blarg?

August 7, 2019

Ten More Simple Rules

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The Public Library of Science‘s Ten Simple Rules series can be fun reading; they’re introductory papers intended to provide novices or non-domain-experts with a set of quick, evidence-based guidelines for dealing with common problems in and around various fields, and it’s become a pretty popular, accessible format as far as scientific publication goes.

Topic-wise, they’re all over the place: protecting research integrity, creating a data-management plan and taking advantage of Github are right there next to developing good reading habits, organizing an unconference or drawing a scientific comic, and lots of them are kind of great.

I recently had the good fortune to be co-author on one of them that’s right in my wheelhouse and has recently been accepted for publication: Ten Simple Rules for Helping Newcomers Become Contributors to Open Projects. They are, as promised, simple:

  1. Be welcoming.
  2. Help potential contributors evaluate if the project is a good fit.
  3. Make governance explicit.
  4. Keep knowledge up to date and findable.
  5. Have and enforce a code of conduct.
  6. Develop forms of legitimate peripheral participation.
  7. Make it easy for newcomers to get started.
  8. Use opportunities for in-person interaction – with care.
  9. Acknowledge all contributions, and
  10. Follow up on both success and failure.

You should read the whole thing, of course; what we’re proposing are evidence-based practices, and the details matter, but the citations are all there. It’s been a privilege to have been a small part of it, and to have done the work that’s put me in the position to contribute.

March 27, 2019

Defined By Prosodic And Morphological Properties

Filed under: academia,academic,awesome,interfaces,lunacy,science — mhoye @ 5:09 pm

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I am fully invested in these critical advances in memetic linguistics research:

[…] In this paper, we go beyond the aforementioned prosodic restrictions on novel morphology, and discuss gradient segmental preferences. We use morphological compounding to probe English speakers’ intuitions about the phonological goodness of long-distance vowel and consonant identity, or complete harmony. While compounding is a central mechanism for word-building in English, its phonology does not impose categorical vowel or consonant agreement patterns, even though such patterns are attested cross-linguistically. The compound type under investigation is a class of insult we refer to as shitgibbons, taking their name from the most prominent such insult which recently appeared in popular online media (§2). We report the results of three online surveys in which speakers rated novel shitgibbons, which did or did not instantiate long-distance harmonies (§3). With the ratings data established, we follow two lines of inquiry to consider their source: first, we compare shitgibbon harmony preferences with the frequency of segmental harmony in English compounds more generally, and conclude that the lexicon displays both vowel and consonant harmony (§4); second, we attribute the lack of productive consonant harmony in shitgibbons to the attested cross-linguistic harmonies, which we implement as a locality bias in MaxEnt grammar (§5).

You had me at “diddly-infixation”.

May 1, 2017

Wooden Shoes As A Service

Filed under: academia,digital,doom,future,interfaces,vendetta — mhoye @ 10:57 pm

P5012703

In international trade, the practice of selling state-subsidized goods far below cost – often as a way of crushing local producers of competing goods – is called “dumping”:

Under the Tariff Act of 1930, U.S. industries may petition the government for relief from imports that are sold in the United States at less than fair value (“dumped”) or which benefit from subsidies provided through foreign government programs. Under the law, the U.S. Department of Commerce determines whether the dumping or subsidizing exists and, if so, the margin of dumping or amount of the subsidy; the USITC determines whether there is material injury or threat of material injury to the domestic industry by reason of the dumped or subsidized imports.

To my knowledge there’s not much out there as far as comparable prohibitions around services. Until recently, I think, the idea wouldn’t have made much sense. How do you “dump” services? The idea was kind of nonsensical; you couldn’t, particularly not at any kind of scale.

If you put your black hat on for a minute, though, and think of commerce and trade agreements as extensions of state policy: another way to put that might be, how do you subject a services-based economy to the same risks that dumping poses to a goods-based economy?

Unfortunately, I think software has given us a pretty good answer to that: you dig into deep pockets and fund aggressively growing, otherwise-unsustainable service companies.

Now a new analysis of Uber’s financial documents suggests that ride subsidies cost the company $2 billion in 2015. On average, the analysis suggests, Uber passengers paid only 41% of the cost of their trips for the fiscal year ended in September 2015.

In other words: given enough subsidy, a software startup can become an attack vector on a services-based economy. A growing gig economy is a sign of extreme economic vulnerability being actively exploited.

I don’t know what to do about it, but I think this is new. Certainly the Canadian Special Import Measures Act only mentions services as a way to subsidize the offending company, not as the thing being sold, and all the recent petitions I can find in Canada and the U.S. both involve actual stuff, nothing delivered or mediated by software. At the very least, this is an interesting, quasi-guerilla way to weaponize money in trans-national economic conflicts.

For industries not yet established, the USITC may also be asked to determine whether the establishment of an industry is being materially retarded by reason of the dumped or subsidized imports.

I have a theory that the reason we’re not calling this out an as act of trade war – the reason we can’t see it at all, as far as I can tell – is that the people worst affected are individuals, not corporations. The people losing out are individuals, working on their own, who have no way to petition the state for redress at that scale, when the harm done in aggregate is functionally invisible without a top-down view of the field.

It’d be easy to make this sound isolationist and xenophobic, and that’s not what I intend – I like cool things and meeting people from other places, and international trade seems like the way the world gets to have that. But we know to put a stop to that when trade policies turn into weapons by another name. And I don’t understand down here at street level if there’s much of a difference between “foreign subsidies artificially undercut price of steel ingots” and “foreign subsidies artificially undercut price of cab rides”.

July 24, 2015

Hostage Situation

(This is an edited version of a rant that started life on Twitter. I may add some links later.)

Can we talk for a few minutes about the weird academic-integrity hostage situation going on in CS research right now?

We share a lot of data here at Mozilla. As much as we can – never PII, not active security bugs, but anyone can clone our repos or get a bugzilla account, follow our design and policy discussions, even watch people design and code live. We default to open, and close up only selectively and deliberately. And as part of my job, I have the enormous good fortune to periodically go to conferences where people have done research, sometimes their entire thesis, based on our data.

Yay, right?

Some of the papers I’ve seen promise results that would be huge for us. Predicting flaws in a patch prereview. Reducing testing overhead 80+% with a four-nines promise of no regressions and no loss of quality.

I’m excitable, I get that, but OMFG some of those numbers. 80 percent reductions of testing overhead! Let’s put aside the fact that we spend a gajillion dollars on the physical infrastructure itself, let’s only count our engineers’ and contributors’ time and happiness here. Even if you’re overoptimistic by a factor of five and it’s only a 20% savings we’d hire you tomorrow to build that for us. You can have a plane ticket to wherever you want to work and the best hardware money can buy and real engineering support to deploy something you’ve already mostly built and proven. You want a Mozilla shirt? We can get you that shirt! You like stickers? We have stickers! I’ll get you ALL THE FUCKING STICKERS JUST SHOW ME THE CODE.

I did mention that I’m excitable, I think.

But that’s all I ask. I go to these conferences and basically beg, please, actually show me the tools you’re using to get that result. Your result is amazing. Show me the code and the data.

But that never happens. The people I talk to say I don’t, I can’t, I’m not sure, but, if…

Because there’s all these strange incentives to hold that data and code hostage. You’re thinking, maybe I don’t need to hire you if you publish that code. If you don’t publish your code and data and I don’t have time to reverse-engineer six years of a smart kid’s life, I need to hire you for sure, right? And maybe you’re not proud of the code, maybe you know for sure that it’s ugly and awful and hacks piled up over hacks, maybe it’s just a big mess of shell scripts on your lab account. I get that, believe me; the day I write a piece of code I’m proud of before it ships will be a pretty good day.

But I have to see something. Because from our perspective, making a claim about software that doesn’t include the software you’re talking about is very close to worthless. You’re not reporting a scientific result at that point, however miraculous your result is; you’re making an unverifiable claim that your result exists.

And we look at that and say: what if you’ve got nothing? How can we know, without something we can audit and test? Of course, all the supporting research is paywalled PDFs with no concomitant code or data either, so by any metric that matters – and the only metric that matters here is “code I can run against data I can verify” – it doesn’t exist.

Those aren’t metrics that matter to you, though. What matters to you is either “getting a tenure-track position” or “getting hired to do work in your field”. And by and large the academic tenure track doesn’t care about open access, so you’re afraid that actually showing your work will actively hurt your likelihood of getting either of those jobs.

So here we are in this bizarro academic-research standoff, where I can’t work with you without your tipping your hand, and you can’t tip your hand for fear I won’t want to work with you. And so all of this work that could accomplish amazing things for a real company shipping real software that really matters to real people – five or six years of the best work you’ve ever done, probably – just sits on the shelf rotting away.

So I go to academic conferences and I beg people to publish their results and paper and data open access, because the world needs your work to matter. Because open access plus data/code as a minimum standard isn’t just important to the fundamental principles of repeatable experimental science, the integrity of your field, and your career. It’s important because if you want your work to matter to people, then you’d better put it somewhere that people can see it and use it and thank you for it and maybe even improve on it.

You did this as an undergrad. You insist on this from your undergrads, for exactly the same reasons I’m asking you to do the same: understanding, integrity and plain old better results. And it’s a few clicks and a GitHub account for you to do the same now. But I need you to do it one last time.

Full marks here isn’t “a job” or “tenure”. Your shot at those will be no worse, though I know you can’t see it from where you’re standing. But they’re still only a strong B. An A is doing something that matters, an accomplishment that changes the world for the better.

And if you want full marks, show your work.

October 29, 2014

Social Engineering

I gave this talk at FSOSS last week, in which I try to reclaim the term “Social Engineering”, so that it stops meaning “get the receptionist to give you their password” and starts meaning “Measuring community growth and turning that into processes and practices that work.”

I thought it went well, though listening to it I can see I’ve got a couple of verbal tics to work on. Gotta stop using ‘um’ and ‘right’ as punctuation.

October 22, 2013

Citation Needed

I may revisit this later. Consider this a late draft. I’m calling this done.

“Should array indices start at 0 or 1? My compromise of 0.5 was rejected without, I thought, proper consideration.” — Stan Kelly-Bootle

Sometimes somebody says something to me, like a whisper of a hint of an echo of something half-forgotten, and it lands on me like an invocation. The mania sets in, and it isn’t enough to believe; I have to know.

I’ve spent far more effort than is sensible this month crawling down a rabbit hole disguised, as they often are, as a straightforward question: why do programmers start counting at zero?

Now: stop right there. By now your peripheral vision should have convinced you that this is a long article, and I’m not here to waste your time. But if you’re gearing up to tell me about efficient pointer arithmetic or binary addition or something, you’re wrong. You don’t think you’re wrong and that’s part of a much larger problem, but you’re still wrong.

For some backstory, on the off chance anyone still reading by this paragraph isn’t an IT professional of some stripe: most computer languages including C/C++, Perl, Python, some (but not all!) versions of Lisp, many others – are “zero-origin” or “zero-indexed”. That is to say, in an array A with 8 elements in it, the first element is A[0], and the last is A[7]. This isn’t universally true, though, and other languages from the same (and earlier!) eras are sometimes one-indexed, going from A[1] to A[8].

While it’s a relatively rare practice in modern languages, one-origin arrays certainly aren’t dead; there’s a lot of blood pumping through Lua these days, not to mention MATLAB, Mathematica and a handful of others. If you’re feeling particularly adventurous Haskell apparently lets you pick your poison at startup, and in what has to be the most lunatic thing I’ve seen on a piece of silicon since I found out the MIPS architecture had runtime-mutable endianness, Visual Basic (up to v6.0) featured the OPTION BASE flag, letting you flip that coin on a per-module basis. Zero- and one-origin arrays in different corners of the same program! It’s just software, why not?

All that is to say that starting at 1 is not an unreasonable position at all; to a typical human thinking about the zeroth element of an array doesn’t make any more sense than trying to catch the zeroth bus that comes by, but we’ve clearly ended up here somehow. So what’s the story there?

The usual arguments involving pointer arithmetic and incrementing by sizeof(struct) and so forth describe features that are nice enough once you’ve got the hang of them, but they’re also post-facto justifications. This is obvious if you take the most cursory look at the history of programming languages; C inherited its array semantics from B, which inherited them in turn from BCPL, and though BCPL arrays are zero-origin, the language doesn’t support pointer arithmetic, much less data structures. On top of that other languages that antedate BCPL and C aren’t zero-indexed. Algol 60 uses one-indexed arrays, and arrays in Fortran are arbitrarily indexed – they’re just a range from X to Y, and X and Y don’t even need to be positive integers.

So by the early 1960’s, there are three different approaches to the data structure we now call an array.

  • Zero-indexed, in which the array index carries no particular semantics beyond its implementation in machine code.
  • One-indexed, identical to the matrix notation people have been using for quite some time. It comes at the cost of a CPU instruction or disused word to manage the offset; usability isn’t free.
  • Arbitrary indices, in which the range is significant with regards to the problem you’re up against.

So if your answer started with “because in C…”, you’ve been repeating a good story you heard one time, without ever asking yourself if it’s true. It’s not about *i = a + n*sizeof(x) because pointers and structs didn’t exist. And that’s the most coherent argument I can find; there are dozens of other arguments for zero-indexing involving “natural numbers” or “elegance” or some other unresearched hippie voodoo nonsense that are either wrong or too dumb to rise to the level of wrong.

The fact of it is this: before pointers, structs, C and Unix existed, at a time when other languages with a lot of resources and (by the standard of the day) user populations behind them were one- or arbitrarily-indexed, somebody decided that the right thing was for arrays to start at zero.

So I found that person and asked him.

His name is Dr. Martin Richards; he’s the creator of BCPL, now almost 7 years into retirement; you’ve probably heard of one of his doctoral students Eben Upton, creator of the Raspberry Pi. I emailed him to ask why he decided to start counting arrays from zero, way back then. He replied that…

As for BCPL and C subscripts starting at zero. BCPL was essentially designed as typeless language close to machine code. Just as in machine code registers are typically all the same size and contain values that represent almost anything, such as integers, machine addresses, truth values, characters, etc. BCPL has typeless variables just like machine registers capable of representing anything. If a BCPL variable represents a pointer, it points to one or more consecutive words of memory. These words are the same size as BCPL variables. Just as machine code allows address arithmetic so does BCPL, so if p is a pointer p+1 is a pointer to the next word after the one p points to. Naturally p+0 has the same value as p. The monodic indirection operator ! takes a pointer as it’s argument and returns the contents of the word pointed to. If v is a pointer !(v+I) will access the word pointed to by v+I. As I varies from zero upwards we access consecutive locations starting at the one pointed to by v when I is zero. The dyadic version of ! is defined so that v!i = !(v+I). v!i behaves like a subscripted expression with v being a one dimensional array and I being an integer subscript. It is entirely natural for the first element of the array to have subscript zero. C copied BCPL’s approach using * for monodic ! and [ ] for array subscription. Note that, in BCPL v!5 = !(v+5) = !(5+v) = 5!v. The same happens in C, v[5] = 5[v]. I can see no sensible reason why the first element of a BCPL array should have subscript one. Note that 5!v is rather like a field selector accessing a field in a structure pointed to by v.

This is interesting for a number of reasons, though I’ll leave their enumeration to your discretion. The one that I find most striking, though, is that this is the earliest example I can find of the understanding that a programming language is a user interface, and that there are difficult, subtle tradeoffs to make between resources and usability. Remember, all this was at a time when everything about the future of human-computer interaction was up in the air, from the shape of the keyboard and the glyphs on the switches and keycaps right down to how the ones and zeros were manifested in paper ribbon and bare metal; this note by the late Dennis Ritchie might give you a taste of the situation, where he mentions that five years later one of the primary reasons they went with C’s square-bracket array notation was that it was getting steadily easier to reliably find square brackets on the world’s keyboards.

“Now just a second, Hoye”, I can hear you muttering. “I’ve looked at the BCPL manual and read Dr. Richards’ explanation and you’re not fooling anyone. That looks a lot like the efficient-pointer-arithmetic argument you were frothing about, except with exclamation points.” And you’d be very close to right. That’s exactly what it is – the distinction is where those efficiencies take place, and why.

BCPL was first compiled on an IBM 7094here’s a picture of the console, though the entire computer took up a large room – running CTSS – the Compatible Time Sharing System – that antedates Unix much as BCPL antedates C. There’s no malloc() in that context, because there’s nobody to share the memory core with. You get the entire machine and the clock starts ticking, and when your wall-clock time block runs out that’s it. But here’s the thing: in that context none of the offset-calculations we’re supposedly economizing are calculated at execution time. All that work is done ahead of time by the compiler.

You read that right. That sheet-metal, “wibble-wibble-wibble” noise your brain is making is exactly the right reaction.

Whatever justifications or advantages came along later – and it’s true, you do save a few processor cycles here and there and that’s nice – the reason we started using zero-indexed arrays was because it shaved a couple of processor cycles off of a program’s compilation time. Not execution time; compile time.

Does it get better? Oh, it gets better:

IBM had been very generous to MIT in the fifties and sixties, donating or discounting its biggest scientific computers. When a new top of the line 36-bit scientific machine came out, MIT expected to get one. In the early sixties, the deal was that MIT got one 8-hour shift, all the other New England colleges and universities got a shift, and the third shift was available to IBM for its own use. One use IBM made of its share was yacht handicapping: the President of IBM raced big yachts on Long Island Sound, and these boats were assigned handicap points by a complicated formula. There was a special job deck kept at the MIT Computation Center, and if a request came in to run it, operators were to stop whatever was running on the machine and do the yacht handicapping job immediately.

Jobs on the IBM 7090, one generation behind the 7094, were batch-processed, not timeshared; you queued up your job along with a wall-clock estimate of how long it would take, and if it didn’t finish it was pulled off the machine, the next job in the queue went in and you got to try again whenever your next block of allocated time happened to be. As in any economy, there is a social context as well as a technical context, and it isn’t just about managing cost, it’s also about managing risk. A programmer isn’t just racing the clock, they’re also racing the possibility that somebody will come along and bump their job and everyone else’s out of the queue.

I asked Tom Van Vleck, author of the above paragraph and also now retired, how that worked. He replied in part that on the 7090…

“User jobs were submitted on cards to the system operator, stacked up in a big tray, and a rudimentary system read, loaded, and ran jobs in sequence. Typical batch systems had accounting systems that read an ID card at the beginning of a user deck and punched a usage card at end of job. User jobs usually specified a time estimate on the ID card, and would be terminated if they ran over. Users who ran too many jobs or too long would use up their allocated time. A user could arrange for a long computation to checkpoint its state and storage to tape, and to subsequently restore the checkpoint and start up again.

The yacht handicapping job pertained to batch processing on the MIT 7090 at MIT. It was rare — a few times a year.”

So: the technical reason we started counting arrays at zero is that in the mid-1960’s, you could shave a few cycles off of a program’s compilation time on an IBM 7094. The social reason is that we had to save every cycle we could, because if the job didn’t finish fast it might not finish at all and you never know when you’re getting bumped off the hardware because the President of IBM just called and fuck your thesis, it’s yacht-racing time.

There are a few points I want to make here.

The first thing is that as far as I can tell nobody has ever actually looked this up.

Whatever programmers think about themselves and these towering logic-engines we’ve erected, we’re a lot more superstitious than we realize. We tell and retell this collection of unsourced, inaccurate stories about the nature of the world without ever doing the research ourselves, and there’s no other word for that but “mythology”. Worse, by obscuring the technical and social conditions that led humans to make these technical and social decisions, by talking about the nature of computing as we find it today as though it’s an inevitable consequence of an immutable set of physical laws, we’re effectively denying any responsibility for how we got here. And worse than that, by refusing to dig into our history and understand the social and technical motivations for those choices, by steadfastly refusing to investigate the difference between a motive and a justification, we’re disavowing any agency we might have over the shape of the future. We just keep mouthing platitudes and pretending the way things are is nobody’s fault, and the more history you learn and the more you look at the sad state of modern computing the the more pathetic and irresponsible that sounds.

Part of the problem is access to the historical record, of course. I was in favor of Open Access publication before, but writing this up has cemented it: if you’re on the outside edge of academia, $20/paper for any research that doesn’t have a business case and a deep-pocketed backer is completely untenable, and speculative or historic research that might require reading dozens of papers to shed some light on longstanding questions is basically impossible. There might have been a time when this was OK and everyone who had access to or cared about computers was already an IEEE/ACM member, but right now the IEEE – both as a knowledge repository and a social network – is a single point of a lot of silent failure. “$20 for a forty-year-old research paper” is functionally indistinguishable from “gone”, and I’m reduced to emailing retirees to ask them what they remember from a lifetime ago because I can’t afford to read the source material.

The second thing is how profoundly resistant to change or growth this field is, and apparently has always been. If you haven’t seen Bret Victor’s talk about The Future Of Programming as seen from 1975 you should, because it’s exactly on point. Over and over again as I’ve dredged through this stuff, I kept finding programming constructs, ideas and approaches we call part of “modern” programming if we attempt them at all, sitting abandoned in 45-year-old demo code for dead languages. And to be clear: that was always a choice. Over and over again tools meant to make it easier for humans to approach big problems are discarded in favor of tools that are easier to teach to computers, and that decision is described as an inevitability.

This isn’t just Worse Is Better, this is “Worse Is All You Get Forever”. How many off-by-one disasters could we have avoided if the “foreach” construct that existed in BCPL had made it into C? How much more insight would all of us have into our code if we’d put the time into making Michael Chastain’s nearly-omniscient debugging framework – PTRACE_SINGLESTEP_BACKWARDS! – work in 1995? When I found this article by John Backus wondering if we can get away from Von Neumann architecture completely, I wonder where that ambition to rethink our underpinnings went. But the fact of it is that it didn’t go anywhere. Changing how you think is hard and the payoff is uncertain, so by and large we decided not to. Nobody wanted to learn how to play, much less build, Engelbart’s Violin, and instead everyone gets a box of broken kazoos.

In truth maybe somebody tried – maybe even succeeded! – but it would cost me hundreds of dollars to even start looking for an informed guess, so that’s the end of that.

It’s hard for me to believe that the IEEE’s membership isn’t going off a demographic cliff these days as their membership ages, and it must be awful knowing they’ve got decades of delicious, piping-hot research cooked up that nobody is ordering while the world’s coders are lining up to slurp watery gruel out of a Stack-Overflow-shaped trough and pretend they’re well-fed. You might not be surprised to hear that I’ve got a proposal to address both those problems; I’ll let you work out what it might be.

May 30, 2012

Verily

Filed under: academia,documentation,weird — mhoye @ 12:12 pm

Today I learned that “I did your mom” jokes are the summit of cultured humour.

DEMETRIUS: Villain, what hast thou done?
AARON: That which thou canst not undo.
CHIRON: Thou hast undone our mother.
AARON: Villain, I have done thy mother.

That’s from Shakespeare’s Titus Andronicus, of all things.

I miss Nick; he would have looked at me like I was dumb for not knowing this.

January 20, 2012

On Hiring

Filed under: academia,doom,fail,interfaces,linux,losers,vendetta — mhoye @ 1:25 pm

I’ve decided that if I find out a job applicant has internet-bragged that they could implement some major (Kickstarter, Ebay, Etsy, Facebook, anything…) website’s functionality in a week with Ruby – and it’s always Ruby, lately – I’m going to give them an interview right away, just so I can ask them why they haven’t.

I’d never give them a job. I just want to watch them squirm when I ask the question.

January 19, 2012

Political Theory, Asymmetric Warfare & Batman Movies

Filed under: academia,documentation,interfaces,life,linux,work — mhoye @ 4:55 pm

I made this presentation to Seneca’s Free Software and Open Source Symposium last year; it is dreadfully embarassing, revealing mainly that I’m a terrible speaker who tells weak jokes, goes off into the weeds too often, rambles and says “um” far and away too much. This is just the voice track over my slides, which I’ll put up later this evening.

I’m sure the general outline of the presentation I’d like to have given is in there somewhere, but here you go.

November 19, 2011

“I knew it, I’m surrounded by assholes.”

Dark Helmet: Who is he?
Colonel Sandurz: He’s an Asshole, sir.
Dark Helmet: I know that! What’s his name?
Colonel Sandurz: That is his name, sir. Asshole. Major Asshole.

Have I mentioned that the No Asshole Rule has profound geopolitical implications? It’s an idea that’s been rattling around my head for a while.

JWZ links to the question:

In Egypt earlier this year, the cops refused to attack the people. East Germany and then the whole Iron Curtain collapsed when the local cops wouldn’t smash heads when Erich Honecker ordered it. What about America? Where are the cops who walked off the job rather than attack their neighbors drowning in debt and despair?

Daniel Davies provides the answer:

And so that brings me to a useful piece of advice for any readers who are aspiring dictators, one that the Communists knew, Suharto knew, but that some modern day tyrants seem to have forgotten. There is always a level of civil unrest that outstrips the capability of even the most loyal and largest regular armed forces to deal with. In all likelihood, as a medium sized emerging market, you will have a capital city with a population of about five or six million, meaning potentially as many as three million adults on the streets in the worst case. Your total active-duty armed forces are unlikely to be a tenth of that. When it becomes a numbers game, there is only one thing that can save you.

And that is, a reactionary citizens’ militia, to combat the revolutionary citizens’ militia. Former socialist republics always used to be fond of buses full of coal miners from way out the back of beyond, but the Iranian basijis are the same sort of thing. Basically, what you need is a large population who are a few rungs up from the bottom of society, who aren’t interested in freedom and who hate young people. In other words, arseholes. Arseholes, considered as a strategic entity, have the one useful characteristic that is the only useful characteristic in the context of an Egyptian-style popular uprising – there are f—ing millions of them.

This is my advice to any aspiring dictator; early on in your career, identify and inventory all the self-pitying, bullying shitheads your country has to offer. Anyone with a grievance, a beer belly and enough strength to swing a pickaxe handle will do. You don’t need to bother with military training or discipline because they’re hopefully never going to be used as a proper military force – just concentrate on nurturing their sense that they, despite appearances, are the backbone of the country, and allowing them to understand that although rules are rules, there are some people who just need a slap. The bigger and burlier the better, but when the time comes they’ll be fighting in groups against people weaker than themselves, often under cover of darkness, so numbers are more important than anything else. The extractive industries are indeed often a good source, as are demobbed veterans (Zimbabwe) or the laity of an established religion.

I think this is my new rule for assessing the stability of any dictatorship around the world, and I am on the lookout for any Francis Fukuyama-style book contracts. The key factor in determining the survival of repressive regimes isn’t economics, religion or military success. It’s arseholes.

If you’ve been reading the news lately, this may sound familiar. It’s that sentence near the end there – “The bigger and burlier the better, but when the time comes they’ll be fighting in groups against people weaker than themselves, often under cover of darkness, so numbers are more important than anything else” – that makes it so horribly prescient.

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