always interact with our political assumptions and power structures in sometimes very-hard-to-see ways. And I also believe in the power of quant modelling to help us understand which things may not work if pursuing certain political aims. But modelling distribution issues - and using utility to do this - no more makes you a communist than using Pareto efficiency makes you a fascist.
(p.s. googling Pareto inequality reminds me there's a mountain of stuff on this subject I don't know. But if I think like that all the time, I won't get a single blog entry written, let alone seventeen...!)
New year's earnestness 1/17
Uber-branded taxis are now ubiquitous* in Leeds, having launched last November. I'm back in Leeds for a month - it was immediately striking that pretty much every taxi now has the large white Uber label, at least in the city centre. That's a pretty impressive transformation in just over six months.
It's a classic disruptive firm; one can imagine CEO Travis Kalanick has personal targets for how many local government authorities to annoy. It can certainly be spun as a nimble tech firm zipping around the tree-trunk legs of a geriatric industry. Predictably, there's been trouble. As well as various protests, some Uber drivers are getting organised to fight for a bigger slice of the profits. (If, as that article says, Uber are taking 20-25% per ride, there isn't a lot of head-room for wages to increase - Uber's dirt cheap fares would have to rise.)
Uber have placed themselves between drivers and customers in a way that reminds me of the weirdness of Apple's app store. In a world where anyone can dump code on their blog and anyone can downoad it, Apple have thrived by creating a portal and sitting as gatekeeper. They take around 30% of every single app sale - and, for developers, this has actually worked out great. They get access to a huge market while getting to code on a single, predictable platform. Small niggles about the political implications of that control might buzz about irritatingly but cause no serious discomfort.
Equally, existing tech could - in theory - link customers and taxi drivers without the need for such a powerful intermediary. The possibility of open-standards platforms transitioning us to the next level of transport has excited many people. Harvey Miller's work, for instance (and this great presentation) sees hope for a "transportation polyculture" where smart-city tech opens up a world of collaborative/co-operative transport. In this world, the kind of fluid, efficient city roads that Uber talk about, where ride-sharing is easy and prevalent, come about via open source principles entirely at odds with Uber's - though such a world would perhaps be just as disruptive to existing taxi firms.
Two radically different internet myths are at the heart of this difference. In one founding myth (as the Economist says) the Net is "the spontaneous result of co-operation by growing numbers of people acting outside the control of the governments and big companies" - a "libertarian paradise" promising a level of openness, connectedness and democracy never before possible. That story is still being told.
But then this other story appears.
"Laws, like sausages, cease to inspire respect in proportion as we know how they are made." (Misattributed to Bismarck.) This Springs to mind every time I try and write recently, though with "research projects" replacing "laws". Equally, I'm not sure people would lose respect for their sausages if they saw them being made, so much as gain a gag reflex. We don't want that in research either.
But it would be nice to blog. More than nice: I think it's a very useful thing to do, for one's own research progress especially. There are many entirely sterile academic blogs that do little more than promote: how great and wonderful the project is and what fantastic impact and outputs result (though note this entertaining if rather undiplomatic post by a prof in my department... sterile, it is not.) Promotion is necessary, to be sure, but by itself both boring and a tragic waste of the potential of blogging.
Writing is thinking in action. There's a common misconception that it's a two-stage process: staring out into space until an idea arrives, then transcribing that Platonic idea down into word form. Not so. The writing process itself is is a form of thinking.
Anyone who keeps a field diary or a work journal does a lot of that privately, of course – but the process of writing blog entries offers a different kind of thinking. You are, after all, writing for an audience, even if no-one actually comes and reads. They might. You never know. That slight additional pressure enables a blog to help the researcher formulate what the hell it is they're really doing and thinking. That's incredibly useful: having a place that's not just a work journal but that also doesn't impose the kind of austere control required for assembling a full paper.
The problem with blogs is also its advantage, at least for me. I often want to write about stuff I'm trying to work out. It really helps. But that thinking-in-public is a little tricksy. What I'd like to do in the rest of this post is say why I think that's worth pursuing anyway. I'll do that with a couple of ideas. One: blogs are good places for "actively seeking out opportunities to feel stupid". Two: good shit happens in those murky stupid places where you're poking your nose into the darkness beyond the streetlight you're looking under.
Idea one: Martin Schwartz on the importance of stupidity in scientific research. He is talking specifically about the physical sciences, but it applies elsewhere. He tells the story of an incredibly intelligent friend of his who left research because 'it made them feel stupid'. Puzzling over this for a while, he realised:
Science makes me feel stupid too. It's just that I've gotten used to it. So used to it, in fact, that I actively seek out new opportunities to feel stupid. I wouldn't know what to do without that feeling.
Huh. He explains his idea of 'productive stupidity': an 'immersion in the unknown' where it's impossible to know the outcome. As he says, 'if we don't feel stupid it means we're not really trying'. Schwartz is careful to contrast this with the idea of 'relative stupidity' that most people grow up with: learning in a system that ranks people on a scale and where it was always possible to be the least stupid in a group. Research is not like that; Schwartz's friend was too uncomfortable with it to stay.
Nicholas Harberd, in his excellent diary of a working plant scientist, captures what those moments feel like:
Of course science is always like this. There are peaks and troughs. I’ve experienced both. But the problem with being in a trough is that it is a place from which the view is limited. There is the feeling of being trapped with no way out. And always the question of how long the entrapment will last. A self-sustaining state: at the time when new vision is most needed, it is most unlikely to come. [p.6]
So this isn't really stupidity. It can make you feel stupid. That feeling (as Harberd hints at) isn't comfortable or easy. The trick that Schwartz learned – and his friend couldn't – was not to take it personally. This is a lesson that physical libraries can teach as well – something that's easy to forget when it seems like all knowledge is only a google away. Taking a walk through journal stacks instills this feeling in me. It's very easy to imagine being an ant crawling in a vast nest of knowledge, only a tiny sliver of which any single person could ever keep in their own skull – but little ants or not, it's our job to keep that corpus alive and evolving over time.
I'm not saying there aren't times when applying one's existing knowledge to problems isn't valid – of course it is. Geography has many planning- related applications. Planners, not unreasonably, want tried and tested methods, not voyages into darkness. But how are new ideas are discovered? Do we still value that?
Idea two: the streetlight effect. As Kirman explains, it:
corresponds to the behaviour of the person who, having dropped their keys in a dark place, chose to look for them under a streetlight since it was easier to see there (Kirman 1992 p.134).
This has a larger scope than simply "refusing to be stupid" and staying under one's streetlight. All researchers work within disciplines (or possibly Kuhnian paradigms) that shape how they see the world they're investigating. Economics is an instructive example: those outside the discipline often view it is the archetypal methodological utopia, creating "citadels of crystalline mathematical perfection that would shatter if touched by the harsh rays of reality" (Ball 2007 p.647). Many economists, however, openly acknowledge this without rejecting economics outright. Overman describes "the tendency to privilege particular economic forces purely because they are more amenable to the theoretical and empirical tools used by mainstream economists" (Overman 2004 p.504). Summers notes the result: "it is all too easy to confuse what is tractable with what is right" (Summers 1991 p.145). Krugman, as is often the case, puts it best and nicely ties back to the streetlight: "the methodology of economics creates blind spots. We just don’t see what we can’t formalise" (Krugman 2008).
These economists are self-aware; it gives them a humility and caution about the power of economic models (a humility entirely absent in much agent modelling; consider this recent example in the Economist - a topic for another time). But it doesn't actually alter the basic point: economics works under its own streetlight.
I've spent a lot of my time in the past few years asking: what happens to the landscape when costs change? Short answer: no-one exactly knows. There are no existing methods capable of answering the question fully – though of course there are many streetlights to look under. If someone from the transition movement tells you we need to relocalise to adapt to upcoming cost changes, how do you answer? Are they right? How do we know either way?
My current project has its specific goals but, for me, an equally important aim is to ask these questions openly. As the blog's intro post said this is all "good old fashioned location theory question, but 21st century challenges are breathing new life into it." This is true: there has never been a more relevant time for geography of all stripes.
This is important for another reason: the pickle we're in, globally. The kind of innovations we need will not come from being shy about our lack of knowledge or being closed to collaboration. In his 'stupidity' article, Schwartz says "science is made harder by competition for grants and space in top journals". This reality can turn collaboration and openness into little more than empty sentiment: something we'd like to do in theory but that goes too firmly against the grain of academic practice. Academic blogging, however, helps with that. For a start, it achieves that all-important job of staking out what your ideas are publicly. It can also act as a prototyping tool for ideas that may end up in more formal academic outlets.
There's a deeper point also. As Dougald Hine lays out so eloquently in his recent lecture, the world is changing around the university. The kind of knowledge-creating relationships we'll need to in the coming decades may not look like they did in the past.
Schwartz, M.A., 2008. The importance of stupidity in scientific research. J Cell Sci 121, 1771–1771.
Harberd, N., 2006. Seed to Seed: The Secret Life of Plants, First American Edition. ed. Bloomsbury USA.
Kirman, A.P., 1992. Whom or What Does the Representative Individual Represent? Journal of Economic Perspectives, Journal of Economic Perspectives 6, 117–36.
Ball, P., 2007. Social science goes virtual. Nature 448, 647–648.
Overman, H., 2004. Can we learn anything from economic geography proper? Journal of Economic Geography 4, 501–516.
Summers, L.H., 1991. The Scientific Illusion in Empirical Macroeconomics. The Scandinavian Journal of Economics 93, 129–148.
Krugman, P. (2008). ‘How I work’. URL: http://web.mit.edu/krugman/www/howiwork.html
Our new grant. Intro write-up also up at the Talisman blog. There's a link in there to this interactive viz of the UK's trade flows - a starting point for working on how best to make the spatial economy visible.
Alison Heppenstall, Gordon Mitchell, Malcolm Sawyer (LUBS) and I have been awarded an 18 month grant by the ESRC through their secondary data analysis initiative. Titled 'Geospatial Restructuring of Industrial Trade' (GRIT), the motivation for the grant came from a deceptively simple question: what happens to the spatial economy when the costs of moving goods and people change?
That's a good old fashioned location theory question, but 21st century challenges are breathing new life into it. During the next few decades an energy revolution must take place if we're to stand any chance of avoiding the worst effects of climate change. What price must carbon be to keep within a given global temperature? How long will any switch to new infrastructure take? (Kramer and Haigh 2009; Jefferson 2008) In fact, will peak oil get us before climate change does? (Wilkinson 2008; Bridge 2010) In a time when we're discovering costs may go up as well as down, do we have a good handle on the spatial impact this may have? Can we use new data sources and techniques to answer that, in a way relevant to people and organisations being asked to rapidly adapt?
GRIT will focus on two jobs. First, creating a higher-resolution picture of the current spatial structure of the UK economy. Second, thinking about how possible fuel costs changes could affect it. We'll examine the web of connections between businesses in the UK, looking to identify what sectors and locations may be put under particular pressure if costs change. There is a direct connection with climate change policy: the most carbon-intensive industries (also very water intensive) are also those with the lowest value density, and so most vulnerable to spatial cost changes.
Most economics still works in what Isard called a "wonderland of no dimension" (Isard 1956, 26) where distance plays no role except as another basic input, in principle substitutable for any other. Some economic geographers believe that because energy and fuel are such a small part of total production costs, "it is better to assume that moving goods is essentially costless than to assume [it] is an important component of the production process" (Glaeser and Kohlhase 2004, 199). At the other extreme, social movements like the transition network privilege the cost of distance above all else. They make the intuitive assumption that if the cost of moving goods goes up, they can't be moved as far – so localisation is the only possible outcome. They are making a virtue of what they see as economic necessity imposed by climate change and peak oil. At the extreme, some even argue that "to avoid famine and food conflicts‚ we need to plan to re-localise our food economy".
Reality lies somewhere between those two extremes of ignoring spatial costs altogether or assuming a future of radical relocalisation. GRIT is taking a two-pronged approach to finding out: producing a data-driven model and talking to businesses and others interested in the problem. Our two main data sources both use the 'standard industrial classification' code system, breaking the UK into 110 sectors. First, the national Supply and Use tables contain an input-output matrix of money flows between all of those sectors. (I've created a visualisation of this matrix as a network: click sectors to view the top 5% of its trade links and follow them. Warning: more pretty than useful, but gives a sense of the scale of flows between sectors.) It contains no spatial information, however – we plan to get this from our second source, the 'Business Structure Database' (BSD). As well as location information for individual businesses, each is SIC-coded and also provides fields for turnover and staff number. It also has information on firms' structure: "such as a factory, shop, branch, etc". (There's a PDF presentation here outlining how we're linking them, though I'll write more about that in a later post.)
By linking these two (and adding a dollop of spatial economic theory) we have a chance to create a quite fine-grained picture of the UK's spatial economy. From that base, questions of cost change and restructuring can then be asked. The 'dollop of theory' is obviously central to that; we've tested a synthetic version that produces plausible outputs (see that presentation for more info) but 'plausible' doesn't equal 'genuinely useful or accurate'. I'll save those problems for another post also. This sub-regional picture of the UK economy is a central output from the project in its own right and it is hoped it can be used in other ways – for instance, for thinking about how industrial water demand may change over time.
Even before that, two big challenges come with those datasets. First, BSD data is highly sensitive. It is managed by the Secure Data Service (SDS) and can only be accessed under strict conditions (PDF). Work has to take place on their remote server, and anything produced needs to get through their disclosure vetting before they’ll release it, to make sure no firm’s privacy is threatened. These conditions include things like: "SDS data and unauthorised outputs must not be printed or be seen on the user’s computer screen by unauthorised individuals." So, no-one without authorisation is actually allowed to look at the screen being worked on. Crikey. The main challenge from the BSD, however, is getting any of the geographical information we want through their vetting procedure. The process of working this out is going to be interesting. To their credit, the SDS have so far been very patient and helpful. While genuinely keen to help researchers, they also have to keep to draconian conditions – it can't be an easy tension to manage.
The second challenge is really getting under the skin of the input-output data. On the surface, it appears to very neatly describe trade networks within the UK, but its money flows can't all be translated simply to spatial flows. For a start, as the visualisation clearly shows, the largest UK sector, 'financial services', gets the UK's biggest single money flow from 'imputed rent' – which doesn't actually exist as exchanged goods or services. This comes down to the purpose of the Supply and Use table – a way to measure GDP. Imputed rent is a derived quantity used to account for the value to GDP of owned property. That's only one small example, but it illustrates a point: care is needed when trying to repurpose a dataset to something it wasn't intended for – in this case, to help investigate the structure of the UK's spatial economy. It is hoped that less problems exist for more physical sectors, but that can't be assumed.
The second 'prong' is to talk to businesses and other interested parties to find out how they deal with changing costs and to see if the work of the project makes sense from their point of view. We plan to hold two seminars to dig into the affect of changing spatial costs on businesses. Anecdotal evidence suggests suppliers have been citing fuel costs as a reason for price increases for a while now.
A whole range of other groups are keenly interested in spatial economics, though it might not always be labelled thus. An example already mentioned, the 'transition movement' is taking action at the local level. It has, in recent years, developed strong links with academic researchers. A vibrant knowledge exchange has developed between locally acting groups and researchers, with the aim of making sure that "transition and research form a symbiotic relationship" (Brangwyn 2012). It isn't just about spatial economics: it's imbued with a sense that people can play a part in shaping their own economic destiny. It's hoped that GRIT will be of interest here also.
So that's GRIT in a nutshell. There are clear gaps in the project's current remit. Trade doesn't stop at the UK's borders and any change in costs will have international effects (an issue I've been pestering Anne Owen from Leeds School of Environment about). Many of the costs most essential to business decisions are either hard to quantify or to do with people, not goods. (Think about how much it costs a hairdresser to get a person’s head under the scissors from some distance away, e.g. in the rent they pay; this hints at the reason data appears to show the service sector may be the most vulnerable to fuel cost changes.)
Aside from the technical aspects of the project, there are two other things to write about I'll save for later: the nature of distance costs and the place of modelling in research and society. And on that last point, just a bit of brainfood to finish on from Stan Openshaw (1978). In theory, GRIT wants to tread both of these lines, but that's something far easier said than done. (Hat-tip Andy Turner for lending me the book.)
Without any formal guidance many planners who use models have developed a view of modelling which is the most convenient to their purpose. When judged against academic standards, the results are often misleading, sometimes fraudulent, and occasionally criminal. However, many academic models and perspectives of modelling when assessed against planning realities are often irrelevant. Many of these problems result from widespread, fundamental misunderstandings as to how models are used and should be used in planning. (Openshaw 1978 p.14)
Brangwyn, Ben. 2012. “Researching Transition: Making Sure It Benefits Transitioners.” Transition Network. http://www.transitionnetwork.org/news/2012-03-29/researching-transition-....
Bridge, Gavin. 2010. “Geographies of peak oil: The other carbon problem.” Geoforum 41 (4) (July): 523–530. doi:10.1016/j.geoforum.2010.06.002
Glaeser, EL, and JE Kohlhase. 2004. “Cities, Regions and the Decline of Transport Costs.” Papers in Regional Science 83 (1) (January): 197–228. doi:10.1007/s10110-003-0183-x.
Isard, Walter. 1956. Location and Space-economy: General Theory Relating to Industrial Location, Market Areas, Land Use, Trade and Urban Structure. MIT Press.
Jefferson, M. 2008. “Accelerating the Transition to Sustainable Energy Systems.” Energy Policy 36 (11): 4116–4125.
Kramer, Gert Jan, and Martin Haigh. 2009. “No Quick Switch to Low-carbon Energy.” Nature 462 (7273) (December 3): 568–569. doi:10.1038/462568a.
Openshaw, Stan. 1978. Using Models in Planning: A Practical Guide.
Webber, Michael J. 1984. Explanation, Prediction and Planning. Research in Planning and Design. London: Pion.
Wilkinson, P. 2008. “Peak Oil: Threat, Opportunity or Phantom?” Public Health 122 (7) (July): 664–666; discussion 669–670. doi:10.1016/j.puhe.2008.04.007.
This is a nifty example of how reality works on the interweb. I saw the poster on facebook and, like many others, for a moment thought, 'well, that's the sun all over, innit?' However, I've been gotcha'd too often by the Guardian's April 1st stories. They generally aim for a core of plausible, while tweaking the average Guardianista's sandal-wearing liberal nipples in just the right way. More than once, April 1st has seen me having a foaming rant, before eventually realisation hits, followed closely by acute embarrassment and sitting in a corner sulking at my own stupidity. (Chris Martin openly supporting David Cameron seemed particularly likely, I recall.)
It occurs to me, though, there's a parallel to how `markets' are talked about. To paraphrase Obi Wan, `market forces are are an energy field created by all living things. They surround us and penetrate us. They bind the galaxy together.' Which is to say, they're a mystical nonsense prayed to daily by people who believe in the confidence fairy. It's cargo cult gibberish. It's like turning up to some vital, knife-edge diplomatic negotiation teetering on the edge of war, cracking open a beer and saying, `chill - language will save us.'
Similar claims are made of the interwebs, and they're wrong for the same reason. There's nothing intrinsic to its structure that will produce truthiness or optimal outcomes. It can be used as a platform for doing that - but only if you actually develop tools to achieve specific aims. A trivial but suggestive example: guitar tab. The net's full of the stuff, and there are many sites with tabs for specific songs. But the vast majority of the time, they turn out to be precisely the same. That's not because they're correct, it's because the first person to dump it on the web got copied and recopied. No effective mechanism exists for improving the accuracy of particular songs. An echo-chamber is the unsurprising result, despite the fact that the net should be the perfect vehicle for some form of guitartab wikipedia. The machinery for that hasn't been built, though.
There are projects attempting to get meta on the net's inability to manage `peer review' effectively, like hypothes.is. That's got to be on the right track if there's no magic force that can do it for us. And the same applies to markets: effective ones are quite specific structures. Often cobbled together haphazardly, they can nevertheless be tweaked and developed for specific purposes, even though - just as with good code development - you'd best stay away from attempting all-encompassing gargantuan rebuild projects (compare the approach of NHS hack day to CSC's work on NHS records).
There's so much more to write about truthiness in the wake of current Republican goings-on, all the Assange gubbins and the ongoing mismatch between the physical and political reality of climate change... another time.
A repost of my first blog entry on the Talisman blog, trying harder to understand visualisation and communication.
This article is the first of a few I hope to write about visualisation and Processing, a graphics tool created by Ben Fry and Casey Reas back in 2001. In this one I'll introduce Processing and get into some hard-core navel-gazing about visualisation. Next time I'll look at ways to use the Processing library as part of larger Java projects, where I'll assume some knowledge of Java and the Netbeans IDE. We can then move on to some fruitful combination of coding and chin-stroking. I'll also be attending the Guardian's data visualisation masterclass and will report back.
Communication and visualisation in research is both absolutely essential and mired in misunderstanding. It's essential, of course: all research needs to communicate its findings. Ideally, we want that communication to be effective. In some fields, communication is not only vital but fraught: the science of climate change faces concerted attempts to distort its output, and some wonder whether researchers are the best people to deal with this.
So what works? And, maybe more importantly, what doesn't work - and why not? The misunderstanding is perhaps quite simple: we think all images are equal. They enter the eye the same for everyone, don't they? Well, no. This post looks at some of these complexities by talking about four different static images: an x-ray, a box-plot, a mind-map and a simple graphic from the Guardian.
Via Planet3.org, the Climate Action Tracker group take a look at where emissions are going given current policy. Note, it's emissions per year. P3 even comes up with a new word for it: a tragictory. Mmm, mellifluous.
We were looking at some of the basic sums elsewhere. It's starting to seem inescapable: short of some miracle, we're going to run the experiment.
It's occurred to me recently that skeptics and deniers can't be blamed for this. I know: there's a powerful, moneyed lobby that's out to spread FUD into everyone's hair. But actually, as many are often keen to point out, there is plenty of money being spent on the 'other side'. I wonder whether (a bit like taketheflourback's contribution, but at a different scale), they've done everyone a favour. Like a global immune response: we should be forced to defend what we think is true, and doing so is the only way to make the body politic's response robust. (Climate scientists already have such a system, mind: I'm talking about the rest of us.)
Climate skepticism and outright denial might just be a convenient scapegoat. If it hadn't existed, I suspect Climate Action Tracker's graph would look exactly the same. As yet - politically, governance-wise - we don't know how to deal with this. At heart, many of us don't want to.
That isn't any reason to stop trying, of course. Anything that can be done, long-term, is going to help - and could make the difference between extreme social cost and utter calamity. Though we would probably be looking at the former, even if carbon emissions were magically halted tomorrow: the climate system's a huge, fast-moving tanker with plenty of inertia in it. But - and I imagine military planners are way ahead of me on this - realistic planning for severe impacts is likely needed. We're upping the risk every year we continue to fumble with this, and risk is very expensive. Eventually, risk turns into out and out destruction.
As if my own mental attitude could make any difference to all this: I still rather naively believe that nihilism is the biggest danger we face. It's a lazy response, more than anything: a pretence that we don't give a shit, used to mask the fact we're desperate for someone else to solve the problem - that Someone In Charge must have a handle on this, surely? We can just relax and live our lives.
Message to future self: how did that work out for you?
A Feynman quote, via Robert Wilson: 'The first principle is that you must not fool yourself, and you are the easiest person to fool.'
This weekend's protest at Rothamsted has reduced a labyrinthine issue to a single outcome: trashed, or not trashed? In our house, we're clear that GM itself is a technology like any other. Fire can cook food, keep you warm or burn your house down. Every single tech we've discovered since has followed much the same pattern. The critical factor is us. (update via Robert: "Related Feynman anecdote. A buddhist monk said to him 'the keys to the gates of heaven also open the gates of hell'.")
But that Feynman quote makes me want to spend a little time picking apart my own assumptions. Rather than actually, you know, do that, I thought I'd just get the questions down while they're sloshing about.
There's a simple lesson from taketheflourback's protest: no part of the political spectrum has a monopoly on scientific befuddlement. It seems almost a trivial point, but it's actually quite slippery. This thought first occurred to me because some people wondered, why so much climate skepticism on the right?
I argued: a lack of similar skepticism on the left didn't imply a greater grasp of climate science. It's just that climate change happens not to clash with most left-of-centre worldviews (except some very far left positions, though unfortunately I'm having trouble finding an example in the 'global warming = global marxist conspiracy' internet swamps). It can also mesh nicely into anti-corporate / capitalist / colonialist stories, as this rather jaunty take on resource wars from Age of Stupid nicely shows.
There's an anti-GM mirror-image of that too: pretty much all climate skeptics are also pro-plant-tech (quite often, even things like pro-DDT).
This is why all the recent US stuff about 'the Republican Brain' was so dismaying. Whatever evidence lay behind it, it's making the same basic error: ignoring scientific illiteracy where it happens to fit our already pre-conceived notions. The natural conclusion - that all right-wingers are scientific dunces - is just plain nonsense. It's also dangerously alienating.