I’m splitting Day 3 in two, as there were three presentations later in the day in addition to the regular papers. They’ll take at least another hour to write up, and right now, I want to sleep. Here’s the papers, three on insurgencies, one on biology:

  • The Role of Influence Operations in a Counterinsurgency Battle by Elise Weaver
    • This author looked at the role of ‘influence operations’ in a counter-insurgency; apparently, that means effort expended to win the ‘hearts and minds’ of the populace in order to diminish popular support for the insurgency and increase support for the counter-intersurgency. She first presented a high level model that gave a general overview of the different types of influence operations and their effects, then presented a number of smaller models that linked into it, each looking in more detail at a particular type of influence operation. These smaller models corresponded to:
      • Attrition
      • Recruitment
      • Intelligence
      • Collateral damage
      • Competitive contagion (the to and fro of popular sentiment)
    • The work was interesting, but it seemed like it was still fairly preliminary – the model seemed very high level, and thus really only managed to confirm results that seemed obvious. The author was quite honest about the drawbacks of her model, though, which is always good, but I think there’s definitely more work needed here.
  • Implementing Irregular Warfare Policy Using Modeling and Simulation by Corey Lofdahl
    • This was one of those papers where I didn’t get a good take home message, but which was nonetheless interesting. In it, the author presented his experience building and presenting models for use by senior NATO decision makers, mostly based on ideas in the book The Quest for a Viable Peace. He didn’t go into a lot of depth on the models, but they covered topics such as government finance, military capacity, political will, and the like. He had a few entertaining stories about dealing with bureaucratic and military egos, too.
  • A System Dynamics Perspective on Insurgency as a Business Enterprise by David Schoenwald, Curtis Johnson, Leonard Malczynski, George Backus
    • This paper took a really interesting and slightly cynical approach to thinking about insurgencies. It started with the premise that many of the monetary feedback loops that are true for business enterprises are probably true for insurgencies. Both require money and, though ideology is a motivating factor for some, many insurgents likely follow a profit based motive, whether money or the power money buys is the final goal. Furthermore, there’s analogies to be drawn between marketing and propaganda, and between customer relations and the threatening, cajoling, and manipulating of the population. Al Qaeda even provides a comparative notion of franchising. Of course, while it’s amusing to make comparisons, it’s important not to get too carried away. The serious intent here was to model and understand the dynamics of money within insurgent organizations, particularly its sources; apparently, the prime ones are kidnap for ransom, drug production, extortion, and black markets.
    • While listening, I went off on a bit of a tangent. One criticism of counter-insurgency efforts is that they help to reinforce a corrupt sitting government. This goes away, however, when one remembers that the point is not to support particular politicians, but to support a working and equitable political system. It seems this must get conflated fairly often, and for a soldier, it must be awful to think that they’re risking their lives to support a set of politicians they really dislike. Moving past that, though, it must be easier to think of the higher motives of reinforcing the institutions that enable a stable state such as, for example, legitimate democratic elections, stable succession, a lack of corruption, basic human rights, and so on. In this sense, too, while the effort starts with counter insurgency, it can’t stop there, otherwise the counter-insurgency is wasted effort.
    • Two final interesting short points
      • Apparently, to reduce drug production, it is more effective to increase the producer’s risk than it is their reduce their production
      • Someone mentioned the quote “Governments need a monopoly on violence”. Cynical, but true.
  • A Simulation Model for Bloodcholesterol Dynamics and Related Disorders by Emre Demirezen, Yaman Barlas
    • Though there were several other science based models presented throughout the conference, this was by far the hardest I saw. It sought to capture the dynamics of cholesterol and other derived compounds in the metabolism of healthy and hypercholesterolemic subjects, with respect to a bunch of factors such as body weight, diet, and exercise. This is really interesting, as though a great many causal relationships between chemicals, cells, and other entities within the body are understood, we really don’t have a good understanding of the dynamics involved and the way in which all of these relationships interact to form stable equilibria. It’s obvious to me that this is one place in which system dynamics can really shine, particularly given the difficulty of understanding systems this complex using other tools.

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I saw six presentations today, three of which were interesting enough to write about:

  • Simulating Pollution from Urban Stormwater in Project Twin Streams Catchment, Auckland, New Zealand by Ines Winz, Gary Brierley
    • As far as I’m aware, the author of this paper was the only other person from NZ at the conference, though I haven’t yet had a chance to talk to her. She presented a model of the impacts of stormwater runoff in terms of erosion and pollution, in that storm water commonly picks pollutants from the land as it runs towards the sea. She sought to use the model to examine and predict the efficacy of different approaches to mitigating the impact of runoff. I picked up one new concept; that of imperviousness – ground coverings and land features that prevent water from being absorbed by the earth, instead diverting it into stormwater drains that generally lead to streams and rivers. Generally, designs that reduce imperviousness are a good thing. Found an interesting primer on the topic here
  • An Operational Framework for Seeing and Simulating Feedbacks in Land Change Science by Burak Guneralp, Michael Reilly, Karen Seto
    • I didn’t get a lot out of the content of this talk, but I liked the modelling technique of integrating multiple system dynamics models together through a spatial model. For example, imagine you’re seeking to model local behaviour in subregions across a large area, where local results have some impact on their neighbours. Using this technique, you’d run models for each subregion in parallel, with each taking inputs and passing outputs to neighbouring subregion models, global models, or perhaps some sort of multi-subregion aggregating models. In essence, you end up with a system dynamics cellular automata, which the geek in me finds particularly awesome.
  • Modeling Insurgencies and Counterinsurgencies by Edward Anderson
    • Apparently models of insurgencies and counter-insurgencies were a big topic this year – one presenter commented that the papers being presented this year represent the bulk of the work in this area over the last ten years. This paper pulled out and modelled insurgencies and counter-insurgency tactics based on the US Army FM 3-24. It focused a lot on population dynamics, including popular support, recruiting, intelligence, and a number of other factors. Of course, given the complexity and uncertainty of contemporary insurgencies, it’s very hard to validate the models, and the authors were up front about that – to cope, they used data from the Irish war of 1919-21, which was simpler (involving only one insurgent faction) and, being historic, was accessible for both sides, though still nonetheless quite sparse. One really interesting summary point from the model: counter-insurgency actions are the only way to defeat an insurgency, but their introduction will always worsen things in the short term and, furthermore, removing them too early may well be worse than not introducing them at all. All up, this was a really interesting paper; Richard – you should look at this.

In the afternoon, I snuck away to visit the Albuquerque Aquarium and Botanical Gardens. There were stingrays, sharks, and a great big tubular tank full of beautiful moon jellyfish lit by the refracted light of various informative displays. On entering the gardens proper, I began to wonder if I’d stepped through a looking glass somewhere on the way as huge fake vegetables, ants, and garden implements surrounded me in a truly surreal setting. The four metre high pumpkin, complete with fake rotting interior was particularly strange. Other parts of the garden were more traditional, with glass houses, a rose garden, and, of course, a great big desert garden. For bonus points, there were lots of hummingbirds and dragonflies. Photos of all this when I get back to Seattle.

After a quick trip back to my hostel to change into something a bit more formal than shorts and t-shirt, I returned to the conference hotel for the conference banquet. The food was great, and the scotch was cheap. After the obligatory speeches, there was traditional Navajo dancing, a little more scotch, and an hour reclining in a chair on the portico outside the conference hotel watching the clouds drift by, chatting, and enjoying the warm night air. Divine.

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The day begun with a keynote by Dennis Meadows on his ‘Limits to Growth’ work. I came away the following ideas:

  • There’s a distinction between global problems and universal problems. Global problems affect everyone and cannot be solved without cooperation from everyone, whereas universal problems affect everyone but can be solved by local groups. Some issues mash up global and universal issues. For example, climate change a global problem, but its effects effects are universal problems; that is, we can’t stop climate change without global collaboration but we can deal with rising sea levels on a local level. Obviously, universal problems are simpler to deal with.
  • There’s another distinction between preventive and adaptive policy. Preventive policy seeks to address potential future problems, while adaptive policy seeks to mitigate current problems. Adaptive policies are easier to gain support for because they address problems whose effects are immediate.\
  • A disproportionately large amount of the innovation going on with respect to limits to growth is happening at the local and metropolitan levels. Why is this? There seems to be a lot of possible reasons, here’s a few off the top of my head: local government has control over much physical infrastructure that can be adapted, smaller groups are able to reach consensus more easily over desirable projects, less variation in the political views of people in local groups as compared to national groups. This would make an interesting problem for someone. What do you think?
  • Malthus was right, just a bit early. If we’re serious about reducing the human impact on the planet, we need to be serious about reducing or even slightly reversing population growth. Even if in the longer term we think we can adapt ourselves and our practices to increase the Earth’s carrying capacity, it’s still arguably the case that reduced population growth would help support higher living standards across the world.
  • Sustainable doesn’t mean cheap. In some cases, durable, well-made, luxury goods are more sustainable than cheap disposable goods. Compare a expensive pen that can be refilled and that is well cared for with a simple throwaway, disposable pen.
  • Drawing from the previous example, sustainability pertains strongly to behaviour, not just technology. Arguably, we can improve the sustainability of our lifestyles more through behavioural changes (though not just recycling!) than through technical changes.

Next up was the morning’s parallel session. I was a little distracted as I was presenting my paper “Exploring the dynamics of Music Piracy”, so I didn’t take notes on any of the other papers during this session. There was one in particular I wanted to see, but regretfully couldn’t: “Economic Origins of the Mafia and Patronage System in Sicily“.

For lunch we tried out a local burger chain. It was .. interesting.

Unfortunately, of the papers I saw in the afternoon, three out of five really didn’t grab me. Another, “Model-based exploration of strategies for fostering adoption of improved seed in West Africa“, was quite interesting, but my laptop was out of battery so I didn’t get good notes. Worth a look if you’re into intellectual property, biotech, or developing nations.

The last paper, “Developing Causal Map Codebooks to Analyze Policy Recommendations“, by Michael Deegan was particularly interesting. It sought to analyze the structure of policy recommendations in order to understand why recommendations are very rarely followed (at least in the domain and context of flood plain management by the US Army Corps of Engineers). Here’s what I took away:

  • There’s a variety of reasons why  recommendations might not be taken up. They may be complex and difficult to understand by non-expert policy-makers; they may be too massive and intricate; there may incorporate significant uncertainty; they may be impossible or impractical to implement in an accountable manner; or their implications might not be clear. On top of these chiefly bureaucratic reasons, there are the normal political considerations of ideology, budget, time, political capital, emotional appeal, and special interests.
  • The core idea was that by drawing causal maps of a recommendation, including all of the causal relationships and arguments that drive it, it can be made much more accessible both to policy makers and the public, thereby increasing the likelihood that they will be taken up. The basic idea, then, is that arguments can be teased out of prose and into graphical diagrams, helping to reveal the complexities, fallacies and implications that would otherwise be hidden. I’ve toyed with this in the past to the point of half writing a proposal based on it, and so I made sure I had a good chat with the author afterwards. I’m particularly interested in the idea of an intelligent parsing agent that is able to extract arguments from text and graphically represent them. In doing this, their structure would become computationally manipulable, enabling tools that correct, interpret, or integrate arguments. I should probably finish writing this idea up at some point.

The day ended with a reception at the Albuquerque Museum. There were the normal speeches, then a marvellously enthusiastic musical group consisting almost entirely of marimba players. They were both inspiring and amusing to watch, what with the furiously pounding on a giant bass marimba and the general leaping about. Photos later.

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Sunday was the PhD colloquium. It was smaller than the full conference has been, but there were still about 50-100 people in attendance. In the morning, there were several presentations, 3 of which I unfortunately missed due to my late arrival the night before, followed by a luncheon. Then, in the afternoon, there was a poster session, some meetings, and a really interesting panel.

After picking up my copy of the conference schedule from registration, one thing became really obvious – there’s a lot of stuff crammed into this conference. Six parallel paper tracks, as well as workshops, chapter meetings, special interest groups, workshops, and all the normal social events.  This is both good and bad – good because it’s rare that there’s nothing interesting going on, bad because conflicts between things you’re interested in are common.

Here’s the stuff that grabbed my interest on Sunday:

  • Tommy Ka Kit Ngai from the U of Cambridge talked about the distribution and uptake of clean water filters in a South Indian case study. Interestingly, he sought to integrate the widely diverse ways that uptake has been explained in the past into a single model. There were two interesting points comments that came up in the discussion:
    1. One guy was very keen to put a dollar figure on the cost of providing the filters to people versus the cost of not having clean water. Given the severely negative impact of tainted water on one’s health, this seemed kinda abhorrent, but his argument was that this would actually make it easier to convince governments and other NGOs to fund water filter distribution. Though it seems plainly obvious that clean water is a Good Thing, I guess he had a point in that the economic argument, ignoring all the humanistic and qualitative factors as it does, is more concrete and thus more compelling to bureaucrats.
    2. Someone else speculated that randomness played a role in concealing the individual benefits of using a water filters. Imagine people get sick 4 +/- 2 times a year if they’re drinking dirty water, and only 2 +/- 1 if they’re drinking clean water. The difference is visible statistically, but in many cases, an individual’s sample size of one could make this difference quite difficult to discern. In cases like this, people are then reliant on the authority of outside agencies to tell them that water filters are good for them. Much better is to have a way of making this difference visible to them. One suggestion might be to have a glass jar sitting somewhere public in the community. Every day someone’s sick, add a pebble to the jar. Do this for three months, then give people water filters and do it again for another three months. Compare the jars. There’s obvious ethical and sampling problems with this, but you can see how useful the general idea of making the causal link popularly visible is.
  • Met a guy at the luncheon with a truly magnificent mullet. He also gained bonus points as his reason for being at the conference was “I come here on vacation”. I heartily approve of that attitude.
  • The ethics panel was really good. Model building is at the centre of many contentious issues in policy and business; salient examples include financial models and the current economic crisis, and climate models predicting climate change and destabilization. Furthermore, models often insulate decision makers from the systems they govern, and consequently model builders have a great deal of power and thus a great deal of responsibility. This means that ethics are critical in this discipline. The panel had three members: Alan Graham, Dennis Meadows, and Kim Warren. Here’s what I got from it:
    • Dennis gave a neat demonstration of the principle of “it’s not what you say, it’s what you do”. He told us he would count down from three, then say “Clap!”, at which point we were to clap in unison. He counted down, clapped himself, then, after a pause said “Clap!”. We, of course, all clapped when he did, not when he told us to.
    • Dennis also argued that professional ethics flow from personal ethics and that the best way to develop strong professional ethics is to focus on strong personal ones. He gave a lot of generally good advice about honesty, scrupulously honouring one’s commitments, knowing one’s limits, relating well with and supporting others, and general humility. Three cool bits: firstly, a quote by Janice Joplin “Don’t compromise yourself, it’s the only thing you’ve got”, which I quite liked; secondly, the idea that one is committing an injustice when one gets into relationships that benefit only one party because exploitation is wrong and charity only works when it’s genuine and not onerous; and thirdly, the suggestion that one should decide where one’s ethical boundary lines lie in advance of them being challenged, because otherwise it’s far too easy to make compromises that one is unhappy with.
    • Alan talked a lot about being honest concerning the limits of one’s tools. Like any tool, System Dynamics is sometimes helpful, but comes with built-in limitations. His recommendations: do not oversell the tool, and be careful not to let your clients overrate its effectiveness; be very careful not to mislead people or allow the perception that this may have occured; and, avoid even the smallest falsehoods, as these will be mercilessly exploited the moment your work becomes contentious. A couple of interesting points came out in his discussion. What do you do when the client takes your model and misleads others with it? To what extent should you get into technical details which might confuse or mislead clients? He suggested that one should clarify carefully the nature of one’s obligation to  client and, where possible, the uses to which one’s model will be put.
    • Kim built on this by talking more about ethical dilemmas. He outlined situations where ethical obligations to the client conflict with ethical obligations to society, then talked a bit about ways of rationalizing and making decisions in such situations. Like Dennis, he emphasized the importance of defining one’s ethical boundary in advance. His discussion also emphasized the need to think about the long term or indirect consequences of a model. While he didn’t seek to convince us that his that his approach was definitely right, he did seem to employ a fairly utilitarian mindset. So, for example, if one’s model suggests implies that a division of company is dragging that company down, it may be ethical to recommend the elimination of that division, despite the effects on the individuals working withing, if not doing so would risk bringing down the whole company, thus jeopardizing the jobs of everyone in the company. Another example involved offering strategy to a company such that they might act anti-competitively or even destroy a competitor. In that case, he said that after consideration, he resolved his ethical issues by making a value judgement and determining that the competitor being destroyed were harmful in some way, and that their elimination would be good for society as a whole. This is interesting, because it really reveals the subjective nature of ethics of this sort.

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So, I’m at the 27th International System Dynamics Conference in Albuquerque, New Mexico, at the moment and, like any wannabe writer with a blog, I’m going to make an attempt at live blogging it.

My flights were nice and comfortable, though the second one, from Phoenix to Albuquerque was seriously delayed. At first, this was due to the plane lacking some internal power unit necessary to start the engine, thus requiring the use of some special plane starting device on a truck. Then, once that was sorted, we still had to wait for the plane to cool down – apparently sitting in the sun for a day in Arizona means an internal temperature of something like 55 degrees Celsius (130 F). As a result, I didn’t get to Albuquerque till about 1:30am, well after the office closed at my hostel. By the time I’d woken one of the staff, found my key, and all that, I didn’t get to sleep till about 2:30am.

Figuring that I wouldn’t get much out of the day if I didn’t have at least 7 hours sleep, I skipped the first couple of presentations, and arrived there a little after 10:30, just in time for the end of a presentation on some kind of network modelling.

Before I start talking about specific presentations, though, I should first provide a brief overview of System Dynamics for the uninitiated. Basically, it’s a method of modelling the dynamics within complex systems by specifying mathematical relationships between specific quantities both abstract and concrete. It’s different from a lot of mathematical models because it focuses on the relationships within whole systems and the simultaneous dynamics of multiple variables, rather than focusing on specific individual variables in isolation. There’s a number of relatively famous books either about or employing System Dynamics that you may have heard of:

System Dynamics is related to the work of Norbert Wiener, the General Systems Theory of Bertalanffy, and the cybernetics employed by James Lovelock in his Gaia hypothesis. It’s variously called systems thinking, industrial dynamics, business dynamics, and many other things. There are, apparently subtle differences between all of these, but I’m too new an initiate to know them. Working with it leaves you talking a lot about positive and negative feedback loops, stable and unstable systems, death spirals, exponential and goal-seeking growth, and exogenous and endogenous variables. If any of those phrases sound familiar, you can probably work out approximately what this is all about.

I’m hoping this description isn’t just making you more confused, but I know it’s only just scratching the surface; for a better introduction, check out the article on wikipedia.

Like any modelling methodology, the predictions of made by models in this field are by no means perfect, but it has the advantage that much of its discourse involves explicit acknowledgement and discussion of the sources of model error. Errors often come from boundary conditions (which factors do you model, and which do you leave out?), nonlinearity and discontinuity (how reliable is our knowledge of the relationship between correlated variables?), and input data (how reliable are the statistics you’re putting into your model?). Even ignoring the precision or accuracy of its predictions, System Dynamics offers a way of examine the relationships between the parts of one’s conceptions of a real world system, bringing up inconsistencies and fallacies that would otherwise have gone unnoticed.

That’s enough for this post. Hopefully, tonight I’ll post highlights of the first day of the conference, otherwise I’ll wrap it in with tomorrow’s events.

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Another quick observation about motivation:

I was lying in bed just now, tired and thinking of sleep. I picked up the book I’m currently reading (the 2008 Year’s Best Fantasy & Horror anthology, if anyone cares), thumbed to the next story, but barely made it to the end of the second paragraph before giving up.

I was about to get up and turn of the light, but for no apparent reason, I picked up a random paper that was sitting on the pile of books next to my bed. I didn’t intend to actually read it – after all, if high quality short fiction can’t hold my attention, dry academic writing certainly won’t do any better – but for some reason I ended up flicking my eyes through the abstract. I wasn’t taking much in, but for some reason I stuck with it long enough to encounter some survey results that were quite interesting, enough so that I felt like writing some quick notes about it in Evernote. So I did.

But then something interesting happened. The motivation I had for my original note-taking gave me a little momentum, and instead of turning the laptop off and going to bed like I originally intended, I suddenly felt like doing something useful, in this case, writing a paper review that I’ve been putting off for about a week, and then writing this.

Why’s this interesting? I’m intrigued by the idea of motivation having momentum. That by getting excited about some small, easy task, I can carry that over to feeling motivated about some larger task. Thinking back, this is definitely something that’s happened before, and that I think I sometimes take advantage of, but never explicitly. I should try to employ this more often.

Actually, thinking on it, this relates to some great advice I got once about writing. If you’ve got some big writing task that’s really hard to start on, just commit to sitting down in front of the computer, loading up the word processor, and looking at it. You don’t have to do anything more than that. More often than not, you’ll want to write a few words down, and sometimes, you’ll get sucked in. Here, like above, the momentum of defeating a small task carries you into defeating a larger one. I think I’ll have to write more about this in the context of writing some other time.

Oh, and by the way, the paper was about the sociology of strategy board games. You can bet I’ll write something about it some other time

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Yesterday was very strange.

Do you ever have those days where you just can’t get anything done? Where all of the things you know are important just seem silly and pointless? Where a Herculean effort is required even to force yourself to put your laundry away?

Of course you do. Everyone has bad days. If you don’t, please comment and tell me your secret.

The thing is, there wasn’t anything actually wrong yesterday. I was in palpably good humour, the weather was pleasant, and nothing went particularly wrong, with the exception of me leaving my gym gear at home, thus being unable to go to Kung Fu practice, my last chance of salvaging the day.

OK. So I get that bad days sometimes happen. But here’s the weird thing. When I finally went to bed late that night, I picked up my notebook and started thinking about the things I needed to do the next day. As I looked over the notes for my various projects, the scrawled to-do lists, and the barely legible Awesome Plans, I felt enthusiastic, organized, and in control. “Huh, that’s funny. I guess the bad day is over”, I thought to myself. “Maybe tomorrow will be better”. A few minutes later though, I got to thinking back on the day, idly wondering which of my many tasks I could have got done had I been less out of it. Those same tasks, which had seemed interesting and important a few minutes ago, suddenly become lackluster, and even painful to contemplate, merely by me having placed them in the context of the bad day.

While I’m sure this has happened to me before, this time I noticed it clearly, and had the presence of mind to play with it a little. By switching back and forth, I could discern that framing tasks in the context of the bad day made them awful, while framing them in the context of the next day made them seem exciting. It was like there was some unholy taint associated with the bad day that spread to anything I contemplated, and even though this was all in the past and there was no way I could make myself perform those tasks in that context, they still felt horrid!

This makes no sense!!

The perception that a day is bad doesn’t seem like it should affect my perception so much. But moreso, I never thought I could manipulate my own enthusiasm and motivation in such a way. Of course, this was a special case – while I could try to avoid thinking of things within a negatively loaded context like this, I don’t really grasp yet how I could use this to positively motivate myself. The experience has opened my eyes to this as a possibility, however.

For the moment, then, the lesson I’m taking is that context plays a much larger role than I ever realized in determining the desirability of things.

Just another way in which we humans aren’t entirely rational, I guess.

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Today is the 40th anniversary of the Apollo 11 moon landing, and if that’s not worth celebrating, I really don’t know what is.

Lots of people are celebrating, of course. Here’s a few sites worth checking out:

Incidentally, NASA itself is just over 50 years old, having celebrated its 50th birthday on July 29 last year. The 50th anniversary website is still up, with videos, lectures, articles, and a photo set called “50 Images, 50 Years“, containing many cool photos.

While writing this, I got to thinking: “40 years is quite a long time, I wonder how old those astronauts are now”. Turns out the youngest man alive who has walked on the moon is Charles Duke, who is 74 years old, while the oldest is good old Buzz Aldrin (whose foot you see at top right), at 79. That’s just a bit scary. We’re probably only 5-10 years from losing first hand experience of walking on another world. While I totally grok that unmanned spaceflight is a far better bet for science and exploration, it’s still a little saddening.

There’s one other celebration I didn’t mention yet. After at least two years of work, we’ve finally launched the new Orion’s Arm website. You might think two years is a long time to make a website, but bear in mind that this was done entirely in volunteered spare time, and involved a complete overhaul of the site’s entire content, which at a recent count was 1.4 million words in total. While I did all of the technical work, the real credit goes to Todd Drashner, Stephen Innis, Steve Bowers, and several others assisting them, who painstakingly read, edited, marked up, and in some cases, completely rewrote the whole thing.

Edit: I just had to include this link to “The Eagle Has Landed“, an award winning documentary from 1969 full of Apollo footage, stills, and audio recordings. Hat tip to Abstruse Goose

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This is the third in a series of posts about music appreciation. In previous posts, I argued that:

  1. Explaining our preferences with ‘taste’ doesn’t help a lot. All it really does is hide their complexities and protect us from the challenge of having to explain ourselves.
  2. Preferences are better explained using ‘facets’ of appreciation that each captures a different way that music might stimulate us. This by no means eliminates subjectivity, but providese a vocabulary, we can use to more easily understand and talk about preferences.  In particular, we become able to describe different people’s taste as differences in the priority or content of the facets they use.

So, what are some example facets? Here’s a list of the ones I’ve been able to identify so far:

  • Structure – The simplest facet is that of musical structure. It’s obvious to every listener that different styles of music have different structures to them, and it seems that, likewise, different listeners have different affinity for different structural elements. Some listeners like complex layered melody, while others prefer simple, accessible tunes. I’m no expert in music theory; my point is that musical structure plays a role in defining our preferences, and that there is no universal agreement on what makes for ‘good’ musical structure (excluding, perhaps, chaos and discordance). Here are some structural elements I commonly consider when trying to explain my own preferences:
    • Harmony
    • Melody
    • Beat & Percussion
    • Complexity
    • Tone
  • Nostalgia – There is some music that I like simply because it reminds me of a particular time, place, or event in my past. This facet is extremely subjective, and often difficult to explain in other ways. For me, examples of this are the Phantom of the Opera (which I listened to a lot when I was about 10), remixes of the music from old Commodore 64 games, and music like Shriekback, Sisters of Mercy, and Headless Chickens, all of which remind me of parties. Depending on the emotional character of my response, nostalgia might cause me to really like a piece of music, or really hate it.
  • Milieu – Similarly to nostalgia, some music evokes a particular setting, or place, or environment, and gains emotional significance from this that affects appreciation for it. The difference is that the association is not based strongly on a particular past experience. For example, one might appreciate music that evokes a particular historical period, or music that is ‘science-fictiony’. This is less subjective than nostalgia, but still quite so.
  • Emotional – Music very often evokes particular emotional responses that are not associated with any particular memory or milieu, but are the result of the music’s style, key, tempo, use of motifs and so forth. This form of emotional response to music seems the least subjective; for example, people can often agree easily on whether music is sombre, cheerful, or inspirational.
  • Utility – A lot of people seem to appreciate music that is good for some particular purpose. This might be music that’s good to code to (for me, that’d be Jeroen Tel, Machinae Supremacy, and similar stuff), music that’s relaxing, music that’s good to dance to, or even music that’s good to garden to (Vangelis’ Soil Festivities).
  • Skill Display – Some music is attractive because of the performer’s skill. This occurs often when there is strong emphasis on a solo performer, such as in violin concertos, jazz, and some prog rock. I also get this feeling when I watch group performances where, in addition to their skill in playing their instruments, the performers exhibit great skill in coordinating their performance. For some people, there’s a point at which displays of skill shift from awesome to pretentious, but to some extent, I think virtuosity is a fairly universal facet of apprecation. Incidentally, in his cluster definition of art, Dutton identifies skill display as one of its key features (see my previous post).
  • Fellow Musicians – I’m not particularly skilled in any instrument, but I know that players of an instrument can appreciate music using that instrument on a level that non-players cannot, because they can consider in more detail the skills and techniques that the performer is using. Fellow musicians might also appreciate music because of the joy it gives them when they perform it themselves. For example, I particularly enjoy music that I can sing to.
  • Social – Music often plays important social roles. It might signal membership of some group, it might be linked with particular social or cultural phenomena (birthday songs, carols, Auld Lang Syne), it might have some ritual meaning (hymns), or it might be a way of establishing group solidarity (anthems). This can apply to groups of any size, from nations to couples (“it’s our song!!”, she exclaimed).
  • Novelty – Novelty definitely affects appreciation. Songs can get old over time, and there’s a definte good feeling associated with discovering a new band. That said, there’s a point where nostalgia takes over, and old songs are revived (80s music!). While I enjoy finding new music, I think this facet isn’t as important to me as it is to others; I’d usually rather let other people go searching, then ask for their recommendations.
  • Narrative – Music, like much other art, can tell a story, and appreciation of that story affects appreciation of the music overall. Narrative might be overt, dominating and structuring the music (musicals), it might be more abstract, where the relationship between the narrative and music is less clear (movie adaptations and medleys), or it might be subtle, where the narrative is embodied in the structure of the music and not made explicit (The Firebird, Rimsky-Korsakov’s Scheherezade).
  • Lyrics – Music often has lyrics, and these can significantly affect appreciation, not at the level of narrative, but at that of words and phrases. Depending on the topic, lyrics are often unimportant to me, particularly given the normal topics of love, sex, and betrayal. Lyrics that are political or philosophical, though, seem better able to grab my attention. One good example is ‘Amused to Death‘ by Roger Waters.

Obviously, this list isn’t exclusive, nor does it correspond to anything empirical – it’s almost entirely a product of introspection, with much inspiration from talking to others about their preferences over the years. I’m simply trying to build a vocabulary of ways in which we can think about our preferences for music so that I can avoid having to talk in simple terms of taste.

I’d be particularly interested to hear suggestions for other facets if you’ve got them..

As mentioned in my first post, I doubt any of this is original, but this doesn’t concern me. In fact, I’d be really interested to see research looking at this sort of thing – I’d be particularly interested in seeing, for example, some sort of data analysis performed on responses given by listeners trying to explain their reaction to particular pieces of music.

In my next, and probably last, post on this topic, I want to talk about the why of all of this – why I find preferences interesting to discuss, and why I get driven insane by people taking my desire for analysis of taste as being somehow critical of them.

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