Reviews


Only what you see man, only what you see

Only what you see man, only what you see

Today a friend took me, without explanation, to see Sophie Calle’s The Unsold (売り残し) at Koyanagi Gallery in Ginza. I don’t often attend art shows – let alone modern art installations – and I almost never visit Ginza, so this was a real novelty for me, but despite my initial misgivings it was definitely worth it. Here is my review.

When I entered the gallery my first glance revealed an installation of everyday objects, including two dresses, that to my jaundiced and cynical eye immediately resembled Tracey Emin’s execrable bed-type stuff, and I was immediately disappointed. However, right at the door there is an introductory explanation (in Japanese and English) of the premise of the work, which changed my mind. Basically, three artists set up a flea market in the grounds of Yasukuni Jinja. They laid out their wares on three squares of cloth, as shown in the picture. One (I don’t recall which) sold worthless every day items, to each of which was attached a story that actually happened (i.e. a real story) with some relationship to the item but in which the item itself was not directly involved (so e.g. the typewriter on sale is not necessarily the typewriter from the story). Another sold a mixture of semi-antiques (cutely mis-spelled as “semi-antics” in this exhibition) and ordinary items, to which were attached completely fake stories with apparent emotional content[1]. The third sold actual antiques, and one of his original photos. For example one person was selling a completely normal bra for about 25,000 yen, and another person was selling a picture of a psycho-analyst (freud?) for 38,000 yen. One of the antiques was an ancient ceramic hot water bottle, and the picture was a pretty cool sea/sky thing. Each artist catalogued what they sold and the amount of money they sold it for – which was surprisingly large. Apparently an American tour guide passed by as this sale was going on and told his charges “there is nothing here, ignore it.” (Cute). The explanation finishes with the simple, curt phrase “These are the unsold.” So the exhibition consists of the material that was not sold.

This exhibition consists of three pieces of cloth on which the remaining items are laid out, attached to each of which is a tag with the price and the story. Behind each installation, on the wall, is a photo of the original setup, so you can see what was sold. On the opposite wall are the tags for the sold items, with their corresponding story. These tags have no information about the item to which they correspond, so you have to wander across to the original picture and guess. The stories are really interesting and believable, though whether they are actually true or not I have no clue. Investigating on wikipedia I discovered that the Eiffel tower story is true, and just as unbelievable as it sounds – Sophie Calle certainly knows how to do crazy things (I can’t remember if the item attached to this story was sold or not).

I’m an uncultured barbarian, so I have no idea what this installation was trying to tell me about whatever, but I thought it was really cool. Trying to understand why people bought these ludicrously overpriced objects because of their vague stories, or didn’t buy some object even though its story was cool, was an exercise in intruding into someone else’s private life. The stories themselves were fascinating, disconnected monologues, none of which I believed (but some of which I have subsequently learnt are real!) I can’t speak for the Japanese but the English used in the broader narrative descriptions – what the exhibition is about, how the artists met – is clear, sparse and strong. The structure of the main introductory sign and its finishing statement, “These are the Unsold” is particularly powerful, and suits the style of the exhibition. It’s a simple idea done well, and it holds your attention. Why did the passersby leave the charred bedspring and buy the useless typewriter? This, I cannot fathom. I wouldn’t buy the red bucket some guy pissed in, but why would someone else buy the bottle. Also the story of the horn is acutely sad and the horn is quite cheap, but apparently un-sellable. What does that mean?

I didn’t know anything about Sophie Calle before this exhibition, but reading her Wikipedia page I get the impression that she is a powerful, prodigious and generally unethical talent. My friend has also seen the exhibit Take Care of Yourself, which as the quoted reviewer says seems to be both shallow and deeply engaging. Her attempt to get blind people to define beauty sounds like it has the potential to be very powerful (I don’t draw any conclusions!) and the work where she gets a guy to shadow her and then presents pictures of herself sounds really interesting. Invading others’ privacy, not so much. How come medical researchers have to get ethics approval, but French artistes can pursue some guy across the world, or hijack a stolen diary for money?

Don’t answer that.

Anyway, I’d never heard of Sophie Calle before today and I think her work is a genuinely interesting and challenging example of modern art at its finest. I don’t know what she’s trying to say with this exhibition and I can’t really say what I think of it, but it’s really cool. It would be better if she followed it up with some kind of article in a peer-reviewed journal giving her conclusion about what the purchases and non-purchases mean, instead of leaving it to an ignorant rube like me to try and understand, and if she had found a way to summarize what was bought and wasn’t (e.g. rankings with stories, or a website where you can see all the objects with what was bought and what wasn’t, and its story) then the exhibition would have been even cooler. But despite these missed opportunities this exhibition is very cool, and in general I have to say Sophie Calle’s work seems pretty interesting. I hope more of her stuff comes to Japan, and I recommend visiting it if you are in Japan, or keeping an eye out for her work if you are not.

 

 

 

fn1: I may be mis-remembering the exact nature of what these items were, but I hope you get the general gist.

I’ve recently been building a fairly complex series of Bayesian spatial regression models in BUGS, and thought I’d share some tips based on hard won experience with the models. The various BUGS packages have the most cryptic and incoherent error messages of any stats software I have ever worked with, and although various Bayesian boosters claim that their modeling approach is intuitive, in my opinion it is the exact opposite of intuitive, and it is extremely hard to configure data for use in the packages. Furthermore, online help is hard to find – google an error message and you will find multiple websites with people asking questions that have never been answered, which is rare in the modern world. I take this as a sign that most people don’t understand the error message, and indeed the BUGS manual includes a list of errors with “possible interpretations” that reads more like the I Ching than a software guide. But Confucius say Enlightenment is not to be found in Black Box Pascal, so here is my experience of BUGS.

The models I’m running are complex, with nested conditional autoregressive structures and the higher level having more than 1000 areas with complex neighbour relationships, and millions of observations. I originally ran them on a completely hideous Hewlett Packard laptop, with 4 cores and 8Gb of RAM. I subsequently upgraded to a Dell Workstation (joy in comparison to HP’s clunky root-kitted horror) with 8 cores and 16Gb of RAM; I’m not sure that hardware is the main barrier to performance here though …

The HP machine had a secret administrator account (arseholes!) so I couldn’t install winBUGS[1], so I started off running OpenBUGS called through R’s R2OpenBUGS package running in RStudio. I use R to set up the data and initial values, because I can’t think of any other way to load millions of observations into a text file without going stir crazy. But when I call OpenBUGS it just hangs … no error messages or any other kind of indication of what is going on. I also can’t tell if it is happening at the data loading or compiling or inits stage.

Some digging around online and I found an old post by Andrew Gelman, observing that BUGS does not work well with “large datasets, multivariate structures, and regression coefficients.”

i.e. pretty much every statistical problem worth doing. Gelman also notes that “efficiently-programmed models can get really long, ugly, and bug-prone,” which seems like a contradiction in terms.

Anyway, noting that my data was large, with multivariate structures and regression coefficients, I thought maybe I should tone it down a bit so I tried using a higher level of spatial heirarchy, which reduces the adjacency matrix by an order of magnitude. Still no dice. It was at this point that I upgraded to the bigger computer.

On the bigger computer the smaller model actually worked! But it didn’t work in the sense that anything meaningful came out of it … It worked in the sense that it reported a completely incomprehensible bug, something like a node having an invalid value. I tried multiple different values and nothing worked, but somewhere on the internet I found someone hinting that you should try running BUGS directly rather than calling through R, so I tried this … having created the data in R, I killed OpenBUGS then opened the OpenBUGS interface directly and input the model, then the data, using the text files created by R[2].

When I did this I could step through the process – model was syntatically correct, then model failed to compile! Given that loading inits comes after compilation, an error telling me that I had the wrong initial value seems a bit misleading… in fact I had an “index out of range” error, and when I investigated I found I had made a mistake preparing one part of the data. So where the actual error was “the model can’t compile because you have provided the wrong data,” when called through R the problem was “you have the wrong initial values” (even though I haven’t actually loaded initial values yet).

WTF?! But let’s step back and look at this process for a moment, because it is seven shades of wrong. When you run R2OpenBUGS in R, it first turns the data and inits into a form that OpenBUGS can read; then it dumps these into a directory; then it opens OpenBUGS and gets OpenBUGS to access those files in a stepwise process – at least, that’s what I see R doing. If I decide to do the model directly in the OpenBUGS graphical interface, then what I do is I get R to make the data, then I use the task manager to kill OpenBUGS, then I call OpenBUGS directly, and get OpenBUGS to access the files R made in a stepwise process. i.e. I do exactly the same thing that R does, but I get completely different error messages.

There are various places on the internet where you might stumble on this advice, but I want to stress it: you get different error messages in OpenBUGS run natively than you do in OpenBUGS called through R. Those error messages are so different that you will get a completely different idea of what is wrong with your program.

Anyway, I fixed the index but then I ran into problems after I tried to load my initial values. Nothing seemed to work, and the errors were really cryptic. “Invalid initial value” is not very useful. But further digging on the internet showed me that OpenBUGS and WinBUGS have different approaches to initial values, and winBUGS is not as strict about the values that it accepts. Hmmm … so I installed winBUGS, and reran the model… and it worked! OpenBUGS apparently has some kind of condition on certain variables that they must sum to 0, while winBUGS doesn’t check that condition. A free tip for beginners: setting your initial values so they sum to 0 doesn’t help, but running the same model, unchanged, in winBUGS, works.

So either OpenBUGS is too strict, or winBUGS lets through a whole bunch of dodgy stuff. I am inclined to believe the former, because initial values shouldn’t be a major obstacle to a good model, but as others[3] have observed, BUGS is programmed in a completely opaque system so no one knows what it is doing.

So, multiple misleading errors, and a complex weirdness about calling external software through R, and I have a functioning model. Today I expanded that model back to the original order of magnitude of small areas, and it also worked, though there was an interesting weirdness here. When I tried to compile the model it took about three hours, and produced a Trap. But the weird thing is the Trap contained no warnings about BUGS at all, they were all warnings about windows (something called Windows.AddInteger or similar), and after I killed the Trap my model updated fine. So I think the compile problems I previously experienced may have had something to do with memory problems in Windows (I had no problems with badly designed adjacency matrices in the larger model), but OpenBUGS just doesn’t tell you what’s going on, so you have no idea …

I should also add, for intrepid readers who have got this far, that this dude provides an excellent catalogue of OpenBUGS errors with his plain English explanations of what they actually meant. He’s like this mystical interpreter of the I Ching for Bayesian spatial regressives. Also I want to add that I think the CAR spatial correlation model is super dodgy. I found this article (pdf) by Melanie Wall from the Journal of Statistical Planning and Inference (what a read!) that shows that the way we construct the spatial adjacency matrix is the primary determinant of the correlation structure, and that the correlation structure determined by this adjacency matrix is nothing like what we think we are getting. Today on my whiteboard and with the help of R I imagined a simple industrial process where each stage in the process is correlated with the one before and after it, and I showed very easily based on Wall’s work that the adjacency matrix required to describe this process is completely different to the one that you would naively set up under the framework described for CAR modeling. So I think most of the “spatial correlation” structures described using CAR models have no relationship to what the programmer thinks they’re entering into the model. But I have no proof of this, so I guess like everyone else I’ll just press on, using the adjacency matrix I think works …

So there you have it. Next time you see an opinion formed on the basis of a spatial regression model built in BUGS, remember the problems I had getting to the output, and ask yourself – do you trust that model? Really?

fn1: Well, I could copy winBUGS into the program files folder but I couldn’t patch it or install the immortality key, which, wtf? When I bought Time Series Modelling and Forecasting by Brockwell and Davis, ITSM came as a free disk with the book. When I buy the BUGS book I get to install software that comes with a big message telling me to get stuffed, and years later they finally provide a key that enables you to use it for free …

fn2: If you aren’t aware of how this works, basically when you call OpenBUGS in R, providing data from inside R, R first dumps the data into text files in the directory of your choosing, then OpenBUGS opens those files. So if you aren’t comfortable preparing data for BUGS yourself, use the list and structure commands in R, then kill OpenBUGS and go to OpenBUGS directly … the text files will remain in the directory you chose.

fn3: Barry Rowlingson does a pretty good job of showing how interesting and useful spatial analysis can be: see e.g. his post on mapping the Zaatari refugee camp in Syria.

Galadriel goes to market

Galadriel goes to market

One of the English loan-words that Japanese people misuse slightly in a really cute way is gorgeous (ゴージャス). In Japanese gorgeous refers not to something really nice, but to something that is overdone or just a bit too much – not necessarily unappealing or unattractive, but just a bit too much. I’ve heard the word applied to appearance, food and even writing (e.g. scientific writing should not be gorgeous). It’s often associated with the stylistic choices of young women of a certain social class, and also with hostesses. It’s not necessarily a marker of class or taste, and not deployed in a particularly judgmental way, but it suggests a certain immaturity or inelegance in taste, something that’s acceptable in young women but not for example something one would respect in an adult[1].

The Hobbit: Battle of Five Armies is the cinematic showcase for this word. It’s too long, the battle scenes especially are unnecessarily embellished, and the heroism is over the top and over-frequent. Almost every moment of it is also great fun. These battle scenes are the kind of battles where you can imagine seven impossible maneouvres before breakfast, where enormous and terrifying trolls are killed with a single knife stroke, and where a war pig can be more terrifying than a giant. There are even sand worms! As battles go it’s a tour de force, the entire movie is basically one long series of battles, with maybe two brief pauses to discuss the importance of family and tasteless jewellery. The centerpiece battles – between the Uruk Hai and the dwarven heroes – are masterfully done and very enjoyable, but they’re so over the top as to be ridiculous. They’re also good examples of exactly what gorgeous means: for example, Legolas’s prancing up the collapsing tower is precisely how I imagine an elf to be able to move against the laws of nature, it’s the right thing to be in this kind of movie, but it is dropped into the middle of such a long-running series of epic-level feats that instead of being stunning and impressive, it’s just another blister of impossibilities on the back of your retina.

In this regard the movie can be contrasted very effectively with other works from the same series. The final battle between the fellowship and the Uruk Hai in The Fellowship of the Ring, for example, is a masterclass in how to turn a classic role-playing battle into believable cinema. It depicts a group of high-level characters at the peak of their power pulling themselves out of what is basically a lethal ambush by overwhelming numbers, with minimal losses. They do things we know are physically impossible, but they aren’t so far from impossible that we are lifted out of the feeling of the battle by them, and they aren’t so fast-flowing that they become overwhelming in their fantasticality. That battle is heroic fantasy at its finest, patently unrealistic but completely believable in the context of the world, and really engaging. The battles in the Battle of Five Armies are so full of over-the-top heroics and impossibilities that they become less an exercise in story-telling and heroic fantasy and more of an exercise in braggadocio by everyone involved. Yes, I want to see my fantasy heroes do impossible things; I want to see victories against overwhelming odds; I want to know that these people are not normal, not like me, doing things I can’t do. I don’t want this experience to be transformed into marveling at the ingenuity of the movie’s creator’s rather than its characters.

Just as a young hostess’s style can be so gorgeous that it becomes a self-evident performance of beauty rather than beauty itself, so this movie has turned heroic fantasy into a performance of itself, rather than a performance for its fans.

And don’t get me mistaken, I am a fan. The Hobbit is not a particularly interesting or enjoyable book, and Peter Jackson had pretty thin gruel to work with in making this part of the epic; he also had to please a group of tantrum-prone true-believers with an immature and shallow approach to the work. Given how dark and grim the later Lord of the Rings movies turned, he also had to find a way to leaven the silly boys-own-adventure style of the main plot with some kind of nod to the growing shadows. By choosing to work in the unwritten parts of the original story – Gandalf’s exploration of Mirkwood and the battle with the necromancer, for example – I think he has made the story more engrossing and enjoyable. He has also managed to present us with a breathtaking and splendid vision of Middle Earth, carved out of New Zealand, that has been more or less consistent across six diverse movies, and has stuck very closely to the aesthetic vision of Tolkien’s main visual interpreters. He managed to lift the dwarves from their shallow representation in the book and Snow White-style triviality in popular culture into serious, adult figures without falling on the cheap Jewish or Scottish stereotypes that often get attached to them, and for this all Tolkien fans should be eternally grateful. The dwarves are excellent, and as dwarves should be – dour, hard working, tough, narrow-minded and loyal. They look like adults and adventurers, and unlike Gimli (or Dwain in this movie) they don’t get turned into comedy sideshows. The Hobbit would have been an utter disaster if it had been made by someone trying to be loyal to the original book and the needs of the fans, it would have been a single stupid movie involving 12 characterless technicolor idiots and a dude in a pointy hat, cocking up everything they do.

Furthermore, The Hobbit is a rare example of a movie that manages to make a dragon a central part of it without cocking it up monumentally, which every other movie except Dragonslayer and Reign of Fire has managed to do. Smaug is an evil, cunning, wily and deeply sinister monster of terrifying power, and as soon as he is let loose on Dale you can see why armies of dwarves would fall before one of these things. His supreme arrogance, coupled with his incredible power and complete disregard for mortals and their feeble efforts, is a joy to behold. This is how a dragon should be! But even here we see Jackson falling for the gorgeous: the simple tale of Smaug’s death gets padded out with an unnecessary piece of sentimentality and impossibility, and a spot of slightly out of place (but nonetheless enjoyable) humour. Nothing in this movie just jumps, or just climbs, or just dies. Not even Smaug.

Still, I didn’t sign up for the last instalment in this epic so I could see a handful of orcs get their arses kicked by some woodland sprites and a few technicolor stereotypes in a backwoods scrap. I signed up for a monumental battle between the noble forces of good and the deepest evil ever conceived, and that’s what I got – in spades. The Orc leaders and Uruk Hai champions were awesome, the dwarven and elven battle scenes were spectacular, the troll stormtroopers impressive and exciting (though like every other stormtrooper, remarkably easy to kill …), the desperation of the human defenders grim and hopeless. This is a two-plus hour rollercoaster of well-deserved death and slaughter, and though you will at times find yourself thinking “what were they thinking?” and marvelling more at the movie-makers’ ingenuity than the actual traits of the people on the screen, you’ll still love every minute of it.

But it is too gorgeous.

fn1: Remembering that in modern Japan the word “adult” is increasingly coming to mean a person over 30, and there is even a growing fashion trend for otona (大人) that is specifically aimed at offering classy but still pretty and sexy clothes to women aged in their 30s and 40s. This style is largely the opposite of gorgeous.

I have a dataset of about 40 million records covering rare events over a 30 year period, with about 600,000 events in total. The data are clustered in about 50 regions, and in the latter years of the file there are only about 4000 events a year (they increase in frequency in the early years). This means that in one year there may be only 80 events in any one region. I want to conduct a multi-level Poisson regression of the events, with about four or five categorical covariates plus year and a random effect for region. I’m doing this using GLLAMM in Stata on an Apple computer with 32Gb of RAM, 12 cores and Stata/MP optimized for all 12 cores (this is not a cheap setup!) The raw dataset takes about 16Gb but I can collapse it to a dataset of counts of events and populations at risk, which reduces it to (I think, from memory) about 170,000 records. I’m using a Poisson distribution, so essentially a loglinear model, but I should probably ideally use negative binomial for zero-inflated data – unfortunately GLLAMM doesn’t handle negative binomial data and I have read of problems with the xtnegbin procedure, so I just have to suck it up and use the Poisson family. I’m also not adjusting for serial dependence, because that would mean extra random effects and/or correlation structures and it would just get too nasty.

The problem here is that GLLAMM just won’t converge. If you set it running with relatively standard settings you can first run it with the NOEST command to get the coefficients, then feed them as starting values into a model with adaptive quadrature and 12 integration points, but it just won’t converge: after 3 or 4 days and 150 iterations (one estimation cycle takes about an hour) it still hasn’t converged, and the maximum likelihood estimate is not concave. The maximization process seems to be proceeding in some fashion, because every 10 iterations or so the likelihood decreases slightly, but it just won’t seem to stop. Interestingly you can’t set the tolerance in the estimation process in GLLAMM, so I can’t stop it when the MLE is decreasing by less than 0.01 (which it is doing now) but more than 0.00001.

This non-convergence is not a data issue – it works fine in a standard Poisson regression, there are no warnings about combinations of covariates with all zeros or all 1s, and this also seems to be the case when the data is divided up into regions (as best I can tell). I think the problem is just that the events are rare, there are a lot of dimensions over which the likelihood needs to change, and it’s just a very tough optimization problem. I have run into this problem with non-linear multi-level models before, and it appears to be a problem of big data with rare events and large numbers of regions. So what to do?

I have noticed in the past that estimation in GLLAMM is more likely to be successful if there are more integration points, which slow down the time to converge but improve stability. I’ve also noticed that the initial estimates can really kill the model, and also I’ve noticed that a big part of the estimation procedure is about getting standard errors, not estimates. Also, although you can’t control tolerance you can limit the number of iterations (a rough version of the same thing). Each iteration taking an hour, if one wants to get actual results it is helpful to run as few iterations as possible[1]. So today I tried a new method for getting convergence, which works in stages like this:

  • Start with the NOEST option to get initial coefficients for starting values
  • Feed these into a model with 1 integration point (Laplace Approximation) and 1 iteration
  • Feed the coefficients from this as starting values to a model with 2 integration points and 2 iterations
  • Keep running new models, slowly increasing integration points and iterations

If I did this a few times, I found that my models started converging after just two Newton-Raphson cycles. By the fifth model (with nip(12) and iterate(8)) the coefficients had all become stable to 4 decimal places, and the variances were largely fixed: all that remained was small changes in the variance of the random effect. At the fourth model some of the variances were out of whack, but the coefficients close to their final value. The fourth and fifth models converged on the second Newton-Raphson step. I set it running last night and it’s basically now fine-tuning, using a model with 24 integration points and a maximum of 32 iterations. That will be the final model, it’s probably going to be done by tomorrow morning.

Because this modeling process starts with the final coefficients from the previous model, it seems to bypass a lot of the convergence problems that arise from starting with a model that has coefficients very far from the final values and then waiting. Instead, you get rough coefficients halfway through the process and then restart. Since much of the challenge for the estimation process seems to be in calculating variances rather than coefficients, this saves you a lot of time waiting to get values. It seems to have shortcircuited a lot of convergence issues. I don’t know if it would work for every problem (GLLAMM seems to be a temperamental beast, and every time I use GLLAMM a new problem seems to rear its ugly head), but if you are having convergence problems and you are confident that they are not caused by bad data, then maybe give my method a try. And let me know if it works! (Or if it doesn’t!)

fn1: Actually this model process takes so long that there are some sensitivity analyses we just have to skip. There is one method we use in preparing the data that I would like to check through resampling and sensitivity analysis, but if every model is going to take 2 days, then you can’t even do a paltry 100-sample bootstrap and get a meaningful answer in half a year. Crazy!

Our World of Darkness campaign, that we began by accidentally exterminating a native American tribe from history, ended today when we accidentally reset history to a parallel world ruled by a Thousand Year Reich built on justice and honour.

In the process we went from a group of ordinary mortals struggling to understand why we were trapped in a pocket universe with a genocidal spirit, to generals of a supernatural host, leading armies of magical beasts in a war against heaven. My character, John Micksen, went from a washed-up, ageing hippy sitting alone in a bar, to Winter Knight wielding a sword out of legend (Excalibur!) and leading an army of the four courts of faerie.

We did great things while we wound our ugly and complex path to this brutal ending. In the last session alone we caused an angel to fall from heaven, destroyed an army, killed a god, had lucifer sacrifice himself to open a gate into the primal stuff of the universe, and reset the world so that an evil god never existed. As we wound our way across continents seeking the keys to the destruction of the God Machine we did great things, and saw great evil. From the first moment we opened a door in the basement of a psychiatric hospital, to find an infinite space filled with chains and cogs, we knew we were up against something relentless and evil, and our actions had to be bold, powerful and often cruel.

We started small, rescuing children from paedophiles who were smuggling them to an evil corporation; we burned the paedophiles alive and fought a fatal battle with the petty angel they served. We crossed into the land of the dead from an abandoned concentration camp to save the children’s’ souls from undead scientists who were performing hideous experiments, and while we were there we liberated lucifer himself from a thousand years of captivity. We fled destroyer angels who laid waste to whole city blocks trying to find us, hid in anarchist squats in East Berlin and vegan fascist terrorist lairs in Chicago. We dealt in pride and babies with the courts of faerie, so that we could betray a demon to a vampire, in service to a cause we didn’t yet understand. We did a deal with an ancient dragon and crept into hades to kidnap its ruler in trade for a faerie queen; that same god of death we later saved from a hideous experiment that used his essence to resurrect Jesus – and that same queen rode back into the faerie land of winter on the back of a Russian T34 tank, that our demon violinist drove. We carved a kingdom out of faerie, and bought a mansion in Ireland to connect to it using gold stolen from hell. For a while Cerberus itself (an intellectual and arrogant beast if ever there were one!) was our mansion’s guard dog, but of course we had to flee when angels came to destroy our mansion – a destruction John Micksen watched while speaking of lost love with an angel more terrible and beautiful than the sun. “The Winter Knight,” he said, after fleeing from her wrath, “Tires of this shit.”

We tired of many things, because we were constantly fleeing from great powers. We destroyed corporations digging around for the answers we sought – literally, leveled their offices and killed their officers. Anyone who helped us or even met us died – bodyguards, wives, children, allies, friends, political fellow-travelers, anyone who sheltered us, anyone who did business with us, and almost everyone who crossed us. They died in fire, the rubble of apartment blocks razed by enraged angels who sought after us, in the pits of hell or in the snowy wastes of faerie, they died chained to a steering wheel in a flaming gasoline stand or savaged by berserk werewolves on vast fields of battle. Some of them were pounded into red mist by the Winter Knight, some left to experience an eternity of frozen pain in the deepest darks of the wastes of faerie winter. Some were tortured by our enemies, or just disappeared into nowhere by ancient powers we had angered. For every one of our allies or friends who suffered, our anger grew and our list of retributions extended. We were not patient, or careful, but we did all we could to destroy those who crossed us.

We were no match for our foes. An implacable god without emotion, possessed of infinite patience, sought to change the world to suit its cold mechanical whims, and the angels that served it felt no mercy, fear or compassion. They slowly reworked the political landscape of the world to suit the mysterious machine passions of their master, turning America  into a fascist dystopian nightmare, laying waste to whole nations with plague and war, exterminating races and cultures with machine precision that no human could ever master. They sought to tip the balance in every dimension. For a short time the courts of faerie waged war against each other and a strange machine god, and all the seasons were thrown into chaos – until we intervened to restore peace and kidnap a mad faerie queen wed to a despicable machine. But for every victory our terrible foes became more ruthless and more wrathful, so that we were forced to flee, and flee again, always running and hiding.

Some of us died three times. Some of us were infected by the God Machine’s sinister viruses, rebooted, cleansed and returned to us unrecognizable. Some of us were cast down from our powers and left to rot and die, before we rose up again to take on new and greater roles. Some of us tried to strike out for freedom and failed. Some of us had to dig deep and fight hard to uncover the secrets of our past, and strike a path into the future. Some of us lost everything, rebuilt, and lost it all again. We reached our wits’ end, burned our patience, rampaged through our enemies’ lairs in rage and anger destroying everything in sight. We stole a sacred stone from Mecca, and books of gibberish from under the noses of angels that could destroy whole armies. We were epic, and constantly terrified.

All of this came down to a final battle on a dusty plane in the American mid-west, to find a gate that would change the past and the future. Our Demon Violinist opened the gate, while armies fought to end the world, and we reset everything so that all our enemies were extinguished. We triumphed! And the world was restored to an order of peace and justice that could never exist in any boring, cold reality.

Truly, this was a glorious campaign of great deeds, terrifying struggle, mysteries unraveled and paedophiles flame-grilled. It was exhilarating, terrifying, deeply absorbing, sometimes incredibly frustrating, confusing and exhausting. I don’t think it had anything in common with a normal World of Darkness campaign, and the Demon book on which it was all based only arrived for the last session. But it was amazing in its scope, its power and its content. And it ended in glory. It was role-playing at its finest!

I have been reading Tolkien, Race and Cultural History: From Fairies to Hobbits, by Dimitra Fimi, in an attempt to get a broader insight into some of the background of Tolkien’s world-building and the ideas underlying it, and it has been presenting some interesting and I think new ideas about how Tolkien’s world developed, some of the reasons for some of the ideas in the world, and some of the challenges he faced in putting it all together. One interesting challenge that Fimi describes in some detail in the book, with perhaps more emphasis than I think it deserves, is the importance of the shape of the world to Tolkien’s thinking, and the extent to which the world’s physical structure troubled Tolkien. Reading the Silmarillion and the Lord of the Rings, it never occurred to me that this mattered, but apparently it did. The world changed during its construction from a flat earth to a round world, and Tolkien appears to have been uncomfortable with the change.

Dr. Fimi gives a rough creation timeline to Tolkien’s ideas, in which the stories of Middle Earth played a role as a kind of reimagining of an ancient history of England, which as it solidifies over time becomes harder and harder to reconcile with actual England. By the time of writing the Lord of the Rings, the fall of Numenor and the associated flood have become a kind of cataclysm that delineates a sense of mythical history from a more concrete prehistory of the actual world. In this interpretation of his creative process, western Middle Earth’s shape is not accidental – it is representative of our modern world, in some pre-historic sense. For Tolkien, the cataclysm that destroyed Numenor served to separate a mythic time of fairies from a more prosaic era more closely connected with modern history (though still preceding it and unknown to its modern observers).

One strange consequence of the importance of switching from a pre-historic mythic world to one closer to our own is the need to switch from a pre-historic physics to a modern physics, and somehow in all of this the world went from being flat to being a normal sphere, with heavens and stars. There are apparently maps and notes which explicitly show this transformation, and Tolkien himself wrote of it in a letter to a friend:

A transition from a flat world (or at least an [Greek word] with borders all about it) to a globe: an inevitable transition, I suppose, to a modern “myth-maker” with a mind subjected to the same “appearances” as ancient men, and partly fed on their myths, but taught that the Earth was round from the earliest years. So deep was the impression made by “astronomy” on me that I do not think I could deal with or imaginatively conceive a flat world, though a world of static Earth with a Sun going round it seems easier (to fancy if not to reason)

Here Tolkien expresses directly the difficulty he has in writing a plausible world based on genuinely mythical precepts – he needs to ground his magical world in some basic reality, even though he puts the science of that reality in scare-quotes and wishes to believe that he has a similar sense to the ancients. Fimi links this to the placement of the stories in the timeline of the real earth; early versions of his stories (in the Book of Lost Tales) are imagined as only being a few hundred years in the past but as he thinks more about the structure and cosmology of his world the timeline changes, so that the same stories are suddenly before the last Ice Age.

Tolkien’s letters on this topic are notable for the use of many scare-quotes: in another letter he puts the words “spherical” and “space” in scare-quotes. I don’t think this is an indication that he sees the science of heliocentrism or astronomy as incorrect, but indicate that when he writes about his stories, Tolkien places himself (at least partially) inside the framework of his world. Fimi reports from an interview in 1963 in which the interviewer (Anthony Curtis) felt that Tolkien spoke about his own world as if it were a true and real place – he had been building it so long, he no longer spoke as if he were not in it. I think this is the provenance of the scare quotes in the above passage: for Tolkien astronomy is real, but when he speaks of cosmology from within the perspective of his imagined world, astronomy becomes “astronomy” and the structure of the earth becomes a matter of conjecture: once it was flat, and lit by trees, but then there was a cataclysm and now it is round. What of it?

Perhaps this is part of the source of the power of Tolkien’s creation. He placed himself inside his myth as if it were real, and tried to create it as if there were nothing outside of the knowledge contained in that world. Modern myth-makers see a world as an interesting prop for a story – an interesting setting is essential to fantasy, after all, and every author needs to make a setting – but Tolkien saw the stories as useful ways of explaining the mythical world that he had created, and lived inside when he was writing those stories. This world that he created was originally tied quite closely to his  idealistic political goals, conceived of both personally (the creation of a “mythology for England”) and in conjunction with the political goals of the society he and his friends created and dominated (the Tea Club/Barrovian Society), and part of these goals was the promulgation of certain ideas about how England was and should be; so it was inevitable that the stories would take on uses other than just the expression of Tolkien’s own mythical vision, and it is almost certainly the case that his mythical vision was influenced by and not inseparable from his political vision (which did not seem to include any racial elements, incidentally). But it appears that as time passed (and the Great War destroyed his and his friends’ idealism) these original political visions faded from his mythmaking, and it became a more personal aesthetic quest (for example, obviously Catholic language disappeared from his dictionaries of Quenya). However, no matter how deeply involved in this quest he became, it appears that he was still tied to a basic need to keep his stories accessible to a broader readership. Making his earth round appears to have been an explicit part of this process.

In the development of Tolkien’s myths we see his transition from boy to man, idealist to cynic, and embarrassed philologist to accomplished story-teller. It also appears that we see his journey from (mythical) flat-earther to reluctant heliocentrist. We will see though that there is one element of his world that does not change across all this time: the racial heirarchies of his world. I will come back to this in a later post on Fimi’s work, which I haven’t yet finished but am finding a very engaging and insightful perspective on Tolkien and his legacy. I strongly recommend it to those who are interested in the details of the development of Tolkien’s world, and I think I can say that it serves only to deepen the respect with which one views Tolkien’s creative achievements, and will not leave one disappointed with Tolkien or his legacy.

Eerily romantic

Eerily romantic

I have recently been exploring the shadowy and terrifying world of the Neath, in a fascinating and quite engaging game called Sunless Sea. This game is set in a location called Fallen London, an scattering of island archipelagos on a vast underground sea, which was formed at the conclusion of a previous game from the same company, Fallen London. This sunless world is an ocean in a deep cavern, full of horrors and strange stories. The game is viewed from above, essentially on a map, and you play the captain of a steamship who is plying the Neath (the name of the underground ocean) trying to become famous or rich or both. Based in the town of London, you travel between islands trading, picking up stories, fighting pirates, and doing the bidding of mysterious powers. Travel across the darkened seas is fraught with risks, however: in addition to the risk of running out of food and fuel and having to eat your crew, there are also pirates, monsters, and the ever-present growing fear of the darkness. Journeys have to be carefully spaced to ensure you can return to London before the fear mounts and your crew mutiny on you, or the nightmares consume you. There are also mysteries to unravel, and stories involving different organizations and kingdoms.

Strange shops in a strange world

Strange shops in a strange world

The game is viewed from above and there are no animations for battles or encounters, just text-based interaction as shown in the picture above. However, despite the lack of animations the graphics are very stylish and engaging, and very carefully build the sense of terror and weirdness that pervades the game. Drawn a little like a comic, but with a grim wash, and with a writing style that is a mixture of dark humour, Victorian prose, and elegant horror, the narrative really gets you involved in the world. It’s also quite challenging, and if you play it the way it is intended, death will be a common event. As the game progresses and the stakes get higher, the struggle with terror also becomes quite consuming, as you try to balance your need to travel the dark reaches of the farthest-flung islands with the compulsion to keep your terror from overwhelming you.

The game has a few flaws, however. First of all it has quite a sedate pace, so if you’re the kind of gamer who needs edge-of-the-seat energetic game play, it will probably bore you. Also, sometimes the mission details are hard to access, and the game doesn’t tell you when you have completed a task (in some cases), so you can feel lost at sea (literally!) when in fact you have met the conditions of a quest. It is also difficult to piece everything together into a coherent story, so sometimes it feels like the game just intends for you to grind, grind, grind – I still don’t have a sense of a unifying story or theme to the game, and I’m not sure if it will hold my attention if it does not have a theme. It is also quite hard to make money, though I have begun too, and the rules aren’t very deeply explained, so you spend a lot of time making pointless mistakes at first, and I suspect some players have given up early on because of this. However, once you’ve died a few times and googled a few things, the peculiarities of the world and its systems will begin to make sense.

With that in mind, I thought I’d produce here a list of tips for how to play, based on what I have learnt so far.

  • Always have good stocks of fuel: at first you will only be making small amounts of money, and may find it difficult to purchase things like weaponry; don’t give in to the temptation to spend your cash on a bigger gun when you don’t have much spare, because if you don’t have much fuel, you will find yourself unable to travel to make more money. Always retain enough fuel to at least be able to do a tomb-colonist run, so you can replenish fuel on the return. And always ensure you have enough fuel for the return journey when you head away from London – it is expensive everywhere else (except Palmerston) and if you run out on the high seas you are in big, big trouble
  • Keep your terror down: It is extremely hard to get your terror down from high levels, and/or expensive, so keep your terror down. The main way to do this is to sail through lighted areas, or close to shore. Sure, the pirate raiding requires that you sometimes sail away from the buoys, but you need to make sure that when you travel you stay in the light as much as possible. Especially on long missions, or missions which are going to themselves raise your terror (and many do!) you don’t need to also be burdened with terror built up through frivolous course-tracking
  • Take the blind bruiser’s gift: the only consequence is that later he will ask you to deliver some souls to a far-away place, and you will make your first big cash of the game when you do that
  • Build up admiralty’s favour: it gets you more lucrative and interesting missions, and access to cheaper repairs
  • Keep visiting Hunter’s Keep: Hunter’s Keep is very close to London, and spending time with the sisters will get your terror down. It may seem boring to drop in on a place where you keep having the same conversations, but that soon changes. Hunter’s keep is one of the first stories to reach its resolution, and if you play your cards right you can emerge from the ruins of the story a lot wealthier than you were at the start
  • Watch your nightmares: When you return to London with terror>50 points it automatically resets to 50 (which, btw, is not good!) but your “nightmare strength” increases. Nightmares on the high seas can lead to trouble, including higher terror and ultimately mutiny. It is extremely hard to get your nightmare strength down, but there is one surefire way: travel to the Chapel of Lights north-east-east of London, and visit the well; you can make a sacrifice here and though you incur a wound, you lose nightmares. Do this twice and you can get rid of almost all your nightmares (though having 2 wounds is very risky)
  • Go bat-hunting: bats are easy to kill, and if you throw their corpses overboard you lose a few points of terror. This is the only relatively reliable way I have found to get terror down a lot, though it is not cheap. Basically if you hang around a buoy near Venderbright (or the island of Tanah-Chook, near Venderbright) you will be regularly attacked by bats, but will gain no terror from your location. If you kill 10 or 20 swarms of bats you will get your terror down by 15-30 points, which is really useful. It will cost you in fuel and supplies, though you can recoup the supplies from bat-meat, so make sure you have spare money and fuel before you do this. I think terror affects your abilities, so it’s good to keep it low
  • Torpedos are useful: keep a few in reserve. I was ambushed by a Lifeberg on my way back from the Avid Horizon, and in a moment of desperation I unleashed some, that did it a lot of damage. I took some hull damage but it kept me alive. They cost a lot, but they can be fired early in the battle and do a lot of damage. Combat in Sunless Sea works by increasing illumination until you can see your enemy enough to shoot them, but for the bigger enemies (like Clay Pirates and Lifebergs) you need illumination 100 to get in a really good salvo against them. Getting to illumination 100 without getting sunk is extremely difficult, but torpedos do damage similar to a powerful gun salvo at illumination 50, so if you get ambushed by something much tougher than you they can be a handy way to get out of trouble
  • Keep visiting the old dude in Venderbright: At some point in Venderbright you will get the option to talk to the head of the tomb-colonists, who gives you a mission to explore and find the colours from 8 or so pages of a book. I found two of these colours but the game didn’t tell me I had them, and it took me ages to visit the old dude again. When I did I got an item worth 500 echoes as a reward. So my advice is, once this mission has been unlocked, visit the guy regularly because you can’t be sure you have achieved one of the goals, and the money is worth it. A lot of people say that trips to Venderbright aren’t worth it, but I don’t agree. Not only can you make a bit of money selling news and colonists, but when you explore you can pick up quite valuable artifacts, and as a stop on the way to places further afield, it’s a good way to make a bit of money and get your terror down a bit. Plus some of the story options (the Bandaged Poissonier, Jonah’s revenge, the old dude with the book) can be valuable for you later. So I recommend continuing to visit here.
  • Always go coral-picking at Port Cecil: a single scintillack is worth 70 echoes.
  • Always collect port reports: they can fund your trips, and the admiralty will pay for them no matter how many times you give them
  • Grab stray chances: someone left a coffin on the docks for me once. I took it, and it opened up a whole new island for me. Take any chance you are given!
  • Avoid fights with bigger ships: sure, you can defeat the clay pirates, but unless your mirrors stat is very high you will take hull damage, which will cost about 50 echoes to fix, and all you will get in exchange is a few supplies or a bolt of parabola-silk or something – the maximum profit will be 20 echoes. You can make 20 echoes from a steam pinnace with zero risk. Avoid them.
  • Use the alt-f4 cheat: I’m playing on a mac, I don’t know how to do alt-f4 but I can still do control-command-escape or whatever, and kill the game when I die. Once you are a long way into the game, dying is not such a great idea, so be ready to do this – when you die, kill the game or load before you save, so that you can restart from your last port of call. Otherwise, you have a long upward climb ahead of you …

I think that’s it. I’m slowly gathering stories and trying to find out where the game goes, and I’m not sure if I will finish it (or if it can be “finished”, per se) but I’m enjoying the experience of this new world. I think it would also make a disturbing and evocative role-playing world. If you’re into cthulhu-esque horror and don’t need fancy graphics to make your games fun, I strongly suggest this game. It can be a bit irritating at first, but once you get up and running it’s a really rich and pleasant experience!

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