The future is a shoe being thrown at a human face – forever!

Ahhh, the curse of a title that you like too much to throw away, but not enough to write a relevant post about. Lengthy, multiply footnoted philosophical meanderings, below the fold.

Update: Unaccountably, I forgot to thank “Robotslave” for massive amounts of help provided in this research. Sorry and thanks!

This was meant to be a title for a post about the utterly fallacious but surprisingly common wishful-thinking belief on the part of wowsers, prigs and other good-government types that “seeing someone throwing a shoe (or custard pie or whatever) at a political figure makes most people think worse of the thrower and his political cause, and sympathetic toward the target”. This simply isn’t true[1]. The instinct to support the underdog isn’t there in nature and one has to arrive at a very high level of civilisation before it becomes a firmly established reaction. And at the sight of airborne humiliation flying toward a political foe, all those centures of evolution drip away, and one’s left just simply pointing and chortling. It’s perhaps not the noblest expression of the human mind, but frankly, any political movement which doesn’t regard this as funny, well, it’s the Emma Goldman moment as far as I’m concerned.

God, I’m never going to get tired of that. Anyway, there’s clearly a Laffer Curve here; on the one hand, if there were no pieings of politicians, the world would be a sad and sorry place, but I’m guessing that if people like Friedman were pied every time they went out, they’d never go out, and we’d still have to read their columns without seeing them occasionally pied. I suspect that we’re not actually on the rightward slope of the Laffer Curve[3] yet and that the world could stand having a few more of these incidents rather than less, but that’s a matter of personal taste.

On the other hand, I never really finished that post because of course, although seeing Bush get shoed was a laugh, it’s a nervous sort of laugh for anyone who is worried about the possibility of President Obama being assassinated, which I know that a lot of people are. And statistically, they’re right to be worried. Roughly 10% of all US Presidents ever elected have been assassinated (4 out of 43), which is roughly as high a death rate as street drug dealers[4]

Which brings me to the actual topic of the post; a link to a post on my other blog where, in comments, we have been working out job-related mortality rates for a variety of professions. To date, we have:

President of the USA: Five job related deaths since 1789 (assassinations of Lincoln, Garfield, McKinley, Kennedy, plus death of William Henry Harrison from job-related stress illness). That’s 0.022831 job related fatalities per year, in a job that can have only one person doing it at a time. Converting this to more normal units of occupational fatality for comparison with other jobs, that’s 2283 deaths per 100,000 President/years. This compares to 117 deaths per 100k worker/years for timber-cutters, the most dangerous standard occupational category.
Soldier, US Army, Iraq war: Up to March 2006, 392 fatalities per 100k soldier years spent in the Iraqi theatre. But of course, soldiers don’t spend all their time in battle zones, so based on reasonable estimates of fatalities outside combat zones, something around 80 would be more reasonable, more or less comparable to fishermen (anecdotally, the in-Iraq death rate would be comparable to Pacific Northwest crab fishermen, the single most dangerous occupation anyone could find).

Soldier, Iraqi Army, Iraq war: On the other hand, the Iraqi Army doesn’t get rotated out of Iraq, and thus by reasonably sourced estimates sees a job-related fatality rate of close to 800/100kwy.

Prime Minister, United Kingdom: It now gets rather controversial. Spencer Perceval was assassinated (definitely work-related) and Lord Palmerston died of a chill caught while on an official trip to Russia. Henry Pelham’s death in office was regarded at the time to have been related to the stress of his job, but how do we code the deaths of Pitt the Younger, and Lord Wilmington? How about George Canning, whose health was in rapid decline by his second appointment as PM? What about Thomas Cromwell, whose execution was clearly a job-related fatality, but who wasn’t head of government? On reflection, I would count three fatalities since 1688, for a job related fatality rate of 937.5/100k Pmy, but I can see how rates as high as twice that could be supported.

Pope: Even more controversial, here. By definition, all Popes die in office and it is very hard to get any data about Popes having died from job-related illnesses, so we had to scale back the project to estimate the rate of violent job related deaths of Popes. The consensus of historians has seven popes definitely having been murdered, which would give a job-related mortality rate of 476/100k Pope years since Gregory the Great in 540 AD. However …

There are a further ten Popes listed by Wikipedia as possibly having been murdered (this number includes John Paul I, so it apparently doesn’t take much in the way of real evidence to get on this list). Adding them in would boost the Papal fatality rate to 1158/100kPy. And furthermore …

The first 25 Popes were martyred. This is surely the very definition of a job related death, and I don’t really see much case for excluding them as an outlier[6] – in any long run of data, you’re bound to get a couple of periods under which Europe was dominated by a vehemently anti-Christian empire[7]. In order to take this additional data into account, we have to extend the window back to St Peter and 33AD[8], but you still get 2126 job related deaths/100kPy.

Monarch, England/United Kingdom. By the time we got onto these, I was getting a lot better at devising coding schemes, and so stipulated that for monarchs, I would count assassination (with a broad criterion for including rumoured murders), execution, death in battle, or death from illness or accident while travelling with an army in the field as job-related fatalities, and would require the record to be of a serving monarch in order to count (deaths post-abdication[9] not counting). On this basis, since 1066, there have been two deaths in battle (Harold Godwinson, Richard III), four murders (Edward II, Henry IV, Henry VI, Edward V), two executions (Jane Grey, Charles I) and one death during random pillaging on the way back from a Crusade (Richard I). That would make 955 job related deaths/100k king-years. But …

Starting the clock at 1066 seems very arbitrary. Although before Harold Godwinson there wasn’t really a king who controlled a territory recognisable as modern England, are we really going to say that Alfred the Great wasn’t King of England? A more logical place to start IMO would be Egbert of Wessex in 802, which means we have to add Edmund the Magnificent and Saint Edward the Martyr to the tally, but brings the overall death rate down to 912/100kky.

Monarch, France: By this time, very easy – having set up the coding for English monarchs, I knew exactly what to do with difficult cases like Napoleon I (out; would have been in on the basis of the inclusive criterion for rumoured murder, but abdicated and thus was not a monarch at the time of death). The only tricky bit was in adding up the denominator; since the first Carolingian monarch in 843, there have been 1010 years and 100 days of French monarchy, during which there were 9 work-related fatalities. That’s only 890 work related deaths/kky, which is doubly interesting as it is lower than the English figure, even though the French data doesn’t have the benefit of the massive improvements in monarchical health and safety which have been seen in the last couple of hundred years.

Active Party Member, Hezbollah. Data nearly impossible to get, but including suicide bombers[10] and dependent on an estimate of the size of Hezbollah, it’s as much as 1,000 to 2,000 per 100kHy. In any case, it’s very difficult to get any estimate under which being a Hezbollah member is as dangerous as being President.

So, recapitulating and tabulating, worst to safest:

President, USA – 2283
Pope – 2126
Hezbollah, active member – 1000-2000
Prime Minister, UK – 937
Monarch, England/UK – 912
Monarch, France – 890
Soldier, Iraqi Army – 800
Soldier, US Army (while in Iraq, March 2003-March 2006) – 392
Fisherman, Pacific Northwest crab fishing – c400
Timber-cutter – 117
Fisherman, overall – 85
Soldier, US Army – c80

Not necessarily what you’d have expected to see, is it? So anyway, where are we going with this?

First, a plug for The Politics of Large Numbers by Alain Desrosière, translated by Camille Naish. Although the translation is rather unfortunately accurate in rendering dry, pedantic officialese French into dry and pedantic English, it’s a great book (thanks to Laleh and Colin Danby in comments to this thread for encouraging me to persist with it). As you can see above, in order to get to my table of dangerous jobs, I had to make a lot of very arguable coding decisions which had a material effect on the relative positions (as far as I can see, no matter how I cut the numbers, I couldn’t have got the political and spiritual leaders down to the level of Pacific Northwest crab fishermen, but by making different judgement calls, I could certainly have made “Pope” look a lot safer). This is the nuts and bolts of the creation of official statistics and Desrosière’s book is very good on the history of their development and the various stages at which key decisions were made, almost always for political reasons (Germany, France and the UK had very different tracks for the development of their official statistics which reflected the realities of their administration in the 19th century).

Even something as seemingly straightforward as the space on hospital forms for “cause of death” is a minefield. Do you classify medical deaths by listing the organ which failed, or the cause of its failure (infection, trauma, etc)? The question always comes back to – what are you trying to achieve with these statistics? “The Politics of Large Numbers” is an excellent book for anyone who is ever tempted to think Bruno Latour’s work never had any really useful applications.

Second, though, there’s a philosophical issue here. More thoughtful readers will have looked through these mortality table calculations with a growing feeling of unease. The first instinct is to say that the sample sizes are too small for a lot of them, and that therefore the confidence intervals are too wide to make any meaningful comparisons. In my view, though, while that’s certainly evidence of good habits of thought, the actual numbers are large enough to be pretty sure that you can make at least some statements with decent confidence. In particular, it really does look to me as if the risk of assassination faced by a President of the USA is a lot higher than the risk of battlefield death faced by an American soldier. It’s true that the sample size is small nd the confidence interval is wide, but qualitatively, the facts are that modern military casualties are low compared to history[11].

I think the real source of philosophical unease at comparing death rates between heads of state and timber cutters as if it were an apples-to-apples basis[12] is not the small sample in and of itself, but the difference between a historical and a statistical mode of thinking. We’re tempted to think of the deaths of Popes, Presidents and kings as unique historical events, each with an individual set of causes. We know about them through their individual details, and in many cases we speculate and investigate to get a fuller picture of how they came about, whether we’re looking at the minutiae of the Texas Book Depository, or the grand sweep of the Hundred Years’ War.

The occupational deaths of fishermen and lumberjacks, on the other hand, for the most part appear to us mediated through lists of statistics[13], as risks which are part of the job. And in these occupations particularly, because the main sources of risk are such things as the pattern of storms and the direction of a falling tree, it’s even easier to fall into thinking of them in the whole, as stochastic processes, with the individual outcomes as the natural results of a stable distribution.

But on the other hand, of course, ordinary industrial fatalities (including those of timber cutters and fisher men) are unique historical events too, with their own individual causes. And these causes are both proximate and world-historical too; the families of many fishermen who died at sea are entirely aware of the way in which the European Single Market contributed to their bereavement. Similarly, there are statistical regularities even in the assassinations of kings and Popes.

The point is (and it’s a point that’s entirely relevant to a number of our present concerns)[14] that both these points of view need to be held at once[16]. As we head into a New Year which is likely to present uncommon challenges to all of us, bear in mind that nearly everything and everyone in the world is both unique unto themselves, and an example of any number of more general classes. Happy Christmas.

[1] Consider, for example, Bernard-Henri Levy. How many of us know anything about his philosophy in any real depth? How many of us, on the other hand, just know him as the repeated victim of a series of pieings from Noel Godin, and presume “hmmm, BH Levy must be a real pompous twat in order to provoke so many pieings”? In my case, I have read a bit of B-H L, and what I read pretty much confirmed my original opinion based on the pieings. Score one point for Malcom “Blink” Gladwell[2].

[2] Who surely must be well past his pie-by date?

[3] Obviously the equivalent to the tax rate here would be the strength and severity of the security response to pieings, in which context I suppose a few words on the vicious beating of Muntazer al-Zaidi are in order. Like any instance of police brutality, this is of course unacceptable. There is certainly a case to be made that given the high assassination risk faced by US Presidents, there is a public interest in dissuading pieings or shoeings of them, because having loads of “false positives” interferes with their security. But really; was there an epidemic of President-pieings beforehand? I would have thought that the normal legal risks and more or less certainty of getting caught would be deterrent enough in the general case.

[4] The death rate of the Black Gangster Disciple Nation gang studied by Sudhir Venkatesh was much higher – it went up to 25% for a four year period. However, this is generally recognised to have been anomalously high and probably reflects the peak of the crack epidemic rather than a “normal”[5] rate.

[5] What constitutes a “normal” death rate? What’s a “normal” environment for crack gangs, a population who are pretty much by definition abnormal? These and other highly politicised questions of statistics addressed further on down the post.

[6] I suspect that David Kane may take the fact that I have discussed the status of outliers here as being some sort of indication that he is not banned, or that I am interested in once more entering into discussion with him about the Lancet studies of Iraq and the correct treatment of Fallujah. Neither is the case.

[7] You might think that the experience of the Early Christians isn’t terribly relevant to someone considering a career as a Pope today but come on; this really is Mediocristan type of thinking! Lots of people didn’t think that there could be a sustained fall in nominal housing prices either!

[8] Using BCE notation seems something of an affectation in context.

[9] This stipulation also avoids having to consider what to do with Oliver Cromwell in the data for “British Head of State”; Cromwell was executed by beheading, but this wasn’t his cause of death.

[10] The death rate for suicide bombers per mission is obviously high, but less than 100%, as it is surprisingly common for Israeli police to successfully intercept them and take them alive.

[11] While modern medical advances will have helped Presidents to survive assassination attempts better than they have in the past (Garfield and McKinley both died at least partly because of the inability of their doctors to find the bullet), I suspect that they have helped troops in the field even more. Presidential security protection has also improved, and it’s true that in the 107 years since the Secret Service was given the job, the death rate has been only 934/kPy, but this is still twice as high as the estimate for in-theatre troops.

[12] Which is as good an opportunity as any to make my periodic plea about “comparing apples with oranges”. Apples and oranges are really very similar things indeed. If I’ve got three apples and you’ve got two oranges, who out of us has got the most fruit? The answer is “it’s me”, isn’t it, not “who can say, you can’t compare apples with oranges”. They’re roughly the same size, roughly the same calorific value and roughly the same price. You can compare apples to oranges, in as much as you can make comparisons at all. Also, the darkest hour is not just before dawn.

[13] Stalin underestimated statisticians on this one; as few as 454 deaths (the number of fishermen who died between 1976 and 1995 according to the files of the Registrar General for Shipping and Seamen) can be a statistic.

[14] I keep hoping to write a proper review of Taleb’s Fooled by Randomness and The Black Swan but realistically my record is not good on delivering on these promises, so I’ll just state the kernel of my disagreement with him here; Taleb rightly castigates people who simply rely on the statistical mode of thinking, but a) his criticism is more often of their use of particular kinds of statistical model rather than of the monoculture of statistical reasoning per se[15], and b) he regularly goes over the edge into claiming that one can or should throw away the whole statistical methodology, which is just as daft as relying on it entirely.

[15] And because I love to repeat a joke, I’ll repeat one of my favourite remarks on quantitative finance – the occasional necessity to remind quant modellers that the Great Depression did actually happen; it wasn’t just a particularly inaccurate observation of the underlying mean return on equities.

[16] Zizek, in The Parallax View makes a similar point and argues further than the nearest we have to an “objective” truth lies in the very act of switching between them, but everyone round here has conniptions when I mention Zizek so I’ll pursue that line no further for the sake of comity.

[17] And because I have more sense than to end on a Zizek footnote, I’ll plug my next big holiday read, “Beyond Human Error“, a book about safety science which seems to tackle the question of integrating the causal/historic and statistical modes of reasoning in a more systematic way.