Occupy Central and the Rising Risk of New Mass Atrocities in China

This is a cross-post from the blog of the Early Warning Project, which I currently direct. The Early Warning Project concentrates on risks of mass atrocities, but this post also draws on my longstanding interest in democratization and social unrest, so I thought I would share it here as well.

Activists have massed by the thousands in central Hong Kong for the past several days in defiance of repeated attempts to disperse them and menacing words from Beijing. This demonstration and the wider Occupy Central movement from which it draws poses one of the sharpest public challenges to Communist Party authority since the Tiananmen Square uprising 25 years ago. In so doing, it clearly raises the risk of a new mass atrocities in China.

Photo credit: AP via BBC News

Photo credit: AP via BBC News

The demonstrations underway now are really just the latest surge in a wave of activism that began in Hong Kong earlier this year. Under the “one country, two systems” framework to which China committed when it regained sovereignty over the then–UK colony in 1997, Hong Kong is supposed to enjoy a great deal of autonomy over local governance. This summer, however, Beijing issued a white paper affirming the central government’s “comprehensive jurisdiction” over Hong Kong, and it blocked plans for open nominations in local elections due in 2017. Those actions spurred (and were spurred by) an unofficial referendum and a mass pro-democracy rally that eventually ebbed from the streets but left behind a strengthened civic movement.

The ongoing demonstrations began with a student boycott of classes a week ago, but they escalated sharply on Friday, when activists began occupying key public spaces in central Hong Kong. Police have made several forceful attempts to disperse or remove the protesters, and official channels have said publicly that Beijing “firmly opposes all illegal activities that could undermine rule of law and jeopardise ‘social tranquility'” in Hong Kong. So far, however, the occupations have proved resilient to those thrusts and threats.

Many observers are now openly wondering how this confrontation will end. For those sympathetic to the protesters, the fear is that Beijing will respond with lethal force, as it did at Tiananmen Square in 1989.

As it happens, the Early Warning Project’s statistical risk assessments do not identify China as a country at relatively high risk of state-led mass killing this year. Partly because of that, we do not currently have a question open on our opinion pool that covers this situation. (Our lone China question focuses on the risk of state-led mass atrocities targeting Uyghurs.)

If we did have a relevant question open on our opinion pool, however, I would be raising my estimate of the risk of a state-led mass killing in response to these developments. I still don’t expect that one will occur, but not because I anticipate that Beijing will concede to the protesters’ demands. Rather, I expect violent repression, but I also doubt that it will cross the 1,000-death threshold we and others use to distinguish episodes of mass killing from smaller-scale and more routine atrocities.

State-led mass killings as we define them usually occur when incumbent rulers perceive potentially existential threats to their authority. Following leading theories on the subject, our statistical analysis concentrates on armed insurgencies and coups as the forms those threats typically take. Authoritarian governments often suppress swelling demonstrations with violence as well, but those crackdowns rarely kill as many as 1,000 nonviolent protesters, who usually disperse long before that threshold is reached. Even the Tiananmen Square massacre probably fell short of this threshold, killing “only” hundreds of activists before achieving the regime’s goal of dispersing the occupation and setting an example that would frighten future dissenters.

Instead, violent state crackdowns usually push countries onto one of three other pathways before they produce more than 1,000 fatalities: 1) they succeed at breaking the uprising and essentially restore the status quo ante (e.g., China in 1989, Uzbekistan in 2005Burma in 2007, and Thailand in 2010); 2) they suppress the nonviolent challenge but, in so doing, help to spawn a violent rebellion that may or may not be met with a mass killing of its own (e.g., Syria since 2011); or 3) they catalyze splits in state security forces or civilian rulers that lead to negotiations, reforms, or regime collapse (e.g., Egypt and Tunisia in 2011). In short, nonviolent uprisings usually lose, transform, or win before the attempts to suppress them amount to what we would call a state-led mass killing.

In Hong Kong right now, the first path—successful repression—appears to be the most likely. Chinese Communist Party leaders have spoken openly in recent years about trying to learn from the mistakes that led to collapse of the Soviet Union, and the mixed signals that were sent to early risers in the USSR—some protests were repressed, but others were allowed to run their course or met with modest concessions—probably rank high on their list of things to avoid. Those Party leaders also know that activists and separatists elsewhere in China are closely watching events in Hong Kong and would probably take encouragement from anything short of a total defeat for Occupy Central. These considerations generate strong incentives to try to quash the current challenge.

In contrast, the second of those three trajectories—a transformation to violent insurgency in response to state repression—seems highly unlikely. Protesters have shown a strong commitment to nonviolence so far and have strategic as well as ideological reasons to continue to do so; after all, the People’s Liberation Army is about as formidable a foe as they come. Brutal state repression might radicalize some survivors and inspire other onlookers, but Hong Kong is a wealthy, urban enclave with minimal access to arms, so a turn toward violent rebellion would face tall structural obstacles.

The third of those trajectories also seems unlikely, albeit somewhat less so than the second. The Communist Party currently faces several profound challenges: a slowing rate of economic growth and widespread concern about a looming financial crisis; an escalating insurgency in Xinjiang; and an epidemic of local protests over pollution, to name just a few. Meanwhile, Xi Jinping’s anti-corruption campaign is creating new fissures within the country’s ruling class, and rumors of dissent within the military have swirled occasionally in the past two years as well. As I discussed in a recent blog post, consolidated single-party regimes like China’s usually weather these kinds of challenges. When they do break down, however, it almost always happens in times like these, when worried insiders start to fight among themselves and form alliances with emboldened popular challengers.

Put those considerations together, and it seems that Beijing is most likely to respond to Occupy Central with a crackdown that could be lethal but probably will not cross the 1,000-death threshold we use to distinguish episodes of mass killing from more routine political violence. It seems less likely but still possible that the prospect or occurrence of such a crackdown will catalyze the kinds of elite splits that could finally produce significant political reform or sustained instability in China. Under none of these circumstances would I expect the challenge in Hong Kong to evolve into an armed rebellion that might produce a new wave of atrocities of its own.

No matter what the immediate outcome, though, it seems increasingly clear that China has entered a period of “thickened history,” as Marc Beissinger calls it, in which national politics will remain more eventful and less certain for some time to come.

No, Pope Francis, this is not World War Three

In the homily to a mass given this morning in Italy, at a monument to 100,000 soldiers killed in World War I, Pope Francis said:

War is madness… Even today, after the second failure of another world war, perhaps one can speak of a third war, one fought piecemeal, with crimes, massacres, destruction.

There are a lot of awful things happening around the world, and I appreciate the pope’s advocacy for peace, but this comparison goes too far. Take a look at this chart of battle deaths from armed conflict around the world from 1900 to 2005, from a study by the Peace Research Institute of Oslo:

The chart doesn’t include the past decade, but we don’t need all the numbers in one place to see what a stretch this comparison is. Take Syria’s civil war, which has probably killed more than 150,000 (source) and perhaps as many as 300,000 or more people over the past three years, for an annual death rate of 50,000–100,000. That is a horrifying toll, but it is vastly lower than the annual rates in the several millions that occurred during the World Wars. Put another way, World War II was like 40 to 80 Syrian civil wars at once.

The many other wars of the present do not substantially close this gap. The civil war in Ukraine has killed approximately 3,000 so far (source). More than 2,000 people have died in the fighting associated with Israel’s Operation Protective Edge in Gaza this year (source). The resurgent civil war in Iraq dwarfs them both but still remains well below the intensity of the (interconnected) war next door (source). There are more than 20 other armed conflicts ongoing around the world, but most of them are much less lethal than the ones in Syria and Iraq, and their cumulative toll does not even begin to approach the ones that occurred in the World Wars (source).

I sympathize with the Pope’s intentions, but I don’t think that hyperbole is the best way to realize them. Of course, Pope Francis is not alone; we’ve been hearing a lot of this lately. I wonder if violence on the scale of the World Wars now lies so far outside of our lived experience that we simply cannot fathom it. Beyond some level of disorder, things simply become terrible, and all terrible things are alike. I also worry that the fear this apparent availability cascade is producing will drive other governments to react in ways that only make things worse.

What are all these violent images doing to us?

Early this morning, I got up, made some coffee, sat down at my desk, and opened Twitter to read the news and pass some time before I had to leave for a conference. One of the first things I saw in my timeline was a still from a video of what was described in the tweet as an ISIS fighter executing a group of Syrian soldiers. The soldiers lay on their stomachs in the dirt, mostly undressed, hands on their heads. They were arranged in a tightly packed row, arms and legs sometimes overlapping. The apparent killer stood midway down the row, his gun pointed down, smoke coming from its barrel.

That experience led me to this pair of tweets:

tweet 1

tweet 2

If you don’t use Twitter, you probably don’t know that, starting in 2013, Twitter tweaked its software so that photos and other images embedded in tweets would automatically appear in users’ timelines. Before that change, you had to click on a link to open an embedded image. Now, if you follow someone who appends an image to his or her tweet, you instantly see the image when the tweet appears in your timeline. The system also includes a filter of sorts that’s supposed to inform you before showing media that may be sensitive, but it doesn’t seem to be very reliable at screening for violence, and it can be turned off.

As I said this morning, I think the automatic display of embedded images is great for sharing certain kinds of information, like data visualizations. Now, tweets can become charticles.

I am increasingly convinced, though, that this feature becomes deeply problematic when people choose to share disturbing images. After I tweeted my complaint, Werner de Pooter pointed out a recent study on the effects of frequent exposure to graphic depictions of violence on the psychological health of journalists. The study’s authors found that daily exposure to violent images was associated with higher scores on several indices of psychological distress and depression. The authors conclude:

Given that good journalism depends on healthy journalists, news organisations will need to look anew at what can be done to offset the risks inherent in viewing User Generated Content material [which includes graphic violence]. Our findings, in need of replication, suggest that reducing the frequency of exposure may be one way to go.

I mostly use Twitter to discover stories and ideas I don’t see in regular news outlets, to connect with colleagues, and to promote my own work. Because I study political violence and atrocities, a fair share of my feed deals with potentially disturbing material. Where that material used to arrive only as text, it increasingly includes photos and video clips of violent or brutal acts as well. I am starting to wonder how routine exposure to those images may be affecting my mental health. The study de Pooter pointed out has only strengthened that concern.

I also wonder if the emotional power of those images is distorting our collective sense of the state of the world. Psychologists talk about the availability heuristic, a cognitive shortcut in which the ease of recalling examples of certain things drives our expectations about the likelihood or risk of those things. As Daniel Kahneman describes on p. 138 of Thinking, Fast and Slow,

Unusual events (such as botulism) attract disproportionate attention and are consequently perceived as less unusual than they really are. The world in our heads is not a precise replica of reality; our expectations about the frequency of events are distorted by the prevalence and emotional intensity of the messages to which we are exposed.

When those images of brutal violence pop into our view, they grab our attention, pack a lot of emotional intensity, and are often to hard to shake. The availability heuristic implies that frequent exposure to those images leads us to overestimate the threat or risk of things associated with them.

This process could even be playing some marginal role in a recent uptick in stories about how the world is coming undone. According to Twitter, its platform now has more than 270 million monthly active users. Many journalists and researchers covering world affairs probably fall in that 270 million. I suspect that those journalists and researchers spend more time watching their timelines than the average user, and they are probably more likely to turn off that “sensitive content” warning, too.

Meanwhile, smartphones and easier Internet access make it increasingly likely that acts of violence will be recorded and then shared through those media, and Twitter’s default settings now make it more likely that we see them when they are. Presumably, some of the organizations perpetrating this violence—and, sometimes, ones trying to mobilize action to stop it—are aware of the effects these images can have and deliberately push them to us to try to elicit that response.

As a result, many writers and analysts are now seeing much more of this material than they used to, even just a year or two ago. Whatever the actual state of the world, this sudden increase in exposure to disturbing material could be convincing many of us that the world is scarier and therefore more dangerous than ever before.

This process could have larger consequences. For example, lately I’ve had trouble getting thoughts of James Foley’s killing out of my mind, even though I never watched the video of it. What about the journalists and policymakers and others who did see those images? How did that exposure affect them, and how much is that emotional response shaping the public conversation about the threat the Islamic State poses and how our governments should respond to it?

I’m not sure what to do about this problem. As an individual, I can choose to unfollow people who share these images or spend less time on Twitter, but both of those actions carry some professional costs as well. The thought of avoiding these images also makes me feel guilty, as if I am failing the people whose suffering they depict and the ones who could be next. By hiding from those images, do I become complicit in the wider violence and injustice they represent?

As an organization, Twitter could decide to revert to the old no-show default, but that almost certainly won’t happen. I suspect this isn’t an issue for the vast majority of users, and it’s hard to imagine any social-media platform retreating from visual content as sites like Instagram and Snapchat grow quickly. Twitter could also try to remove embedded images that contain potentially disturbing material. As a fan of unfettered speech, though, I don’t find that approach appealing, either, and the unreliability of the current warning system suggests it probably wouldn’t work so well anyway.

In light of all that uncertainty, I’ll conclude with an observation instead of a solution: this is one hell of a huge psychological experiment we’re running right now, and its consequences for our own mental health and how we perceive the world around us may be more substantial than we realize.

The Worst World EVER…in the Past 5 or 10 Years

A couple of months ago, the head of the UN’s refugee agency announced that, in 2013, “the number of people displaced by violent conflict hit the highest level since World War II,” and he noted that the number was still growing in 2014.

A few days ago, under the headline “Countries in Crisis at Record High,” Foreign Policy‘s The Cable reported that the UN’s Inter-Agency Standing Committee for the first time ever had identified four situations worldwide—Syria, Iraq, South Sudan, and Central African Republic—as level 3 humanitarian emergencies, its highest (worst) designation.

Today, the Guardian reported that “last year was the most dangerous on record for humanitarian workers, with 155 killed, 171 seriously wounded and 134 kidnapped as they attempted to help others in some of the world’s most dangerous places.'”

If you read those stories, you might infer that the world has become more insecure than ever, or at least the most insecure it’s been since the last world war. That would be reasonable, but probably also wrong.  These press accounts of record-breaking trends are often omitting or underplaying a crucial detail: the data series on which these claims rely don’t extend very far into the past.

In fact, we don’t know how the current number of displaced persons compares to all years since World War II, because the UN only has data on that since 1989. In absolute terms, the number of refugees worldwide is now the largest it’s been since record-keeping began 25 years ago. Measured as a share of global population, however, the number of displaced persons in 2013 had not yet matched the peak of the early 1990s (see the Addendum here).

The Cable accurately states that having four situations designated as level-3 humanitarian disasters by the UN is “unprecedented,” but we only learn late in the story that the system which makes these designations has only existed for a few years. In other words, unprecedented…since 2011.

Finally, while the Guardian correctly reports that 2013 was the most dangerous year on record for aid workers, it fails to note that those records only reach back to the late 1990s.

I don’t mean to make light of worrisome trends in the international system or any of the terrible conflicts driving them. From the measures I track—see here and here, for example, and here for an earlier post on causes—I’d say that global levels of instability and violent conflict are high and waxing, but they have not yet exceeded the peaks we saw in the early 1990s and probably the 1960s. Meanwhile, the share of states worldwide that are electoral democracies remains historically high, and the share of the world’s population living in poverty has declined dramatically in the past few decades. The financial crisis of 2008 set off a severe and persistent global recession, but that collapse could have been much worse, and institutions of global governance deserve some credit for helping to stave off an even deeper failure.

How can all of these things be true at the same time? It’s a bit like climate change. Just as one or even a few unusually cool years wouldn’t reverse or disprove the clear long-term trend toward a hotter planet, an extended phase of elevated disorder and violence doesn’t instantly undo the long-term trends toward a more peaceful and prosperous human society. We are currently witnessing (or suffering) a local upswing in disorder that includes numerous horrific crises, but in global historical terms, the world has not fallen apart.

Of course, if it’s a mistake to infer global collapse from these local trends, it’s also a mistake to infer that global collapse is impossible from the fact that it hasn’t occurred already. The war that is already consuming Syria and Iraq is responsible for a substantial share of the recent increase in refugee flows and casualties, and it could spread further and burn hotter for some time to come. Probably more worrisome to watchers of long-term trends in international relations, the crisis in Ukraine and recent spate of confrontations between China and its neighbors remind us that war between major powers could happen again, and this time those powers would both or all have nuclear weapons. Last but not least, climate change seems to be accelerating with consequences unknown.

Those are all important sources of elevated uncertainty, but uncertainty and breakdown are not the same thing. Although those press stories describing unprecedented crises are all covering important situations and trends, I think their historical perspective is too shallow. I’m forty-four years old. The global system is less orderly than it’s been in a while, but it’s still not worse than it’s ever been in my lifetime, and it’s still nowhere near as bad as it was when my parents were born. I won’t stop worrying or working on ways to try to make things a tiny bit better, but I will keep that frame of reference in mind.

In Praise of a Measured Response to the Ukraine Crisis

Yesterday afternoon, I tweeted that the Obama administration wasn’t getting enough credit for its measured response to the Ukraine crisis so far, asserting that sanctions were really hurting Russia and noting that “we”—by which I meant the United States—were not directly at war.

Not long after I said that, someone I follow tweeted that he hadn’t seen a compelling explanation of how sanctions are supposed to work in this case. That’s an important question, and one I also haven’t seen or heard answered in depth. I don’t know how U.S. or European officials see this process beyond what they say in public, but I thought I would try to spell out the logic as a way to back up my own assertion in support of the approach the U.S. and its allies have pursued so far.

I’ll start by clarifying what I’m talking about. When I say “Ukraine crisis,” I am referring to the tensions created by Russia’s annexation of Crimea and its evident and ongoing support for a separatist rebellion in eastern Ukraine. These actions are only the latest in a long series of interactions with the U.S. and Europe in Russia’s “near abroad,” but their extremity and the aggressive rhetoric and action that has accompanied them have sharply amplified tensions between the larger powers that abut Ukraine on either side. For the first time in a while, there has been open talk of a shooting war between Russia and NATO. Whatever you make of the events that led to it and however you assign credit or blame for them, this state of affairs represents a significant and undesirable escalation.

Faced with this crisis, the U.S. and its NATO allies have three basic options: compel, cajole, or impel.

Compel in this case means to push Russia out of Ukraine by force—in other words, to go to war. So far, the U.S. and Europe appear to have concluded—correctly, in my opinion—that Russia’s annexation of Crimea and its support for separatists in eastern Ukraine does not warrant a direct military response. The likely and possible costs of war between two nuclear powers are simply too great to bear for the sake of Ukraine’s autonomy or territorial integrity.

Cajoling would mean persuading Russian leaders to reverse course through positive incentives—carrots of some kind. It’s hard to imagine what the U.S. and E.U. could offer that would have the desired effect, however. Russian leaders consider Ukraine a vital interest, and the West has nothing comparably valuable to offer in exchange. More important, the act of making such an offer would reward Russia for its aggression, setting a precedent that could encourage Russia to grab for more and could also affect other country’s perceptions of the U.S.’s tolerance for seizures of territory.

That leaves impel—to impose costs on Russia to the point where its leaders feel obliged to change course. The chief tool that U.S. and European leaders have to impose costs on Russia are economic and financial sanctions. Those leaders are using this tool, and it seems to be having the desired effect. Sanctions are encouraging capital flight, raising the costs of borrowing, increasing inflation, and slowing Russia’s already-anemic economic growth (see here and here for some details). Investors, bankers, and consumers are partly responding to the specific constraints of sanctions, but they are also responding to the broader economic uncertainty associated with those sanctions and the threat of wider war they imply. “It’s pure geopolitical risk,” one analyst told Bloomberg.

These costs can directly and indirectly shape Russian policy. They can directly affect Russian policy if and as the present leadership comes to view them as unbearable, or at least not worth the trade-offs against other policy objectives. That seems unlikely in the short term but increasingly likely over the long term, if the sanctions are sustained and markets continue to react so negatively. Sustained capital flight, rising inflation, and slower growth will gradually shrink Russia’s domestic policy options and its international power by eroding its fiscal health, and at some point these costs should come to outweigh the putative gains of territorial expansion and stronger leverage over Ukrainian policy.

These costs can also indirectly affect Russian policy by increasing the risk of internal instability. In authoritarian regimes, significant reforms usually occur in the face of popular unrest that may or may not be egged on by elites who defect from the ruling coalition. We are already seeing signs of infighting among regime insiders, and rising inflation and slowing growth should increase the probability of popular unrest.

To date, sanctions have not dented Putin’s soaring approval rating, but social unrest is not a referendum. Unrest only requires a small but motivated segment of the population to get started, and once it starts, its very occurrence can help persuade others to follow. I still wouldn’t bet on Putin’s downfall in the near future, but I believe the threat of significant domestic instability is rising, and I think that Putin & co. will eventually care more about this domestic risk than the rewards of continued adventurism abroad. In fact, I think we see some evidence that Putin & co. are already worrying more about this risk in their ever-expanding crackdown on domestic media and their recent moves to strengthen punishment for unauthorized street rallies and, ironically, calls for separatism. Even if this mobilization does not come, the increased threat of it should weigh on the Russian administration’s decision-making.

In my tweet on the topic, I credited the Obama administration for using measured rhetoric and shrewd policy in response to this crisis. Importantly, though, the success of this approach also depends heavily on cooperation among the U.S. and the E.U., and that seems to be happening. It’s not clear who deserves the credit for driving this process, but as one anonymous tweeter pointed out, the downing of flight MH17 appears to have played a role in deepening it.

Concerns are growing that sanctions may, in a sense, be too successful. Some observers fear that apparent capitulation to the U.S. and Europe would cost Russian leaders too much at home at a time when nationalist fervor has reached fever pitch. Confronted with a choice between wider war abroad or a veritable lynch mob at home, Putin & co. will, they argue, choose the former.

I think that this line of reasoning overstates the extent to which the Russian administration’s hands are tied at home. Putin & co. are arguably no more captive to the reinvigorated radical-nationalist fringe than they were to the liberal fringe that briefly threatened to oust them after the last presidential election.

Still, it is at least a plausible scenario, and the U.S. and E.U. have to be prepared for the possibility that Russian aggression will get worse before it gets better. This is where rhetorical and logistical efforts to bolster NATO are so important, and that’s just what NATO has been doing. NATO is predicated on a promise of collective defense; an attack on any one member state is regarded as an attack on all. By strengthening Russian policy-makers’ beliefs that this promise is credible, NATO can lead them to fear that escalations beyond certain thresholds will carry extreme costs and even threaten their very survival. So far, that’s just what the alliance has been doing with a steady flow of words and actions. Russian policy-makers could still choose wider war for various reasons, but theory and experience suggest that they are less likely to do so than they would be in the absence of this response.

In sum, given a short menu of unpalatable options, I think that the Obama administration and its European allies have chosen the best line of action and, so far, made the most of it. To expect Russia quickly to reverse course by withdrawing from Crimea and stopping its rabble-rousing in eastern Ukraine without being compelled by force to do so is unrealistic. The steady, measured approach the U.S. and E.U. have adopted appears to be having the intended effects. Russia could still react to the rising structural pressures on it by lashing out, but NATO is taking careful steps to discourage that response and to prepare for it if it comes. Under such lousy circumstances, I think this is about as well as we could expect the Obama administration and its E.U. counterparts to do.

Another Chicken Little Post on China

Last fall, I described what I saw as an “accumulating risk of crisis” in China. Recent developments in two parts of the country only reinforce my sense that the Communist Party of China (CPC) is entering a period during which it will find it increasingly hard to sustain its monopoly on state authority.

The first part of the country drawing fresh attention is Hong Kong, where pro-democracy activists have mobilized a new nonviolent challenge to the Party’s authority in spite of the center’s pointed efforts to discourage them. Organizing under the Occupy Central label, these activists recently held an unofficial referendum that drew nearly 800,000 voters who overwhelmingly endorsed proposals that would allow the public to nominate candidates for elections in 2017—an idea that Beijing has repeatedly and unequivocally rejected. Today, on 1 July, tens of thousands of people marched into the city’s center to press those same demands.

1 July 2014 rally in Hong Kong (AP via BBC News)

The 1 July rally looks set to be one of the island’s largest protests in years, and it comes only weeks after Beijing issued a white paper affirming its “comprehensive jurisdiction” over Hong Kong. Although the official line since the 1997 handover has been “one country, two systems,” the expectation has generally been that national leaders would only tolerate differences that didn’t directly challenge their authority, and the new white paper made that implicit policy a bit clearer. Apparently, though, many Hong Kong residents aren’t willing to leave that assertion unchallenged, and the resulting conflict is almost certain to persist into and beyond those 2017 elections, assuming Beijing doesn’t concede the point before then.

The second restive area is Xinjiang Uyghur Autonomous Region, where Uyghurs have agitated for greater autonomy or outright independence since the area’s incorporation into China in 1949. Over the past year or so, the pace of this conflict has intensified again.

The Chinese government describes this conflict as a fight against terrorism, and some of the recent attacks—see here and here, for example—have targeted and killed large numbers of civilians. As Assaf Moghadam argues in a recent blog post, however, the line between terrorism and insurgency is almost always blurry in practice. Terrorism and insurgency—and, for that matter, campaigns of nonviolent resistance—are all tactical variations on the theme of rebellion. In Xinjiang, we see evidence of a wider insurgency in recent attacks on police stations and security checkpoints, symbols of the “occupying power” and certainly not civilian targets. Some Uyghurs have also engaged in nonviolent protests, although when they have, the police have responded harshly.

In any case, the tactical variation and increased pace and intensity of the clashes leads me to believe that this conflict should now be described as a separatist rebellion, and that this rebellion now poses a significant challenge to the Communist Party. Uyghurs certainly aren’t going to storm the capital, and they are highly unlikely to win sovereignty or independence for Xinjiang as long as the CPC still rules. Nevertheless, the expanding rebellion is taxing the center, and it threatens to make Party leaders look less competent than they would like.

Neither of these conflicts is new, and the Party has weathered flare-ups in both regions before. What is new is their concurrence with each other and with a number of other serious political and economic challenges. As the conflicts in Xinjiang and Hong Kong intensify, China’s real-estate market finally appears to be cooling, with potentially significant effects on the country’s economy, and pollution remains a national crisis that continues to stir sporadic unrest among otherwise “ordinary” citizens. And, of course, Party leaders are simultaneously pursuing an anti-corruption campaign that is hitting higher and higher targets. This campaign is ostensibly intended to bolster the economy and to address popular frustration over abuses of power, but like any purge, it also risks generating fresh enemies.

For reasons Barbara Geddes helps to illuminate (here), consolidated single-party authoritarian regimes like China’s tend to be quite resilient. They persist because they usually do a good job suppressing domestic opponents and co-opting would-be rivals within the ruling party. Single-party regimes are better than others at co-opting internal rivals because, under all but exceptional circumstances, regime survival reliably generates better payoffs for all factions than the alternatives.

Eventually, though, even single-party regimes break down, and when they do, it’s usually in the face of an economic crisis that simultaneously stirs popular frustration and weakens incentives for elites to remain loyal (on this point, see Haggard and Kaufman, too). Exactly how these regimes come undone is a matter of local circumstance and historical accident, but generally speaking, the likelihood increases as popular agitation swells and the array of potential elite defectors widens.

China’s slowing growth rate and snowballing financial troubles indicate that the risk of an economic crisis is still increasing. At the same time, the crises in Hong Kong, Xinjiang, and the many cities and towns where citizens are repeatedly protesting against pollution and corruption suggest that insiders who choose to defect would have plenty of potential allies to choose from. As I’ve said before, I don’t believe that the CPC regime is on the brink of collapse, but I would be surprised to see it survive in its current form—with no legal opposition and direct elections in rural villages only—to and through the Party’s next National Congress, due in in 2017.

Refugee Flows and Disorder in the Global System

This

The number of people displaced by violent conflict hit the highest level since World War II at the end of 2013, the head of the United Nations refugee agency, António Guterres, said in a report released on Friday…

Moreover, the impact of conflicts raging this year in Central African Republic, South Sudan, Ukraine and now Iraq threatens to push levels of displacement even higher by the end of 2014, he said.

…is, I think, another manifestation of the trends I discussed in a blog post here last September:

If we think on a systemic scale, it’s easier to see that we are now living through a period of global disorder matched in recent history only by the years surrounding the disintegration of the Soviet Union, and possibly exceeding it. Importantly, it’s not just the spate of state collapses through which this disorder becomes evident, but also the wider wave of protest activity and institutional transformation to which some of those collapses are connected.

If that’s true, then Mr. Guterres is probably right when he predicts that this will get even worse this year, because things still seem to be trending toward disorder. A lot of the transnational activity in response to local manifestations is still deliberately inflammatory (e.g., materiel and cash to rebels in Syria and Iraq, Russian support for separatists in Ukraine), and international efforts to quell some of those manifestations (e.g., UN PKOs in CAR and South Sudan) are struggling. Meanwhile, in what’s probably both a cause and an effect of these processes, global economic growth still has not rebounded as far or as fast as many had expected a year or two ago and remains uncertain and uneven.

In other words, the positive feedback still seems to be outrunning the negative feedback. Until that turns, the systemic processes driving (and being driven by) increased refugee flows will likely continue.

Addendum: The quote at the start of this post contains what I think is an error. A lot of the news stories on this report’s release used phrases like “displaced persons highest since World War II,” so I assumed that the U.N. report included the data on which that statement would be based. It turns out, though, that the report only makes a vague (and arguably misleading) reference to “the post-World War II era.” In fact, the U.N. does not have data to make comparisons on numbers of displaced persons prior to 1989. With the data it does have, the most the UNHCR can say is this, from p. 5: “The 2013 levels of forcible displacement were the highest since at least 1989, the first year that comprehensive statistics on global forced displacement existed.”

The picture also looks a little different from the press release if we adjust for increases in global population. Doing some rough math with the number of displaced persons in this UNHCR chart as the numerator and the U.S. Census Bureau’s mid-year estimates of world population as the denominator, here are some annual statistics on displaced persons as a share of the global population:

1989: 0.65%
1992: 0.84%
2010: 0.63%
2014: 0.72%

In no way do I mean to make light of what’s obviously a massive global problem, but as a share of the global population, the latest numbers are not (yet) even the worst since 1989, the first year for which UNHCR has comparable data.

There Is No Such Thing as Civil War

In a 2008 conference paper, Jim Fearon and David Laitin used statistics and case narratives to examine how civil wars around the world since 1955 have ended. They found that deadly fights between central governments and domestic challengers usually only end after an abrupt change in the relative fighting power of one side or the other, and that these abrupt changes are usually brought on by the beginning or end of foreign support. This pattern led them to ruminate thus (emphasis in original):

We were struck by the high frequency of militarily significant foreign support for government and rebels. The evidence suggests that more often than not, civil wars either become – or may even begin as –the object of other states’ foreign policies…Civil wars are normally studied as matters of domestic politics. Future research might make progress by shifting the perspective, and thinking about civil war as international politics by other means.

Their study recently came to mind when I was watching various people on Twitter object to the idea that what’s happening in Ukraine right now could be described as civil war, or at least the possible beginnings of one. Even if some of the separatists mobilizing in eastern Ukraine really were Ukrainian nationals, they argued, the agent provocateur was Russia, so this fight is properly understood as a foreign incursion.

As Jim and David’s paper shows, though, strong foreign hands are a common and often decisive feature of the fights we call civil wars.

In Syria, for example, numerous foreign governments and other external agents are funding, training, equipping, and arming various factions in the armed conflict that’s raged for nearly three years now. Some of that support is overt, but the support we see when we read about the war in the press is surely just a fraction of what’s actually happening. Yet we continue to see the conflict described as a civil war.

In the Central African Republic, it’s Chad that’s played “an ambiguous and powerful role” in the conflict that has precipitated state collapse and ethnic cleansing there. As the New York Times described in April,

[Chad] was accused of supporting the overthrow of the nation’s president, and then later helped remove the rebel who ousted him, making way for a new transitional government. In a statement on Thursday, the Chadian government said that its 850 soldiers had been accused of siding with Muslim militias in sectarian clashes with Christian fighters that have swept the Central African Republic for months.

At least a couple of bordering states are apparently involved in the civil war that’s stricken South Sudan since December. In a May 2014 report, the UN Mission to South Sudan asserted that government forces were receiving support from “armed groups from the Republic of Sudan,” and that “the Government has received support from the Uganda People’s Defence Force (UPDF), notably in Juba and Jonglei State.” The report also claimed that “some Darfuri militias have allied with opposition forces in the northern part of Unity State,” which borders Sudan. And, of course, there is a nearly 8,000-strong UN peacekeeping operation that is arguably shaping the scale of the violence there, even if it isn’t stopping it.

Pick a civil war—any civil war—and you’ll find similar evidence of external involvement. This is what led Jim and David to muse about civil wars as “international politics by other means,” and what led me to the deliberately provocative title of this post. As a researcher, I see analytic value in sometimes distinguishing between interstate and intrastate wars, which may have distinct causes and follow different patterns and may therefore be amenable to different forms of prevention or mitigation. At the same time, I think it’s clear that this distinction is nowhere near as crisp in reality as our labels imply, so we should be mindful to avoid confusing the typology with the reality it crudely describes.

A Useful Data Set on Political Violence that Almost No One Is Using

For the past 10 years, the CIA has overtly funded the production of a publicly available data set on certain atrocities around the world that now covers the period from January 1995 to early 2014 and is still updated on a regular basis. If you work in a relevant field but didn’t know that, you’re not alone.

The data set in question is the Political Instability Task Force’s Worldwide Atrocities Dataset, which records information from several international press sources about situations in which five or more civilians are deliberately killed in the context of some wider political conflict. Each record includes information about who did what to whom, where, and when, along with a brief text description of the event, a citation for the source article(s), and, where relevant, comments from the coder. The data are updated monthly, although those updates are posted on a four-month lag (e.g., data from January become available in May).

The decision to limit collection to events involving at least five fatalities was a pragmatic one. As the data set’s codebook notes,

We attempted at one point to lower this threshold to one and the data collection demands proved completely overwhelming, as this involved assessing every murder and ambiguous accidental death reported anywhere in the world in the international media. “Five” has no underlying theoretical justification; it merely provides a threshold above which we can confidently code all of the reported events given our available resources.

For the past three years, the data set has also fudged this rule to include targeted killings that appear to have a political motive, even when only a single victim is killed. So, for example, killings of lawyers, teachers, religious leaders, election workers, and medical personnel are nearly always recorded, and these events are distinguished from ones involving five or more victims by a “Yes” in a field identifying “Targeted Assassinations” under a “Related Tactics” header.

The data set is compiled from stories appearing in a handful of international press sources that are accessed through Factiva. It is a computer-assisted process. A Boolean keyword search is used to locate potentially relevant articles, and then human coders read those stories and make data from the ones that turn out actually to be relevant. From the beginning, the PITF data set has pulled from Reuters, Agence France Press, Associated Press, and the New York Times. Early in the process, BBC World Monitor and CNN were added to the roster, and All Africa was also added a few years ago to improve coverage of that region.

The decision to restrict collection to a relatively small number of sources was also a pragmatic one. Unlike GDELT, for example—the routine production of which is fully automated—the Atrocities Data Set is hand-coded by people reading news stories identified through a keyword search. With people doing the coding, the cost of broadening the search to local and web-based sources is prohibitive. The hope is eventually to automate the process, either as a standalone project or as part of a wider automated event data collection effort. As GDELT shows, though, that’s hard to do well, and that day hasn’t arrived yet.

Computer-assisted coding is far more labor intensive than fully automated coding, but it also carries some advantages. Human coders can still discern better than the best automated coding programs when numerous reports are all referring to the same event, so the PITF data set does a very good job eliminating duplicate records. Also, the “where” part of each record in the PITF data set includes geocoordinates, and its human coders can accurately resolve the location of nearly every event to at least the local administrative area, a task over which fully automated processes sometimes still stumble.

Of course, press reports only capture a fraction of all the atrocities that occur in most conflicts, and journalists writing about hard-to-cover conflicts often describe these situations with stories that summarize episodes of violence (e.g., “Since January, dozens of villagers have been killed…”). The PITF data set tries to accommodate this pattern by recording two distinct kinds of events: 1) incidents, which occur in a single place in short period of time, usually a single day; and 2) campaigns, which involve the same perpetrator and target group but may occur in multiple places over a longer period of time—usually days but sometimes weeks or months.

The inclusion of these campaigns alongside discrete events allows the data set to capture more information, but it also requires careful attention when using the results. Most statistical applications of data sets like this one involve cross-tabulations of events or deaths at a particular level during some period of time—say, countries and months. That’s relatively easy to do with data on discrete events located in specific places and days. Here, though, researchers have to decide ahead of time if and how they are going to blend information about the two event types. There are two basic options: 1) ignore the campaigns and focus exclusively on the incidents, treating that subset of the data set like a more traditional one and ignoring the additional information; or 2) make a convenient assumption about the distribution of the incidents of which campaigns are implicitly composed and apportion them accordingly.

For example, if we are trying to count monthly deaths from atrocities at the country level, we could assume that deaths from campaigns are distributed evenly over time and assign equal fractions of those deaths to all months over which they extend. So, a campaign in which 30 people were reportedly killed in Somalia between January and March would add 10 deaths to the monthly totals for that country in each of those three months. Alternatively, we could include all of the deaths from a campaign in the month or year in which it began. Either approach takes advantage of the additional information contained in those campaign records, but there is also a risk of double counting, as some of the events recorded as incidents might be part of the violence summarized in the campaign report.

It is also important to note that this data set does not record information about atrocities in which the United States is either the alleged perpetrator or the target (e.g., 9/11) of an atrocity because of legal restrictions on the activities of the CIA, which funds the data set’s production. This constraint presumably has a bigger impact on some cases, such as Iraq and Afghanistan, than others.

To provide a sense of what the data set contains and to make it easier for other researchers to use it, I wrote an R script that ingests and cross-tabulates the latest iteration of the data in country-month and country-year bins and then plots some of the results. That script is now posted on Github (here).

One way to see how well the data set is capturing the trends we hope it will capture is to compare the figures it produces with ones from data sets in which we already have some confidence. While I was writing this post, Colombian “data enthusiast” Miguel Olaya tweeted a pair of graphs summarizing data on massacres in that country’s long-running civil war. The data behind his graphs come from the Rutas de Conflicto project, an intensive and well-reputed effort to document as many as possible of the massacres that have occurred in Colombia since 1980. Here is a screenshot of Olaya’s graph of the annual death counts from massacres in the Rutas data set since 1995, when the PITF data pick up the story:

Annual Deaths from Massacres in Colombia by Perpetrator (Source: Rutas de Conflicta)

Annual Deaths from Massacres in Colombia by Perpetrator (Source: Rutas de Conflicta)

Now here is a graph of deaths from the incidents in the PITF data set:

deaths.yearly.colombia

Just eyeballing the two charts, the correlation looks pretty good. Both show a sharp increase in the tempo of killing in the mid-1990s; a sustained peak around 2000; a steady decline over the next several years; and a relatively low level of lethality since the mid-2000s. The annual counts from the Rutas data are two or three times larger than the ones from the PITF data during the high-intensity years, but that makes sense when we consider how much deeper of a search that project has conducted. There’s also a dip in the PITF totals in 1999 and 2000 that doesn’t appear in the Rutas data, but the comparisons over the larger span hold up. All things considered, this comparison makes the PITF data look quite good, I think.

Of course, the insurgency in Colombia has garnered better coverage from the international press than conflicts in parts of the world that are even harder to reach or less safe for correspondents than the Colombian highlands. On a couple of recent crises in exceptionally under-covered areas, the PITF data also seems to do a decent job capturing surges in violence, but only when we include campaigns as well as incidents in the counting.

The plots below show monthly death totals from a) incidents only and b) incidents and campaigns combined in the Central African Republic since 1995 and South Sudan since its independence in mid-2011. Here, deaths from campaigns have been assigned to the month in which the campaign reportedly began. In CAR, the data set identifies the upward trend in atrocities through 2013 and into 2014, but the real surge in violence that apparently began in late 2013 is only captured when we include campaigns in the cross-tabulation (the dotted line).

deaths.monthly.car

The same holds in South Sudan. There, the incident-level data available so far miss the explosion of civilian killings that began in December 2013 and reportedly continue, but the combination of campaign and incident data appears to capture a larger fraction of it, along with a notable spike in July 2013 related to clashes in Jonglei State.

deaths.monthly.southsudan

These examples suggest that the PITF Worldwide Atrocities Dataset is doing a good job at capturing trends over time in lethal violence against civilians, even in some of the hardest-to-cover cases. To my knowledge, though, this data set has not been widely used by researchers interested in atrocities or political violence more broadly. Probably its most prominent use to date was in the Model component of the Tech Challenge for Atrocities Prevention, a 2013 crowdsourced competition funded by USAID and Humanity United. That challenge produced some promising results, but it remains one of the few applications of this data set on a subject for which reliable data are scarce. Here’s hoping this post helps to rectify that.

Disclosure: I was employed by SAIC as research director of PITF from 2001 until 2011. During that time, I helped to develop the initial version of this data set and was involved in decisions to fund its continued production. Since 2011, however, I have not been involved in either the production of the data or decisions about its continued funding. I am part of a group that is trying to secure funding for a follow-on project to the Model part of the Tech Challenge for Atrocities Prevention, but that effort would not necessarily depend on this data set.

Conflict Events, Coup Forecasts, and Data Prospecting

Last week, for an upcoming post to the interim blog of the atrocities early-warning project I direct, I got to digging around in ACLED’s conflict event data for the first time. Once I had the data processed, I started wondering if they might help improve forecasts of coup attempts, too. That train of thought led to the preliminary results I’ll describe here, and to a general reminder of the often-frustrating nature of applied statistical forecasting.

ACLED is the Armed Conflict Location & Event Data Project, a U.S. Department of Defense–funded, multi-year endeavor to capture information about instances of political violence in sub-Saharan Africa from 1997 to the present.ACLED’s coders scan an array of print and broadcast sources, identifiy relevant events from them, and then record those events’ date, location, and form (battle, violence against civilians, or riots/protests); the types of actors involved; whether or not territory changed hands; and the number of fatalities that occurred. Researchers can download all of the project’s data in various formats and structures from the Data page, one of the better ones I’ve seen in political science.

I came to ACLED last week because I wanted to see if violence against civilians in Somalia had waxed, waned, or held steady in recent months. Trying to answer that question with their data meant:

  • Downloading two Excel spreadsheets, Version 4 of the data for 1997-2013 and the Realtime Data file covering (so far) the first five months of this year;
  • Processing and merging those two files, which took a little work because my software had trouble reading the original spreadsheets and the labels and formats differed a bit across them; and
  • Subsetting and summarizing the data on violence against civilians in Somalia, which also took some care because there was an extra space at the end of the relevant label in some of the records.

Once I had done these things, it was easy to generalize it to the entire data set, producing tables with monthly counts of fatalities and events by type  for all African countries over the past 13 years. And, once I had those country-month counts of conflict events, it was easy to imagine using them to try to help forecast of coup attempts in the world’s most coup-prone region. Other things being equal, variations across countries and over time in the frequency of conflict events might tell us a little more about the state of politics in those countries, and therefore where and when coup attempts are more likely to happen.

Well, in this case, it turns out they don’t tell us much more. The plot below shows ROC curves and the areas under those curves for the out-of-sample predictions from a five-fold cross-validation exercise involving a few country-month models of coup attempts. The Base Model includes: national political regime type (the categorization scheme from PITF’s global instability model applied to Polity 3d, the spell-file version); time since last change in Polity score (in days, logged); infant mortality rate (relative to the annual global median, logged); and an indicator for any coup attempts in the previous 24 months (yes/no). The three other models add logged sums of counts of ACLED events by type—battles, violence against civilians, or riots/protests—in the same country over the previous three, six, or 12 months, respectively. These are all logistic regression models, and the dependent variable is a binary one indicating whether or not any coup attempts (successful or failed) occurred in that country during that month, according to Powell and Thyne.

ROC Curves and AUC Scores from Five-Fold Cross-Validation of Coup Models Without and With ACLED Event Counts

ROC Curves and AUC Scores from Five-Fold Cross-Validation of Coup Models Without and With ACLED Event Counts

As the chart shows, adding the conflict event counts to the base model seems to buy us a smidgen more discriminatory power, but not enough to have confidence that they would routinely lead to more accurate forecasts. Intriguingly, the crossing of the ROC curves suggests that the base model, which emphasizes structural conditions, is actually a little better at identifying the most coup-prone countries. The addition of conflict event counts to the model leads to some under-prediction of coups in that high-risk set, but the balance tips the other way in countries with less structural vulnerability. In the aggregate, though, there is virtually no difference in discriminatory power between the base model and the ones that at the conflict event counts.

There are, of course, many other ways to group and slice ACLED’s data, but the rarity of coups leads me to believe that narrower cuts or alternative operationalizations aren’t likely to produce stronger predictive signals. In Africa since 1997, there are only 36 country-months with coup attempts, according to Powell and Thyne. When the events are this rare and complex and the examples this few, there’s really not much point in going beyond the most direct measures. Under these circumstances, we’re unlikely to discover finer patterns, and if we do, we probably shouldn’t have much confidence in them. There are also other models and techniques to try, but I’m dubious for the same reasons. (FWIW, I did try Random Forests and got virtually identical accuracy.)

So those are the preliminary results from this specific exercise. (The R scripts I used are on Github, here). I think those results are interesting in their own right, but the process involved in getting to them is also a great example of the often-frustrating nature of applied statistical forecasting. I spent a few hours each day for three days straight getting from the thought of exploring ACLED to the results described here. Nearly all of that time was spent processing data; only the last half-hour or so involved any modeling. As is often the case, a lot of that data-processing time was really just me staring at my monitor trying to think of another way to solve some problem I’d already tried and failed to solve.

In my experience, that kind of null result is where nearly all statistical forecasting ideas end. Even when you’re lucky enough to have the data to pursue them, few of your ideas pan out. But panning is the right metaphor, I think. Most of the work is repetitive and frustrating, but every so often you catch a nice nugget. Those nuggets tempt you to keep looking for more, and once in a great while, they can make you rich.

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