The Neuroscience Power Crisis: What's the fallout?

The Neuroscience Power Crisis: What's the fallout?

Last week a paper ($) was published in Nature Reviews Neuroscience that is rocking the world of neuroscience. The crack team of researchers including neuroscientists, psychologists, geneticists and statisticians analysed meta-analyses of neuroscience research to determine the statistical power of the papers contained within.

The group discovered that neuroscience as a field is tremendously underpowered, meaning that most experiments are too small to be likely to find the subtle effects being looked for and the effects that are found are far more likely to be false positives than previously thought. It is likely that many theories that were previously thought to be robust might be far weaker than previously imagined. This topic by its very nature is something that is very difficult to assess on the level of any individual study, but when the field is looked at as a whole, an assessment of the statistical power across a broad spread of the literature becomes possible and this has brought worrying implications.

Something that the research only briefly touches on is that neuroscience may not be alone. Underpowered research could indeed be endemic through other sciences besides neuroscience. This may be a consequence of institutionalised failings resulting in a spread of perverse incentives such as the pressure on scientists to churn out paper after paper rather than genuinely producing quality work. This has big implications on our assumption that science is self correcting; today in certain areas this may not necessarily be the case. I sat down with Katherine Button and Marcus Munafò, a couple of the lead researcherson the project, to discuss the impact of the research. The conversation is below:

I'd like to begin by asking you if any individual low powered studies you might have stumbled upon are particularly striking to you. I'm particularly curious of low powered studies that stand out as having made an impact on the field or perhaps ones that were the most heavily spun upon release or resulted in dubious interpretations.

K: We looked at meta-analyses and didn't look directly at the individual studies which contributed to those meta-analyses. Some of the quality of the meta-analyses stood out because of unclear reporting of results; in some cases we had to work quite hard to extract the data, but because we were working at the meta level we weren't really struck by the individual studies.

M: It's probably worth taking a step back from this paper and thinking about the motivation for doing it in the first place, and the sort of things that gave rise to the motivation to write the paper. My research group is quite broad in its interests, so we do some genetic work, some human psychopharmacology work, I've worked with people on animal studies. Dating back several years, one of the consistent themes that was coming out of my research was that some effects that are apparently robust, if you read the published literature, are actually much harder to replicate than you might think. That's true across a number of different fields; for example if you look at candidate gene studies, it is now quite widely agreed that most of these are just too small to detect an effect that would be plausible, given what we know about genetic effects now. A whole literature has built up around specific associations that captured the scientific imagination, but when you look at the data either through a meta-analysis, or by trying to replicate the finding yourself, you find it's a lot more nebulous than some readings of the literature would have you believe. This was coming out as a really consistent theme. I started by doing meta-analysis as a way of identifying genetic variants robustly associated with outcomes so I could then genotype those outcomes myself, back in the day when genotyping was expensive. It proved that actually none of them was particularly robust, that was the clear finding.

I cut my teeth on meta-analytic techniques in that way and started applying the technique a bit more widely to human behavioural studies and so on, and one of the things that was really striking was that the average power in such diverse fields was really low - about 20%. That was the motivation behind looking at this more systematically and doing it in a way that would allow us to frame the problem, hopefully constructively, to an audience that might not have come across these problems in detail before. I could point at individual papers, but I'd be reluctant to, as that would say more about what I happen to have read rather than particularly problematic papers. It's a broad problem, I don't think it's about a particular field or a particular method.

K: During my PhD I looked at emotional processing in anxiety and whether processing is biased towards a certain type of emotional expressions. In a naive reading of the literature, certain things came out, like there is a strong bias for fearful faces or disgusted faces, for example, but when I tried to replicate these findings, my results didn't seem to fit. When I looked at the literature more critically, I realised that the reported effects were all over the place. I work in a medical department where there is an  emphasis of the need for more reliable methods and statistical approaches, and Marcus was one of my PhD supervisors and had investigated the problems of low power in other literatures. Applying the knowledge gained from statistical methods training to critique the emotion processing literature lead me to think that a lot of this literature is probably false-positive. I wouldn't be surprised if that was the same for other fields.

M: We tried to draw in people from a range of fields - John Ioannidis is an epidemiologist, Jonathan Flint is a psychiatric geneticist, Emma Robinson does animal model work and behavioural pharmacology, Brian Nosek is a psychologist, Kate works in a medical department, I work in a psychology department, and one of the points we try to make is that individual fields have learned some specific lessons. Clinical trials have learned about the value of pre-registration of study protocols and power analysis, genetics has learned about the importance of large scale consortial efforts, meta-analysis, stringent statistical criteria and replication. Many of those lessons could be brought together and applied more or less universally.

Can you explain the importance of meta-analyses for assessing the problem of underpowered research?


K: To work out the power that a study has to detect a true effect requires an estimation of the size of that true underlying effect. We can never really know what the true underlying effect is, so the best estimate we have is the effect size indicated by a meta-analysis, because that will be based on several studies’ attempt to measure that effect. We used the meta-analyses as a proxy for the true underlying effect and then went back and looked at the power the individual studies would have had assuming that meta-effect was actually true. That's why you have to do this meta-analytic approach, because just calculating the power an individual study has to detect the effect observed in that study is circular and meaningless in this context.

M: We really are trying to be constructive - we don't want this to be seen as a hatchet job. I think we've all made these kinds of mistakes in the past, certainly I have, and I’m sure I’ll continue to make mistakes without meaning to, but one of the advantages of this kind of project is that it’s made me think about how I can improve my own practices, such as by pre-registering study protocols.

K: And it's not just mistakes, it's also a practicality issue - resources are often limited. Yet even if you know your study is underpowered it's still useful to say that “with this sample size, we can detect an effect of this is the size”. If you are upfront about the limitations of a small sample, then at least you know what size of effects you can and can’t detect, and interpret the results accordingly.

M: And make it clear when your study is confirmatory and when your study is exploratory – that distinction, I think, is blurred at the moment; my big concern is with the incentive structures that scientists have to work within. We are incentivised to crank the handle and run smaller studies that we can get published, rather than take longer to run fewer studies that might be more authoritative but aren't going to make for as weighty a CV in the long run because, however much emphasis there is on quality, there is still an extent to which promotions and grant success are driven just by how heavy your CV is.

I'm also interested in how in your opinion neuroscience compares to psychology and other sciences more broadly in terms of the level of statistical power in published research, do you think neuroscience is an anomaly or is the problem equally prevalent across in other disciplines?

M: My sense is that wherever we've looked we've come up with the same answer. We haven't looked everywhere but there is no field that has particularly stood out as better or worse, with the possible exception of phase three clinical trials that are funded by research councils without vested interests - those tend to be quite authoritative. But again, our motivation was not that neuroscience is particularly problematic - we were trying to raise these issues with a new audience and present some of the potential solutions that have been learned in fields such as genetics and clinical trials. It was more about reaching an audience than saying this field is better or worse than other fields because my sense is this is a universal problem.

Are there any particularly urgent areas you would like to highlight where under-powered research is an issue?

K: The emotional processing and anxiety literature – only because I am familiar with it. But  I agree with Marcus’ point that these problems go across research areas and you are only familiar with them within the fields in which you work. I started off thinking that there were genuine effects to be found. There are so many studies with such conflicting evidence that you write a paper and try and say the evidence is conflicting and not very reliable, but then reviewers might say “how about so-and-so’s study?” and you  just don’t have the space in  papers to give a critique of all the methodological failings of all these studies.

M: I think there is a real distinction to be made between honest error where there are people who are trying to do a good job but they are incentivised to promote their findings and market their findings and it’s all unconscious and not malicious. There may be people who actually think of really gaming the system and don’t actually care whether or not they are right – that’s a really important distinction.

K: Something we do in my department is work with statisticians who are very careful about not overstating the claims of what we’ve found, I’ve done a few things looking at predictors of response to treatment which is effectively subgroup analysis of existing trial data and we try to be really upfront about the fact that these analyses are exploratory and that there are lots of limitations of subgroup analyses. I try to put at the forefront –‘type one and type two errors are possible and these findings need to be replicated before you believe any of them’. But as soon as you find a significant p-value, there are still a lot of reviewers that say ‘oh but this is really important for this, that or the other’ and no one wants to publish a nicely considered paper. There is a real emphasis from people saying ‘but why can’t you speculate on why this is really important and the implications this could have’ and you think that it could be important, but it could also be complete chance, so at every stage you are battling against the hyping up of your research.

M: I’ve had reviewers do this for us. In one case we were fairly transparent about presenting all our data and some of them were messy and some of them less so, and one of the reviewers said ‘just drop this stuff, it makes for a cleaner story and cleaner data if you don’t report all your data’ and we said ‘well actually we’d rather report everything and be transparent!’

K: As soon as you drop the nineteen things that didn’t come out, your one chance finding looks really amazing!

M: This is what I mean about honest error, the reviewer had no vested interest, the reviewer wasn’t trying to hype our results for us because – why would he or she? It’s just the system.

K: I think story telling is a real problem because a good story helps people to understand what your saying – it’s like when you write a blog you have to have a theme so people can follow you but there’s a balance to be struck between making your work accessible to readers but also not missing the point completely and going off on a tangent.

M: But that’s at the design stage; one of the things we are incentivised to do - wrongly in my opinion – is to include loads of measures so you’ve got a chance of finding something and then dropping all the other measures so it’s easier to tell the story. Actually what would be better is from the outset to design a study with relatively few outcomes where they all have their place and then you can write them up with all of them in there even if the results aren’t clear cut.

K: But that would require a lack of publication bias to really incentivise that, throwing all of your eggs into one basket is incentivised against really heavily. What we’ve tried to do recently when we are doing pilot studies, is writing in the protocols ‘we are going to be looking at all these different outcomes but this is our primary analysis and all these others are secondary exploratory analyses’. There are ways to report honestly and include lots of variables.

Q How big do you feel the gap is between bad science and institutionalised problems?

M: It’s not just about statistics; it takes a lot of guts as a PhD student to run the risk of having no publications at the end of your PhD.

K: It’s terrifying. Whether you get a post-doc depends on what your CV looks like.

M: I think of it as a continuum where there are very few people who are fraudulent, but then there are very few people who are perfect scientists, most of us are in the middle, where you become very invested in your ideas, there is confirmation bias, so one of the obvious things is you do an experiment as planned, you get exactly the results you expect and you think – great – and start writing it up, but if that process happens and you don’t get the results you were expecting you go back and check your data. So there can easily be a systematic difference in the amount of error checking that happens from one case to another, but in both cases there is the same likelihood that there will be errors in the data. It takes a lot of courage at the stage where you’ve run the analysis and got the results you were expecting to then go back and test them to destruction. Many scientists do this, but some don’t, not because they’re malicious but because that’s a natural psychological phenomenon – confirmation bias – you see what you are expecting to see.

Q Are there any specific bad practices that you think need to be highlighted?

M: Again, one of my main issues is with current incentive structures, which are hard for people to change from the bottom up – if you change your behaviour you are suddenly disadvantaged, relative to everyone else, in the short term. Then you have the problem that a lot of it is actually unconscious, well meant, non-malicious human instinct. Then you have the problem that when you do identify concerns there is no framework from which you say something without coming across as really hostile and confrontational – and that’s not necessarily constructive.

Many thanks to Katherine Button (@ButtonKate) and Marcus Munafò (@MarcusMunafo) for taking part in this interview. You can keep up to date with their work by following their lab’s page on Twitter.


Button KS, Ioannidis JP, Mokrysz C, Nosek BA, Flint J, Robinson ES, & Munafò MR (2013). Power failure: why small sample size undermines the reliability of neuroscience. Nature reviews Neuroscience, 14 (5), 365-76 PMID: 23571845

Image credit: Shutterstock/Feraru Nicolae

3,000-pound Triceratops skull unearthed in South Dakota

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Credit: David Schmidt / Westminster College
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Should we legalize gangs?

An unconventional solution to the problem of violence.

Credit: Brian Lundquist via Unsplash
Politics & Current Affairs

In 2007, Mexico was catching up to its northern neighbor — at least when it came to safety. Two decades of rapidly declining violence had brought the country's murder rate to within throwing distance of the United States.

Credit: INEGI and SNSP, compiled by Mexico Crime Report (

Then, quite suddenly, a war broke out. Murders more than tripled, from fewer than 9,000 in 2007 to over 27,000 in 2011. In 2018, murder hit another all-time high, with over 34,000 homicides.

This year, murder has continued to climb, with June being one of the bloodiest months since the Mexican Revolution. So far, Mexico is on course for 40,000 homicides in 2019 — more than twice as many people as died in the Syrian civil war last year.

The cause of the violence is obvious: a massive war between Mexico's cartels. But the dynamics that are fueling violence south of the U.S. border are not unique to Mexico, or even to its sophisticated, transnational drug cartels. The problem of organized criminal violence afflicts nearly every country in the Americas.

In Central America, gangs like MS-13 and Barrio 18 have fostered an epidemic of murder, extortion, and kidnapping, which is helping drive the surge of migrants seeking asylum at the U.S. border.

In the United States, battles between street gangs have recently caused murder to spike in cities like Chicago, Baltimore, and St. Louis, while notorious prison gangs, like the Mexican Mafia, Aryan Brotherhood, and Latin Kings, are effectively running the U.S. prison system. In South America, a war between rival gangs has pushed Brazil's murder rate to all-time highs.

The natural response for governments facing such violent groups is total suppression: a full-frontal assault to crush the organizations and lock up the ringleaders.

But there is a powerful argument that this strategy, while understandable, is actually responsible for making the violence worse. One country is trying a radically different approach: in 2007, Ecuador began a process of "legalizing" its street gangs, and its murder rate has fallen by 70% in the decade since.

It's easy to read too much into one anecdote from a single country, but seen in context, Ecuador's example may offer a positive contrast to the cautionary tales seen elsewhere in the hemisphere.

Mexico: Splintering Gangs, Spiraling Violence

Mexico dealt with the violence and corruption associated with drug cartels for decades. But in 2000, a major shift occurred in the country's power structure, when Mexico's Institutional Revolutionary Party (PRI) lost its 70-year stranglehold on Mexican politics.

Newly elected leaders from the conservative PAN party did not directly attack the cartels, but the power transition led to turnover among police, prosecutors, and military officials. With government loyalties shifting for the first time in decades, cartels began losing their corrupt protection arrangements with the government, destabilizing the relatively peaceful relationships of previous decades. Even while the murder rate continued to fall, cartel-associated killings grew from about 1,000 a year in 2003 to nearly 3,000 in 2007.

In 2007, newly inaugurated PAN President Felipe Calderon promised to crack down on the rising violence and crush the cartels. For the first time in its drug war, Mexico deployed tens of thousands of troops inside the country. The military was tasked with executing Calderon's "kingpin" or "decapitation" strategy, systematically killing or capturing cartel leadership to try to destabilize the groups.

Officially, this strategy is still working. Joaquin "El Chapo" Guzman, leader of the Sinaloa Cartel, was just convicted and is now facing life in an American prison, after being recaptured in 2016. The leader of the Zetas Cartel was also captured last year. Dozens of other shot-callers have been killed or imprisoned in recent years.

But rather than eliminating the cartels, this policy has simply caused them to splinter and fragment into new groups. There are now more cartels than ever, waging a bloody, multi-sided war for territory across the country. Research from the University of San Diego has tied the recapture of El Chapo, in particular, to the latest surge in violence, as gangsters fight for control of the Sinaloa Cartel and its territory.

Credit: BBC

Former President Enrique Pena Nieto, who served from 2013-2018, declared last year that the military had "won" the war against the big cartels, but admitted that "this weakening brought with it small criminal groups, without there being the capacity on the local level to effectively confront them."

In cities like Acapulco, the LA Times reports, "the cartel system has collapsed completely, with historic levels of violence being driven by dozens of warring street gangs."

The churn among senior management (and the loss of reliable partners inside the state) has caused organized crime to become disorganized — but it hasn't disappeared, and the chaos has made the violence worse than ever. With more gangs fighting over the same turf, there are exponentially more opportunities for conflict, and local police are hopelessly overwhelmed.

Supply and Demand for Gangs

The theory behind suppression strategies is that the gang itself is the problem. If we get rid of the organization — capture its leaders, disrupt recruitment, seize assets, etc. — it will crumble and evaporate, because it won't be able to sustain itself. Problem solved.

But that's almost never what actually happens. In Chicago, police tried a similar zero-tolerance approach and "decapitated" the old gangs, and the result was the same as in Mexico: smaller, less organized, and more numerous gangs, fighting a dizzyingly complex war. Chicago's violence has been difficult to quell precisely because there is nobody to call a ceasefire — or rather, there are now too many people who have to negotiate and agree on it.

Brown University economist David Skarbek isn't surprised by the failure of suppression strategies, because they are based on the same kind of mistake that has been playing out in the U.S. prison system for decades. In his book The Social Order of the Underworld: How Prison Gangs Govern the American Penal System, he argues that we have been systematically misdiagnosing why gangs exist — and so it's no wonder why our solutions keep failing.

"Gangs don't exist because there are just a lot of particularly evil people, or because there are sort of 'gang member' types, people who are inclined to be gang members," he says. Instead, paradoxically, "Gangs exist because people want more safety in a dangerous, volatile environment — and they want more regular access to contraband in illicit markets."

In other words, gangs aren't a "supply-side" problem — it's not about the group itself, it's about the social and economic dynamics that create the demand for gangs in the first place. In violent, risky situations (like overcrowded prisons), people form gangs because they need things that the authorities cannot give them (like guaranteed safety) or will not (like cell phones and illegal drugs).

To facilitate these services, gangs have also created rules to regulate the black market and resolve disputes in private. "The gangs have some pretty clear rules about when you can use violence against other prisoners. You can't just choose to assault another prisoner," Skarbek says.

In violent, risky situations, people form gangs because they need things that the authorities cannot give them.

"They'll organize a controlled setting— maybe in a cell at a time when correctional officers aren't going to be around. They'll allow interpersonal violence to take place, but they'll regulate it in a way so that it's less likely to destabilize the prisoner community."

Spontaneous, public acts of violence often lead to prison-wide lockdowns, and that interferes with the gangs' business. "They can't sell drugs or turn a profit during periods of lockdown. They have a private financial incentive to reduce large scale disruptions, large scale rioting, and so that gives them the incentive to want to govern these interactions."

"I think of (gangs) as the symptom of a disease, rather than the underlying disease itself. The underlying disease is forcing people into dangerous situations where there's insufficient resources or governance."

Skarbek has no illusions about the brutality that these gangs are willing to inflict, both inside and out of prison. "There's much to be worried about with gangs," he says. "But I think of them as the symptom of a disease, rather than the underlying disease itself. The underlying disease is forcing people into dangerous situations where there's insufficient resources or governance."

Abuela Needs a Sicario

In his book Narconomics: How to Run a Drug Cartel, the journalist Tom Wainwright tells the story of Rosa, "a barrel-shaped seventy-year-old who cannot be taller than about four feet six," who works as a maid in a suburb of Mexico City.

"In between mopping floors and making blueberry pancakes," Wainwright recounts, "she is plotting a murder."

Rosa had a problem that is increasingly common throughout Mexico: a pair of men had for years been killing, robbing, and stealing from her community with absolute impunity.

Three months ago, one of her sixteen grandchildren came home with her husband to find two burglars in the middle of ransacking their house. The robbers escaped but later came back to give the husband a vicious beating with an axe handle, as a warning not to report them. "He still walks like this," Rosa says, mimicking the awkward swing of his fractured arms.
… The police are doing nothing about all this. "Honestly, I don't trust them," Rosa says. "If the authorities don't do anything, what are we left with? One can't live like this anymore. We can't live with the fear that at any moment they can enter our house and kill us."

So Rosa and her neighbors began raising money to hire a hitman (sicario) to take out the robbers. "Rosa's story may be horrifying, but it is not as unusual as it sounds," according to Wainwright. "Many organized criminal groups provide this sort of 'protection.'"

Drug dealers, for instance, cannot go to the police if they are robbed, cheated, or attacked, and so they tend to band together to defend themselves and their market — and they aren't as patient as your average abuela.

This desperate grandmother was hardly a hardened criminal, but her case illustrates exactly the kind of incentives faced by people who find themselves in dangerous, poor, violent situations — within a prison, neighborhood, or even a country — where the formal authorities cannot or will not provide security.

Drug dealers, for instance, cannot go to the police if they are robbed, cheated, or attacked, and so they tend to band together to defend themselves and their market — and they aren't as patient as your average abuela.

Now, after years of rising insecurity, corruption, and chaos, ordinary citizens are also succumbing to the logic of gangs and forming armed groups for protection. In the Mexican state of Guerro, for example, private "self-defense groups" (effectively, vigilante gangs) have banded together into a 11,000-member paramilitary to defend their towns and fight the cartels. But this third power structure, outside both the government and the cartels, risks pouring new fuel on the conflict and further undermining the state — and, as Colombia has shown, paramilitaries are no more accountable or less susceptible to corruption than other groups.

A Different Path

Ultimately, the way to defeat gangs is to eliminate the demand for them by providing reliable security inside prisons, schools, and the community at large. This isn't easy to do, and the specifics will differ depending on the place and purpose of the gang.

Unfortunately for Mexico, there is little sign that newly inaugurated President Andrés Manuel López Obrador (also known as AMLO) is changing course. In July, he inaugurated a new 70,000-strong militarized "National Guard" to try to quell cartel violence and circumvent corruption in the army and police. The new force may provide a brief boost to security, but it won't fundamentally change the dynamics that have corrupted the local police, federales, and army before it.

Instead of hoping for a miraculous breakthrough from brute force, governments should look for ways to mitigate the worst aspects of gangs. In his wide-ranging study Making Peace in Drug Wars: Crackdowns and Cartels in Latin America, the political scientist Benjamin Lessing argues that American governments need to abandon their tough-on-crime, maximum pressure strategy toward gangs and embrace a "conditional repression" strategy.

Conditional repression means offering a deal to the gangs (whether explicitly or implicitly): "We have a ton of firepower, but on a normal day, we're not going to let it all loose on you — unless you do X, Y, or Z"— for example, killing civilians, children, or police, or having shootouts in public.

Instead of hoping for a miraculous breakthrough from brute force, governments should look for ways to mitigate the worst aspects of gangs.

Lessing argues that "brute-force repression generates incentives for cartels to fight back, while policies that condition repression on cartel violence can effectively deter cartel-state conflict."

The downside of this approach is that it tacitly admits that we are not "doing everything we can" to stop organized crime. The upside is that, because police pressure is not always 100% maxed out, there is a significant deterrent available to discourage open violence and channel cartel operations into less destructive paths.

Conditional repression tells cartel leaders that, at any given time, the police have the power to make their life much worse than it is. Maximum repression tells the cartels they have nothing to lose by attacking the state.

There is evidence from across Latin America that the government can also use this privileged position to negotiate and enforce truces between rival cartels, creating an incentive for the cartels to stop fighting each other. In 2012, the government of El Salvador (assisted by the Catholic Church) negotiated a truce between MS-13 and Barrio 18, which cut the country's murder rate in half in a single year.

Unfortunately, that truce fell apart two years later when the government minister responsible for it was removed from office. Brazil's recent surge in murder has been blamed on a gang truce from 1997 suddenly falling apart in the middle of 2016, as violence spilled from the country's dangerously overcrowded prisons into the streets.

"Brute-force repression generates incentives for cartels to fight back, while policies that condition repression on cartel violence can effectively deter cartel-state conflict."

In Ecuador, the government seems to have embarked on a more successful and durable strategy of conditional repression, and the result has been a massive reduction in violence. By 2018, the homicide rate in Ecuador was nearly as low as in the United States.

Sources: FBI, UNODC, media reports

Starting in 2007, Ecuador made a number of radical changes to its law enforcement strategy, by doubling its spending on security and launching an ambitious program of "legalization" for the country's street gangs, including notorious groups like the Latin Kings and STAE.

The program allows gang members to register with the state to receive benefits, including training and job placement. Members are not asked to give up their gang affiliation — to the contrary, the goal is to bring in current gang members and transform the gang into a more benign social group — but they are expected to abide by the conditions of the program.

According to a report by the Inter-American Development Bank (IADB), "legalized" gang members understand the deal: "Our leaders told us that we were no longer allowed to go to war… After that, you know, the government began to give us job opportunities. So, if we began to act violently again, the government would take away what they had already begun to give us, so what we did was to reciprocate the government's help (to ensure the relationship continued)."

The main benefits the gang received from "legalizing" was different treatment by the police. According to the report,

Before legalization, if the STAE (gang) got together to hold a meeting in a park, the police would inevitably arrive to arrest and physically abuse them. … Legalization was primarily a reinstatement of the right to the city… They are no longer stopped and frisked or targeted for wearing their gang colors in public spaces. Many noted that this was perhaps the biggest victory of legalization.

But another key aspect of the program was conditional on keeping the street gangs away from the cartels, which historically do not operate directly in Ecuador, but launder money and smuggle drugs through the country.

"This is one of the most important aspects of the Ecuadorian approach," the report argues. "Mano dura (the heavy hand) for cartels but inclusion towards gangs. The government actively and consciously strove to avoid gangs working for cartels (especially due to the proximity of Peru and Colombia, both major drug-trafficking hubs), hence they aggressively pursued organized crime networks while applying policies of social inclusion to street gangs."

The legalized gang members understand that the arrangement is precarious, and it could fall apart if a new president is elected. According to the IADB, their goal right now is to "institutionalize the legalization process and give it a sustainability and legitimacy that would be impervious to political shifts."

It's not clear how much of Ecuador's decline in murders is due to random factors, more and better policing, or the new strategy on gangs. No one should imagine that Ecuador's gang problem has vanished, and it would be facile to suggest that Mexico should simply import this program wholesale, applying it to criminal organizations that are very different than Ecuador's relatively small street gangs.

But at a high level, the difference in approaches is worth noting. Ecuador's policy admits that as long as there is a demand for gangs, they will continue to exist, and they must be dealt with, rather than blindly smashed. By contrast, Mexico seems determined to follow the supply-side, mano dura policies that have failed across the Americas.

In Making Peace in Drug Wars, Lessing argues for a pragmatic approach, managing the problem of criminal gangs without chasing the illusion of eliminating it overnight:

It is critical to reframe the policy problem, from eradicating drugs or crushing the cartels or punishing dastardly traffickers, to minimizing the harms produced by the drug trade… Reframing the problem ultimately implies "diplomatic recognition": accepting that as long as there is demand for drugs, there will be traffickers, and orienting repressive policy to favor the sorts of traffickers we would like to have.

That is a hard sell, especially for voters that are justly horrified and outraged by the crimes these groups have perpetrated. What Ecuador might ultimately show us is that it is possible for a democratic government to increase basic public safety, while incentivizing less bad behavior from its gangs. The results have been a rare positive example in one of the most violent regions of the world. Whether the rest of the region can learn from its example remains to be seen.

How to detect “stealth” solar storms before they destroy our society

While we can see many solar storms coming, some are "stealthy." A new study shows how to detect them.

By NASA Goddard Space Flight Center - Flickr: Magnificent CME Erupts on the Sun - August 31, CC BY 2.0,
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