Science


Reports have been filtering out recently of a study that found a relationship between US unemployment rates and deaths due to opioid use. The Washington Post reported on these results, suggesting that there is a connection between unemployment and death due to “diseases of despair” (their words), and citing the unfortunate Case and Deaton study that found increasing mortality rates among non-hispanic whites in the USA. The implication is that some kind of post-2008 economic depression-related despair has driven the white working class to drugs, with an attendant high death toll. This is particularly poignant in light of the recent election, since some of the states (like West Virginia) that voted heavily for Trump are also heavily affected by opioid abuse. The implication here is that the economic despair supposedly driving Trump voting is also driving high mortality in these communities, which have also supposedly been hollowed out by globalization, immigration and Democratic neglect (only Democrats can neglect poor white people; Republicans ride in to save them with trickle down economics while Democrats abandon them for groovy inner-city Black Lives Matter activists and funky Chicago law professors). But is any of this true?

The news reports are based on the findings of a study by Hollingsworth, Ruhm and Simon, Macroeconomic conditions and opioid abuse, published in my bete-noir, the National Bureau of Economic Research (NBER) working papers series. This is where economists publish their brain farts before they are shot down in peer review, and this paper is a typical economist brain fart. This study suffers from the usual problems of NBER papers: it has a ludicrous model, uses the wrong modeling approach, does some dubious data manipulation, and probably isn’t representative. Worse still, the study is based on a failed and useless model of drug addiction that eschews a balanced understanding of drug addiction in favour of a lazy just-so story about the causes of drug addiction that has no basis in reality. I will briefly discuss the modeling problems that make this study useless, and then discuss in more detail the problem of its underlying theoretical structure.

Modeling problems with the study

The study is a classic example of how economists just cannot handle data well. First, the authors have presented a ludicrous model which has an enormous number of explanatory variables – one for every county in their data set, one for every year, and an additional term for the combination of states and years – which means that the model has a huge number of terms to be estimated. Worse still, they do not include age or sex in the model, so they don’t adjust at all for differences in age structure between different counties and states or ethnic groups. Non-heroin opioid addiction in the USA seems to be clustered in rural whites, and probably reflects addiction pursuant to pain relief for real health problems. If so the problem is likely more prevalent in older groups (which have higher levels of chronic pain) who may well be more vulnerable to early death – so adjustment for age is important in these studies. The authors find mortality rates in whites increasing much faster than blacks or hispanics but this could well be because these groups are younger and thus earlier into their drug addiction, or simply less likely to die. This complexity is further compounded by the authors decision to impute drug types to drug-related deaths where the drug is not specified – they simply statistically estimate what drug caused the death, which makes all their results highly vulnerable to the quality of the model by which they impute 30% of all drug-related deaths. So the authors have estimated a model with a huge number of terms and have not properly adjusted for the age structure of the population. This is extremely important, since the CDC has shown that opioid-related mortality is much higher in older people, and if areas with many old people also have high unemployment there will be a spurious relationship between unemployment and mortality if age is not adjusted for.

Incidentally, this paper gives completely different crude opioid mortality rates to the CDC, probably because it uses a subset of states with unusually high mortality rates. So there is a huge generalizability problem right there.

The other big problem with the model is that, of course, being economists, the authors do not use the correct modeling approach. Opioid mortality is a rare even with very small numbers of deaths when disaggregated by race at the county level – even the authors admit that many of their data points have zero deaths – but the authors have chosen to divide the counts of mortality by the population of the area, to get crude rates, and then to model these using ordinary least squares linear regression. As I have repeatedly said here, OLS regression is completely the wrong method to use on data that is constrained. In this case the data is constrained to be greater than or equal to zero, and is likely very close to zero in most cases. OLS regression assumes a completely different probability structure to the correct method, Poisson regression, and applying OLS regression to rates means that you are assuming all zero rates have the same probability. In contrast, a Poisson regression adjusted for population size models a zero count with a different probability depending on the population size, so a zero event in a large population has a different meaning to a zero event in a small population. It also models a non-linear relationship between the underlying death rate and the unemployment rate, which is crucial to understanding how the underlying death rate is related to unemployment. By not using a Poisson regression for rare events the authors have mushed together a bunch of very different mortality patterns as if they were all the same, and completely changed the nature of the relationship between unemployment and mortality.

Big no no!

So the modeling is completely flawed, but this isn’t the worst part of this study. The worst part of this study is that the underlying theory is completely flawed.

Opioid use is not a disease of despair

The fundamental problem with this model is the assumption that macroeconomic conditions drive opioid use. Figure 1 shows the observed and modeled number of monthly deaths due to heroin overdose in New South Wales, Australia between 1995 and 2003, taken from Degenhardt and Day, Impact of the Heroin Shortage: Additional Research (I prepared this figure for this technical report).

Figure 1: Monthly observed and modeled heroin overdose deaths in New South Wales, 1995-2003

This figure shows a clear rapid peak occurring in 1999, followed by a gradual decline and then a sudden downward step in January 2001. This downward step is even more evident in heroin possession offences (Figure 2, also prepared by me, from Gilmour et al, Using intervention time series analysis to assess the effects of imperfectly identifiable natural events: A general method and example, BMC Medical Research Methodology 2006; 6:16).

Figure 2: Observed and modeled trend in heroin possession offences in New South Wales, 1995-2003

Is it really conceivable that trends in unemployment were so intense over the 8 years of this data series that they caused heroin possession offences to more than double, and heroin mortality to double, within 2 years, and to then decline by 50% before halving in one month? What are the macroeconomic effects driving this phenomenon? In fact youth unemployment in NSW declined consistently over the 1990s, and was at a historic low when heroin mortality peaked. What changed over the 1990s was the availability of heroin, which was flooding the market in the mid-1990s; and what changed in 2001 was that new models of drug interdiction and cooperation between police agencies led to unprecedented success in fighting drug traffickers, so that in the early ’00s they pulled out of Australia in favour of easier targets. The result was a sudden precipitous decline in heroin availability, a massive increase in cost, a temporary increase in street-based sex work and cocaine use, and a rapid flight of young people from the market. This occurred against a backdrop of readily available harm reduction services and widespread, free methadone treatment, to which many drug users fled when the price skyrocketed.

The reality is that drug addiction patterns are driven primarily by availability of the drug and availability of treatments for drug addiction. Far from being a “disease of despair” as the Washington Post described it, with patterns of use determined by social dislocation and poverty, heroin addiction is a disease of opportunity, driven primarily by the presence of the drug, its ease of use, and the economic potential to purchase it. There is no relationship between drug use and unemployment or poverty, and we have known this since Robin Lee did her groundbreaking work on returning heroin addicts after the Vietnam war. I suspect the truth of the American opioid epidemic is much more boring, and much more difficult to explain, than unemployment: It is a problem of availability. I don’t know what causes that problem but my guess is that sometime in the 2000s legislative changes made opioids much more easily available. In 2003 the Medicare Prescription Act was passed, and my guess is that it made it much easier for middle-aged poor people to get access to pain relief – pain relief they desperately needed for a wide array of real problems. With access to affordable opiates but with no corresponding access to specialist pain management professionals a cohort of middle-aged workers became addicted to opioids, and in the subsequent 10 years they started dying. It’s a boring health policy explanation for a terrible problem, and it can only be fixed by improvements in quality of care, access to specialists, and careful attention to modern strategies for pain relief.

Unfortunately this story doesn’t fit with a narrative – popular on left and right – of drug addiction as a disease of despair. In this narrative the left sees drug addiction as a product of an alienating and destructive society, best solved by improvements in welfare and labour rights, while the right sees drug addiction as a consequence of unemployment and poverty, which are best solved by getting everyone into work (since good welfare programs are anathema to the right). For economists both of these stories show the primacy of economics as a driver of social problems, and make a good just so story. But the reality of opioid addiction is that it is a complex health policy problem best solved by careful attention to the way that opioids are dispensed and pain is managed. True, this policy prescription requires potentially quite radical changes in the way that doctors approach chronic illness, poverty and occupational health – but it’s completely boring outside of health policy. Stories of a “generation left behind”, forced to vote for Trump because of the carnage sweeping through their blighted communities, are much more interesting than “oh yeah, we made dangerous drugs cheaper and didn’t train doctors how to manage them.”

This article and the interest it drove are another example of two pernicious problems in modern debate: economists can’t be trusted with health data, and journalists are too quick to believe economists. When this is tied with a problem that is easily amenable to sensationalism and patronizing assumptions, of course you get a narrative that is completely divorced from the truth. In this case we don’t know what the truth of the numbers is, since the economists in question made a model so bad it has no bearing on the truth; and we were led into believing that this model could ever explain the very real problems facing these communities by credulous economists and journalists all too willing to believe lazy stereotypes about drug users and drug use.

Let’s score that as another failure for two of the worst professions, and hope we can make some real changes to prescription laws and pain management so that the people affected by this problem can find better, safer ways of managing their chronic pain. And please, please please, can economists please stop touching health data until they learn a method other than OLS regression?

Save

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The New England Journal of Medicine appears to have plunged deep into the debate on health insurance reform since Trump was elected, and in its 9th March issue has a series of articles and opinion pieces on Obamacare’s effects. This includes a piece pointing out that Obamacare expanded access to treatment for substance addiction, including opioid addiction (a big and growing problem in the US at the moment) and also a research article examining the impact of the medicaid expansion on specific health and health financing outcomes (the findings: it was broadly very positive). It also has a short research article examining the claim that the individual insurance markets have been thrown into a death spiral by the poor design of the law.

This claim has been going around for about a year now, and is generally based around the fact that some insurers have left some markets, and in some cases blamed Obamacare for their decision. For example, Zero Hedge made this claim in 2015, and the National Review took it up in July 2016. Articles discussing the alleged failings of the exchanges typically point to the withdrawal of big companies such as Aetna from some exchanges, suggesting that these companies are withdrawing because the fundamental dynamic of the exchanges prevents them from making a profit. This is important in the US context because for people earning above 138% of the federal poverty line who do not have employer-based insurance, the best and most efficient way for them to get insurance coverage is through a marketplace called an exchange, which is a special clearinghouse for selecting Obamacare-compliant insurance plans that is set up either by your state or by the federal government if your state refused to cooperate with the law. (An example of a generally well-liked exchange in a Republican-run state is Kentucky’s Kynect exchange). Obamacare’s defenders have pointed out that some consolidation is natural in markets when they change, and that new entrants or changing business practices will naturally force some businesses to fail or leave – that’s capitalism! Under this defense, the exchanges are working as intended and there’s nothing to worry about, except that in some smaller states this process may lead to a collapse of competition as only one or two insurers remain – a problem Clinton intended to fix by introducing a public provider in all markets if she won the presidential election.

The new article in the NEJM explores this issue in detail, by collecting data on all the plans that operated in exchanges from 2016 – 2017 and comparing those that left with those that remained. The authors make the particular point that once the exchanges opened the marketplace itself changed, and this had implications for insurers. They say:

In particular, the ACA’s insurance-market reforms required firms to develop and market new products that were attractive to low-income Americans who faced few access and pricing restrictions based on their underlying health status.

This means that organizations that are unfamiliar with these market conditions might struggle. They explain this as follows:

Anecdotal evidence supports the argument that the skills of particular insurers may not have been well suited to these marketplaces. Many of the exiting firms, such as UnitedHealth, have primarily covered enrollees in the self-insured–employer market, in which insurers provide administrative services and are not primarily responsible for bearing actuarial risk or for developing products targeting low-income consumers. In addition, many of the assets that have proven quite valuable in the self-insured market — such as a large national footprint that is attractive to multistate employers — may not be particularly useful in state-based individual insurance marketplaces.

They then present the results of their detailed assessment of the properties of those businesses that entered or left the market place, which they summarize in a table, reproduced as Table 1 below.

Table 1: The characteristics of leavers

This table makes clear that the insurers who left the marketplace in 2016 were offering more expensive plans with narrower networks and lower levels of behavioral health coverage; they were also much more likely to be bigger actors in the market for fully-insured people and much less likely to have experience in Medicaid markets. Overall this suggests that these companies left the exchanges not because the exchanges were flawed, but because these companies were not experienced in targeting low-income Americans who make up a large share of the individual insurance market, and having made a play at the individual market decided to get out when they were out-competed by organizations with more experience in the marketplace. The authors further note that actually a lot of the insurers active in the exchange markets are making a profit and are aggressively targeting new marketplaces – but these insurers tend to be smaller organizations with experience in Medicaid services, and don’t attract the same attention as the big employer-market insurers who failed.

This study isn’t definitive and has some limitations – for example it did not compare leavers in 2016 with historical leavers before Obamacare was implemented, and it only compared silver plans (which are the most popular but not necessarily the most profitable, I guess). Nonetheless, it gives the lie to the claim that Obamacare’s exchanges are not working, or at least suggests that they are working well enough to warrant tweaks and improvements rather than complete abolition. Once again the NEJM has shown that Obamacare’s opponents are long on rhetoric and short on facts, and that although this health care law is not perfect, it is doing okay and is certainly a significant improvement on the status quo. Let’s hope that whatever reforms proceed over the next two years will lead to improvements in the areas that are not working, and not wholesale destruction of America’s best chance at universal health coverage in half a century.

(This review is a little pointless because the exhibition closes tomorrow).

Yesterday I visited the Mori Art Museum in Roppongi Hills to see the Universe and Art exhibition. This exhibition attempts to show the relationship between artists’ and scientists’ attempts to explain the cosmos and the human relationship with the stars. It incorporates artistic visions of the cosmic order, scientific explanations of space over time, and artistic interpretations of science, from many different cultural perspectives. To do this it displays a wide array of art, items, scientific objects, film and video art. These objects have been drawn from many different cultures – Indian, Asian, Europe and the Americas – over several thousand years, with a particular emphasis on Japanese material from the past and the present. They include mandalas from India and Japan, star charts from China and Japan, and early stories about space from Japan and Europe. It also includes film, photos and objects from the space programs of several nations, science fiction art and stories inspired by these programs, and visual art that either glorifies or critiques or reinterprets them. Some highlights that I particularly enjoyed are listed below.

The meteoric iron katana

Blade of coolness +5

Blade of coolness +5

What can I say? Apparently Okayoshi Kunimune made two swords from meteoric iron, which took three weeks to craft and required several trips to the local shrine for prayer. One of these is on display, and it is quite impressive. It has all the fine lines of a classically-forged katana, but the metal is kind of darker and less shiny, more sinister-looking. Also the scabbard has “Meteor sword” written on it, which just says it all really. This blade was forged the old-fashioned way in 1898, which was after the samurai era, but was forged in the traditional way, which means that it has that slight rippling pattern in the metal around the blade. Viewed end on it looks wicked sharp. The photo I took is just a snap and overstates how dark the blade is, but I do think it is darker than a normal blade (I haven’t seen many of these artifact blades so I don’t know how dark an original samurai blade is). One of these blades ended up in the possession of the Taisho Emperor, which means that he was decked out in a sword made from a meteorite. I think that makes this a kind of unique artifact and it genuinely is very cool, just sits their heavy with its own sense of foreboding awesomeness. Everyone was impressed by this sword.

Bjorn Dahlem’s Black Hole (M-Spheres)

Space!

Space!

This installation is large and imposing and when viewed in detail kind of naff – it’s just a bunch of fluorescent lights stuck onto some wood – but viewed from afar with that kind of disfocused gaze that you have to take with certain kinds of art it suddenly becomes much more imposing and abstract. In the centre is supposed to be a black hole, with what I guess are galaxies or some kind of star tracks circling around it. A single sphere of black metal somewhere in the middle is, I guess, the black hole that it all is meant to be built around. It’s surprisingly cool (though the windows at the far end of the room give a view of Tokyo from the 52nd floor of this building and are kind of more awesome in their own way). It doesn’t move or anything, unlike …

The God Machine

It watches and waits ...

It watches and waits …

This monstrosity is set up in its own room, and is basically just a series of robust metal arms circling slowly in rings of different size and speed, with brilliant lights on the arms. The lights themselves move in simple planar orbits but the whole structure is set at an angle to the floor surrounded by walls of white, and the motions of the shadows of the arms on the wall are complex, occasionally threatening, and frustratingly close to predictable. The size, clarity, depth and position of the shadows changes as the arms complete their loops, and depending on the direction you look you see a very different system of shadows interacting. A single spike sticking up from the floor casts a complex pattern of shifting triple shadows on the floor. The whole thing is a simple set of ordered moving parts, but it carries this sense of immensity and brooding threat that makes it really cool. I think it’s by Wolfgang Tillmans, who contributed a few beautiful images as well. His website gives a sense of some of his other art, which is quite striking.

The great books

Original history

Original history

The exhibition also featured first editions of Newton’s Principia, Darwin’s The Origin of the Species, and the first works of Copernicus and Kepler. Kepler and Copernicus’s books are open at centre pages so you can see the quality of their work, while the Principia is open to the frontispiece.

On the shoulders of giants ...

On the shoulders of giants …

I studied physics in my undergraduate years, and then statistics, and so for me even just the frontispiece of Newton’s original work (shown above) carries an enormous weight and power – this is truly a book of vast importance in the history of science, and to stand in front of a work that is so close to the original hand of one of science’s greatest and most influential minds is really a great privilege. This book is over 300 years old, heavy and worn with the weight of history, and everything in my career and everything I love about the science I do is built on what is in its thick and fragile pages. So it was really great to stand looking at that frontispiece and revel in the significance of of those three words: Naturalis Principia Mathematica. I imagine if one were an evolutionary biologist one would get the same feeling from Darwin’s Origin of the Species, which was also on display, but for me as someone trained in physics this book is a great treasure and it was the first (and I guess, the last) time I will be in the presence of this original piece of history.

The exhibition had other contributions from the scientists of that era, including an excerpt from da Vinci’s Codex Atlanticus that described the movement of the planets (his handwriting is incredibly beautiful, every letter a work of art), armillary spheres and beautiful navigational tools made in intricate and beautiful detail out of brass, and a replica of Gallileo’s original telescope (also, his Sedereus Nuncius and his sketches of the moon, that he made with that incredibly primitive telescope). It’s really humbling to stand in the presence of so many of the original moments of modern science, and to think that almost everything we do now depends on the work these men put into these humble books, or that once people had to find their way to Tokyo using nothing more than one of those brass navigational instruments. It’s quite incredible to see them and realize just how primitive it all was – these scientists really were fumbling around the universe, making guesses on the basis of almost nothing, when you think about what we can do today. And almost everything we can do today depends on their fumbling efforts … So it was quite amazing to see all this stuff in one exhibition, and also to see some of the wild, amusing and speculative ways in which artists of that time and since have speculated on the implications of those scientific endeavours. It’s also obvious when you see that early work that there is no barrier between science and art – those scientists were technicians but they approached their work with a religious zeal and an obvious sense of aesthetics, a joy in the beauty of maths and physics as well as in the discovery of the unknown. For all the challenges of that era, for these men it must have been a very exciting time to be alive.

The Crows and the Insects in Amber

Some of the video installations weren’t so great but there were two amazing works. The first was a high resolution high magnification video exploration of a piece of amber with insects trapped inside it. Set to eery backing music, it moved through the amber filming different parts of it in such a way that it produces spacescapes and scenes like starscapes, nebulae or distant galaxies. In between these strange galactic visuals it zoomed in or out on the insects themselves, so that they loomed in the camera like Cthulhoid monsters, alien horrors, or strange planetary landscapes. This installation was probably 4-5 minutes long (or at least the part I saw was) but it was a fascinating way to turn a piece of something ancient, terrestrial and tiny into something vast, timeless and cosmic. A brilliant idea.

The second was a video work by teamlab, Crows are Chased and the Chasing Crows are Destined to be Chased as well, Blossoming on Collision–Light in Space. For this you enter a large dark room and stand in a specific spot in the centre of the room, then the entire room begins to shift and move as the video covers all the walls, floor and ceiling. From your central spot you watch crows take flight and then you chase them along the lines of their flight, and then they burst over you and disappear and suddenly you’re chasing new ones. I don’ t know why crows, I don’t know why we’re chasing them, but it’s really good. It’s a kind of mixture of video game and interactive exhibit, I guess, but all through a movie. It probably wasn’t entirely suited to this exhibition – it could easily be the open sky rather than space that these crows are flying through – but it was still a splendid experience.

This exhibition finishes tomorrow so there is not really any point in recommending that you, dear reader(s), rush on down to see it, but at least now you know what you missed. This was a really interesting attempt to combine two fields of human endeavour that are often seen as at odds with each other or unconnected, and it did a really good job both of merging the two and also of introducing me to some genuinely cool modern artists working in this field. It also serves as a good reminder of how space exploration, from its earliest beginnings, has been not just an engineering and physics endeavour, but an artistic effort that expresses something about what it means to be human and what our position is in the cosmos. As we watch new and modern efforts to explore our solar system – and, possibly, to colonize it – it’s worth remembering that they are always about more than just science, which makes them simultaneously both a luxurious waste of money, and an essential attempt to understand the core of what it is to be human. I hope in the future other museums and art galleries will attempt a similar exhibition to this, so people outside of Japan can share this unique insight into how art and science have worked together over thousands of years to bring humans closer to the stars, both physically and spiritually.

Mushroom man on the spit!

Mushroom man on the spit!

I just finished reading episode 1 of this entertaining and weird manga, called Dungeon meshi in Japanese, by Ryoko Kui. It’s the tale of a group of adventurers – Raios the fighter, Kilchack the halfling thief, and Marshille the elven wizard – who are exploring a dungeon that is rumoured to lead to a golden kingdom that will become the domain of whichever group of adventurers kill the evil wizard who has taken it over. The story starts with them having to flee a battle with a dragon, which swallows Raios’s little sister whole. She manages to teleport the rest of the party out of the dungeon in an act of self sacrifice, and they decide that they should go back in and save her from the dragon. They could wait and resurrect her from its poo, but they decide they would rather go in, kill it and cut her out of its belly (dragon digestion is very slow). No answers are forthcoming to the question of why she can’t just teleport herself out as well, or how she will survive in a dragon’s belly, but I’m sure the reasons are clear.

Anyway, because they left all their gear and loot behind when they fled, they would need to sell their armour and weapons and downgrade in order to make enough money to buy supplies for the return trip. Also they don’t have time to go back to town and get more stuff. So they decide to go straight back into the dungeon and live on a subsistence diet of whatever they can gather and kill in the dungeon. This is particularly appealing to Raios, who has always secretly wanted to eat the creatures he kills (when he tells them this, Marshille and Kilchack decide that he’s a psychopath, but they ain’t seen nothing yet …) Off they go!

They soon run into a dwarf called Senshi who has spent 10 years exploring the dungeon and learning to cook its monsters. Raios has a book of recipes but Senshi tells him that’s all bullshit, and teaches them to cook as they go. Senshi has always wanted to eat a dragon, so he offers to join them and help in their quest. Thus begins the long process of returning to the deepest levels of the dungeon, one meal at a time …

The food chain, in the dungeon

The food chain, in the dungeon

This manga is basically a story about a series of meals, with some lip service to killing the monsters that go in the meals. It starts with a brief description of the ecology of dungeons, which sets out a nice piece of Gygaxian naturalism, along with the food pyramid suitably reimagined for mythical beasts, and gives us a tiny bit of background about the dungeon crawling industry, which is so systematized as to be almost industrial in its scope. Once we have this basic background we’re off on a mission to eat everything we can get our hands on: Mushroom men, giant scorpions, giant bats, basilisk meat and eggs, green slimes (which make excellent jerky apparently), mandrake, carnivorous plants and ultimately a kind of golem made of armour. In the process they make some discoveries about the nature of the beasts – for example, Marshille discovers that you can use giant bats to dig up mandrake and that a mandrake tastes differently depending on whether you get it to scream or not, and the golem is actually armour that has been animated by a strange colony of mollusc-like organisms that are excellent when grilled in the helmet or stir-fried with medicinal herbs.

Giant scorpion and mushroom man hot pot

Giant scorpion and mushroom man hot pot

Plus, we get recipes, which are detailed and carefully thought-out and also slightly alarming. For example, for the mushroom man and giant scorpion hot pot (pictured above) we get to see the team slicing open the body of a mushroom man, which is kind of horrific. The final meal of this issue, the walking armour, is particularly disturbing, since the crew basically sit around in a room plying mollusc flesh out of the pieces of an empty suit of armour, then grill them, except the head parts, which they cook by simply sticking the entire helmet on the bbq and waiting for them to fall out as they roast. It’s made clear that the armour is operated by an interlocking network of separate mollusc-things that have some kind of group sentience, but then once they manage to drag some out of the armour they slip them into a bowl of water and declare happily “they drowned!” Really it’s just like eating a big sentient shellfish. i.e. completely disgusting, in a disturbingly fascinating way.

Each recipe also comes with a disquisition on its nutritional benefits (and the importance of a balanced diet), along with a spider diagram showing the relative magnitude and balance of different ingredients (in the bottom right of the picture above, for example). In some cases special preparation is required – the green slime needs to be dried for several weeks, but fortunately Senshi has a special portable net for this task, and a green slime he prepared earlier which the crew can sample. In other cases, such as the basilisk, medicinal herbs of various kinds need to be included with the meal, which sadly makes it impossible for the reader to make their own roast basilisk, lacking as we do the necessary ingredients to neutralize the poison in the basilisk after we catch it. There are also tips on how to catch the ingredients – the basilisk has two heads for example but only one brain, so you can confuse it if you attack both heads at once – and some amusing biological details too. For example, it is well known that chimaera made from more than two animals are not good to eat because they don’t have a main component of their structure, while chimera of just two animals – like the basilisk – will adopt the taste and general properties of whatever their main animal is (in this case, a bird)[1].

In addition to the rather, shall we say, functional, approach to non-human creatures, the story also has some quite cynical comments on the adventuring business. During the encounter with the carnivorous plant, for example, they find a half-digested body. They feel they should return this body to the surface, but just like climbing Everest, they don’t want to go back up till they reach their goal, so instead they leave it in the path for a returning group to deal with. Realizing this might cause someone to trip, they arrange to hang it from a tree by a rope in what is, essentially, a mock execution, and then they go to sleep underneath it (Marshille, unsurprisingly, has bad dreams). To counter this cynicism Marshille acts in part as the conscience of the group, spinning on her head in rage at one point when they suggest eating something, and refusing outright to eat humanoids, but she is usually overruled and then forced to admit that yes actually this meal is quite delicious. Marshille seems to be the stand-in for the reader, since she generally expresses the disgust that the reader is likely (I hope!) to feel, and also gets things explained to her obviously for our benefit (this comes across as very man-splainy, since it’s the male fighter telling her how the world really is, but since she spends most of her time responding in apopleptic rage, it’s bearable).

Beyond its cynical but loving commentary on the world of dungeon crawling, its fine recipes and detailed exposition of dungeon ecology, this book is also a careful retelling of a staple of Japanese television entertainment – the cooking variety show. Anyone who has spent more than about a minute in Japan will have noticed that Japanese television is heavily dominated by variety shows about food, and a common format is for a group of stars and starlets to go to a remote town and sample its local delicacies. Usually this happens in rural Japan, though it can also often be seen in overseas settings, and it always involves a brief description of what is special about how the food is prepared and the ingredients obtained, and then a scene where everyone eats it and says “delicious”, and if there is a starlet involved she will be the one asking the questions while an older person (usually male) explains things to her. So this manga is an almost perfect recreation of that format, except with adventurers instead of starlets and magical creatures instead of standard ingredients. Also, the food shows usually don’t go beyond saying oishii over and over, but in the book we get more detailed expressions of the nature of the food, its texture and taste, which is just great when you’re talking about a humanoid mushroom.

Part RPG dungeon crawl, part variety show, part ecological textbook, this manga is a simple, pleasant read with an engaging story and two entertaining characters (the dwarf and the elf). It’s a really good example of the special properties of manga as a story-telling medium, since the entire idea and its execution would be almost impossible in short story or novel form, but is really well-suited to words with pictures. The pictures give it a more visceral feeling than if you were simply reading a short story about a dungeon cooking show, but the manga format gives I think more detail to the food and science descriptions than you would get in a TV drama. It’s a great balance, and an entertaining read. From a non-native Japanese perspective, it has the flaw that the kanji don’t have furigana (the hiragana writing by the side of the kanji which makes them easy to read), so it takes a while for a non-expert reader to get through, but it doesn’t have the heavy use of slang language and transliteration of rough pronunciation that you see in comics like One Piece, which makes them almost unreadable to non-experts. In general the grammar is simple and straightforward, though sometimes Senshi’s speaking style is overly complex and he uses weird words. In some manga, and especially in novels, the sentences are long and complex and very hard to read for slow readers, but here the sentences are short and straightforward, and the language is mostly standard Japanese. I found I could read in ten page blocks without too much difficulty, using a kanji lookup tool on my phone (I use an app called KanjiLookup that enables me to write them with my finger, which I’m not very good at but a lot better at now I have read this whole manga). After about 10 pages I get sick of constantly referencing the app and put the book down, but it’s not so challenging that I gave up entirely, probably because of the simple language and the short sentences and the very clear link between what is being said and what is being depicted. So as a study exercise I recommend it. As a cookbook or a moral guide, not so much …

 

 


fn1: Actually I’m pretty sure the “basilisk” in this story was actually a cockatrice.

In the modern world, progress means unemployment. Recent events in the US show that fear of the wreckage of progress is beginning to affect major political movements in the developed world, although it’s unlikely that the new champion of the mythical “white working class” is going to ease the problems they are supposed to be facing. And whatever the particular racial composition of the working classes of the developed world, it is certainly true that they are facing challenges to their economic security, both now and in the future. Furthermore, if we are to move towards a post-scarcity world these challenges are going to be a lot worse. If the developed world makes the right decisions in the next 15 years (I think we can rest assured it won’t) we could see a world of self-driving cars and vat-grown meat, powered by renewable energy from sun, sea and sky that destroys jobs in the fossil fuel sector forever. In some ways we are close to a post-scarcity society – for example, the CSIRO estimates that the Australian coast line holds 8 times the energy required to power all of Australian society – but the changes we make to get there are going to have huge economic and social impact. Beyond the job losses and their cultural impact, what does it mean for Trump’s mythical “white working class” man (it’s always a man), who drives a big pick up truck, works in a coal mine and loves steak, to lose his job in the mines and see his children eating factory-grown meat and driving automated cars?

My own father is a model example of this problem. My father left school at about 15 to start an apprenticheship as a typesetter, and aside from a brief break to work as a hydatids control officer in New Zealand, worked for 40 years as a typesetter until computers destroyed his entire industry in the late 1980s. Finally he was sacked from his job in a small Australian country town, with no severance pay or future, and forced onto unemployment benefits in his early 50s. As a result our house was repossessed, he declared bankruptcy and returned to the UK to live on unemployment benefits, leaving me to fend for myself at the age of 17. This was emblematic of the devastation that computers wrought on this industry in the 1990s, and basically an entire generation of men were driven out of work and replaced by young university graduates with computers. My understanding is that subsequent shake-ups in the industry saw it further consolidated so that the small company my father worked for was probably also extinguished, and replaced with, first, print distribution centres in the big cities, and then print-on-demand services. Now the work of probably 100 typesetters is done by just one person handling print requests from professionals using word software. For my father (and his family) nothing about this story is good, but from an economic and industrial perspective this is exactly what needed to happen, and I benefit from it all the time in the form of cheap printed books and the ease of just emailing a file to Kinko’s and getting it a day later, instead of having to deal with a cranky old bigot like my father whenever I want to print a report. Win! Except for my father and his family …

For my father, thrown onto the dole queue at 50, there was really no solution to this problem. Nobody hires 50 year old men into entry-level positions, and there was no work in his industry anymore, which was in freefall. Sure he could have tried to get work as a taxi driver or some other kind of alternative industry, but these all have barriers to access and they don’t tend to pay entry-level workers the salary they need to support a family and a mortgage. There was no gig economy in the 1990s (nor would a gig economy support the lifestyle needs of a 50 year old man with a family). Like most working class men of his era, he didn’t have the capital to set up his own business, and the only business he could have set up was in any case being systematically destroyed by the computer age. To be clear, my father tried to keep ahead of the game in his field – he wasn’t a slacker, and for example my earliest experience of computers for work was the Mac he brought home in 1988 that didn’t even have a hard drive, on which he was teaching himself to do typesetting tasks (I think he used Adobe products even then!). But staying ahead of the game doesn’t work in an industry slated for destruction, and even in an industry where he might have been able to set up consulting work opportunities the chances of success were limited. Many economists would suggest that this destructive process is liberating, freeing up people like my dad to find new opportunities – to sink or swim in the new economy – but the reality is that when you lose your job with a mortgage and family, in your fifties, in a country town, you don’t swim. You sink. Which is what my dad did, very rapidly.

If we are to move to a post-scarcity society there is going to be a lot more of this, and a lot of it will be more destructive than what I witnessed with my father. The coal death spiral is going to be fast and brutal, and the men who emerge from their last shift in those mines are not going to have alternative work, since they have no education, no skills and no other work. In my father’s case, we lived in a country town that was held up by one industry – the local lead smelter – and that too is now sinking, leaving pretty much everyone else in the town in the same situation as my father. The move to a post-scarcity society has turned that town to a wasteland, and everyone in it is going to have to sink or swim in the new economy.

But should they?

The fundamental problem here is that we are moving towards a society that doesn’t have enough work, in a society that values people only based on their labour. Cast about through the language with which political economics describes what happened to my father and you won’t find a positive term. You’ll hear about men “thrown on the scrapheap”, about “long term welfare dependency” and “cycles of poverty”. You won’t hear men like my dad described as “liberated by technology” or “freed from work”. You won’t hear about how their self-worth was improved by having time to go to flower-arranging classes, and attend to their stamp collecting duties. The only people who are respected for having lots of free time for community work are young people and rich people. Working men are expected to work. But as we move towards a post-scarcity society, what are we to do with all these people we cast into this world of negative phrases and bad stereotypes and empty futures?

In the UK/Australian framework, my father had access to welfare. This meant he lived in a trailer park, earning perhaps 10% of his income as a full-time employee, forced into humiliating rituals of job-seeking and “signing on” to get his meagre payment, even though everyone involved in constructing and managing this system – from Margaret Thatcher down – knew that he would never get another job. Everyone also knew it wasn’t his fault, but you could spend years trawling through the rhetoric of the politicians, the newspaper columnists, and hate radio, and you would never hear talk about people on unemployment because their job was destroyed by a businessman’s strategy – you only hear about dole bludgers, the undeserving poor, people who can’t be bothered to pull themselves up by their bootstraps. Into this world fell my father, proud working man, never to work again, to live on scrapings from the bottom of the government’s deficit-financed barrel.

That isn’t really right, is it?

But we’re going to see a lot more of this, so we need to start thinking about how to handle it. In particular, we need to recognize that as we abolish whole industries with sweeps of policy, we’re going to create more unemployed than we can find jobs for. We need to start talking about these people not as victims of structural readjustment, but as beneficiaries. Instead of bemoaning their fate, we need to welcome it, and treat them accordingly. Instead of telling my father he was thrown on the scrapheap, we should be saying to him, “congratulations! Technology abolished your job! The rest of your life is yours now, thanks for all your effort!” But we can’t do this if we don’t back it up with a proper respect for his material conditions. If we’re going to move to a world of infinite energy supplied by the sun, using solar panels constructed by a machine and monitored by a single guy who manages a solar farm big enough to power a city, we’re going to have to find a better way of dealing with all the coal miners and gas extractors that is better than saying “sorry!” and giving them a meagre welfare payment. So here are two proposals for how to manage the shift to a post-scarcity society, that are based in the reality of where we’re heading, rather than a behavioralist economist’s ideal of a kill-or-be-killed employment market.

  1. Accept the reality of job losses and growing unemployment: Rather than simultaneously treating structural adjustment as a disaster for workers while also demanding they get another job, any job, recognize that people done out of a job by the movement towards a world of no work are the beneficiaries of that move, and the first new citizens of the post-scarcity era. Identify industries that are obviously being destroyed – whether by offshoring, technology, or policy design – and offer specific rescue packages for the workers involved. Not stupid retraining packages based on the pretense that a 50 year old guy kicked out of the only industry he ever knew can ever work again, but real maintenance packages. Say to these men and women, “thanks for your years of work. Progress means your industry is gone, but we appreciate your efforts, and we understand this is a big change, so we’re going to support you.” Provide protection for their homes and incomes, and offer them the chance to retire early with dignity. Don’t insult them by treating them as if they were a 20-something dole-bludging surfer taking 6 months off the labour force to find the waves – offer them a real readjustment package that says “thanks, we appreciate your work, and we don’t need it any more, here’s your reward for a job well done.” Begin to build a class of post-scarcity citizens, not a class of post-adjustment wash outs.
  2. Consider education as a job, not preparation for a job: My father left school at 15 to pursue a career in an industry that was destroyed around him in a few years when he was in his 50s. But a 9 year education is not enough to get by in a modern society – this is a sacrifice he made in his youth to support an economy that changed around him. After his industry failed he spent the rest of his working-age years languishing, with nothing much to do, viewing the world through the lens of a working man with very little education. In the modern world we need as many people as possible to have the best possible education, so why not send him back to school? The government could have said “Thanks for your efforts, we realize that you left school at 15 to help society grow, and now we don’t need your work anymore and we don’t think that’s a fair exchange. Why don’t you go back to school and make up all those years you lost? And if you finish school and you’ve got the thirst for it, we’ll support you through university as well.” Of course, in many developed countries there is no actual barrier to a 50-something dude going back to lower high school – but we know they won’t do that without support, because it just doesn’t work that way. So support them, and make sure that their 40 years of contribution to society doesn’t hold them back from enjoying the same education as even the lowest surfie stoner in the modern world. And if this means that my father spends the last 15 years of his working life going all the way from lower high school to a PhD, then retires and never does anything with it, so what? Our society can afford it.

This is the reality of the modern world. We can afford so much more than we give out. The wealth my father’s efforts generated over his career would have been way more than sufficient for him to be retired 15 years early, the mortgage on his house supported by the government, and an education thrown in for free. He worked hard for some of the biggest publishing companies in the UK and Australia, massive profit makers whose role in the economy was significant. They no doubt paid (or should have paid) more than sufficient taxes to reimburse him for his labour once they no longer needed him. And if we are going to move to a world where most jobs are no longer necessary due to science, automation, or the need to abolish certain industries, we need to recognize that people like my father will be the first denizens of the brave new world we’re creating. We need to reward them, not punish them, for their service. Furthermore, we need to consider the possibility that even with the best, most perfect industry policies in the world, we will only create 1 job for every 2 we destroy – in which case we are going to be permanently increasing the size of the non-working population. So we need to start thinking about maintaining them, not as a burden on the rest of society, not as people who just won’t get a job, but as the forerunners of a society without work.

We are heading towards a society without work. The first people to experience that society are the long-term unemployed and the unemployed older workforce. If we don’t find a way to treat them as full citizens, and to ensure they can engage in society as full citizens – with accompanying salaries and bonuses – we need to realize that sometime in the future we are going to be living in a society with a very small number of wealthy workers and a very large number of poor unemployable people. Such a society is not sustainable, and in some ways, if the rhetoric about his voters is true, Trump is a sign of what will happen to us if we don’t deal with this issue.

Technology is intended to liberate us from labour. We call them labour-saving devices for a reason. But ultimately we need to recognize that once you have liberated a certain number of people from labour, you have created a new, non-working society, and you need to find a way to manage it. We want a post-scarcity society, not a post-happiness society. So let’s start thinking about ways to reward people for a lifetime of labour, rather than punishing them for picking the wrong industry 40 years ago.

 

Recently I wrote a post criticizing an article at the National Bureau of Economic Research that found a legal ivory sale in 2008 led to an increase in elephant poaching. This paper used a measure of illegal poaching called commonly the PIKE, which is measured through counting carcasses discovered in searches of designated areas. This PIKE measures the proportion of deaths that are due to illegal poaching. I argued that the paper was wrong because the PIKE has a lot of zero or potentially missing values, and is bounded between 0 to 1 but the authors used ordinary least squares (OLS) regression to model this bounded number, which creates huge problems. As a result, I wasn’t convinced by their findings.

Since then I have read a few reports related to the problem. I downloaded the data and decided to have a look at an alternative, simple way of estimating the PIKE in which the estimate of the PIKE emerges naturally from a standard Poisson regression model of mortality. This analysis better handles the large number of zeros in the data, and also the non-linear nature of death counts. I estimated a very simple model, but I think a stronger model can be developed using all the standard properties of a well-designed Poisson regression model, rather than trying to massage a model misspecification with the wrong distributional assumptions to try and get the correct answer. This is an outline of my methods and results from the most basic model.

Methods

I obtained the data of legal and illegal elephant carcasses from the Monitoring Illegal Killing of Elephants (MIKE) website. This data indicates the region, country code, site number, and number of natural deaths and illegally killed elephants at each site in each year from 2002 – 2015. I used the full data set, although for comparing with the NBER paper I also used the 2003-2013 data only. I didn’t exclude any very large death numbers as the NBER authors did.

The data set contains a column for total deaths and a column for illegal deaths. I transformed the data into a data set with two records for each site-year, so that one row was illegal killings and one was total deaths. I then defined a covariate, we will call it X, that was 0 for illegal killings and 1 for total killings. We can then define a Poisson model as follows, where Y is the count of deaths in each row of the data set (each observation):

Y~Poisson(lambda)                               (1)

ln(lambda)=alpha+beta*X                   (2)

Here I have dropped various subscripts because I’m really bad at writing maths in wordpress, but there should be an i for each observation, obviously.

This simple model can appear confounding to people who’ve been raised on only OLS regression. It has two lines and no residuals, and it also introduces the quantity lambda and the natural logarithm, which in this case we call a link function. The twiddle in the first line indicates that Y is Poisson distributed. If you check the Poisson distribution entry in Wikipedia you will see that the parameter lambda gives the average of the distribution. In this case it measures the average number of deaths in the i-th row. When we solve the model, we use a method called maximum likelihood estimation to obtain the relationship between that average number of deaths and the parameters in the second line – but taking the natural log of that average first. The Poisson distribution is able to handle values of Y (observed deaths) that are 0, even though this average parameter lambda is not 0 – and the average parameter cannot be 0 for a Poisson distribution, which means the linear equation in the second line is always defined. If you look at the example probability distributions for the Poisson distribution at Wikipedia, you will note that for small values of lambda values of 0 and 1 are very common. The Poisson distribution is designed to handle data that gives large numbers of zeros, and carefully recalibrates the estimates of lambda to suit those zeros.

It’s not how Obama would do it, but it’s the correct method.

The value X has only two values in the basic model shown above: 0 for illegal deaths, and 1 for total deaths. When X=0 equation (2) becomes

ln(lambda)=alpha              (3)

and when X=1 it becomes

ln(lambda)=alpha+beta    (4)

But when X=0 the deaths are illegal; let’s denote these by lambda_ill. When X=1 we are looking at total deaths, which we denote lambda_tot. Then for X=1 we have

ln(lambda_tot)=alpha+beta

ln(lambda_tot)-alpha=beta

ln(lambda_tot)-ln(lambda_ill)=beta     (5)

because from equation (3) we have alpha=ln(lambda_ill). Note that the average PIKE can be defined as

PIKE=lambda_ill/lambda_tot

Then, rearranging equation (5) slightly we have

ln(lambda_tot/lambda_ill)=beta

-ln(lambda_ill/lambda_tot)=beta

ln(PIKE)=-beta

So once we have used maximum likelihood estimation to solve for the value of beta, we can obtain

PIKE=exp(-beta)

as our estimate of the average PIKE, with confidence intervals.

Note that this estimate of PIKE wasn’t obtained directly by modeling it as data – it emerged organically through estimation of the average mortality counts. This method of estimating average mortality rates is absolutely 100% statistically robust, and so too is our estimate of PIKE, as it is simply an interpretation of a mathematical expression derived from a statistically robust estimation method.

We can expand this model to enable various additional estimations. We can add a time term to equation (2), but most importantly we can add a term for the ivory sale and its interaction with poaching type, which enables us to get an estimate of the effect of the sale on the average number of illegal deaths and an estimate of the effect of the sale on the average value of the PIKE. This is the model I fitted, including a time term. To estimate the basic values of the PIKE in each year I fitted a model with dummy variables for each year, the illegal/legal killing term (X) and no other terms. All models were fitted in Stata/MP 14.

Results

Figure 1 shows the average PIKE estimated from the mortality data with a simple model using dummy variables for each year and illegal/total killing term only.

Figure 1: Estimated Annual PIKE values

Figure 1: Estimated Annual PIKE values

The average PIKE before the sale was 0.43 with 95% Confidence Interval (CI) 0.40 to 0.44. Average PIKE after increased by 26%, to 0.54 (95% CI: 0.52 to 056). This isn’t a very large increase, and it should be noted that the general theory is that poaching is unsustainable when the PIKE value exceeds 0.5. The nature of this small increase can be seen in Figure 2, which plots average total and illegal carcasses over time.

Figure 2: Trend in illegal killings and total deaths

Figure 2: Trend in illegal killings and total deaths

Although numbers of illegal carcasses increased over time, so did the number of legal carcasses. After adjusting for the time trend, illegal killings appear to have increased by a factor of 2.05 (95% CI 1.95 – 2.16) after the sale, and total kills by 1.58 (95% CI 1.53 – 1.64). Note that there appears to have been a big temporary spike in 2011-2012, but my results don’t change much if the data is analyzed from only 2003-2013.

Conclusion

Using a properly-specified model to estimate the PIKE as a side-effect of a basic model of average carcass counts, I found only a 25% increase in the PIKE despite very large increases in the number of illegal carcasses observed. This increase doesn’t appear to be just the effect of time, since after adjusting for time the post-2008 step is still significant, but there are a couple of possible explanations for it, including the drought effect mentioned by the authors of the NBER paper; some kind of relationship between illegal killing and overall mortality (for example because the oldest elephants are killed and this affects survival of the whole tribe); or an increase in monitoring activity. The baseline CITES report identified a relationship between the number of person-hours devoted to searching and the number of carcasses found, and the PIKE is significantly higher in areas with easy monitoring access. It’s also possible that it is related to elephant density.

I didn’t use exactly the same data as the NBER team for this model, so it may not be directly comparable – I built this model as an example of how to properly estimate the PIKE, not to get precise estimates of the PIKE. This model still has many flaws, and a better model would use the same structure but with the following adjustments:

  • Random effects for site
  • A random effect for country
  • Incorporation of elephant populations, so that we are comparing rates rather than average carcasses. Population numbers are available in the baseline CITES report but I’m not sure if they’re still available
  • Adjustment for age. Apparently baby elephant carcasses are hard to find but poachers only kill adults. Analyzing within age groups or adjusting for age might help to identify where the highest kill rates are and their possible effect on population models
  • Adjustment for search effort and some other site-specific data (accessibility and size, perhaps)
  • Addition of rhino data to enable a difference-in-difference analysis comparing with a population that wasn’t subject to the sale

These adjustments to the model would allow adjustment for the degree of searching and intervention involved in each country, which probably affect the ability to identify carcasses. It would also enable adjustment for possible contemporaneous changes in for example search effort. I don’t know how much of this data is available, but someone should use this model to estimate PIKE and changes in mortality rates using whatever is available.

Without the correct models, estimates of the PIKE and the associated implications are impossible. OLS models may be good enough for Obama, but they aren’t going to help any elephants. Through a properly constructed and adjusted Poisson regression model, we can get statistically robust estimates of the PIKE and trends in the PIKE, and we can better understand the real effect of interventions to control poaching.

Last week’s Journal of the American Medical Association had an excellent article by Chapman et al giving a robust analysis of the effect of the change in Australia’s gun laws that happened in 1996. These laws (the National Firearms Agreement) were enacted very rapidly after a major mass shooting (the Port Arthur massacre) in which 35 people died. Their major components were banning certain kinds of weapon, and introducing a gun buyback scheme to enable gun owners to hand in their guns and be compensated, provided they did so within an amnesty period. Wikipedia describes the law changes in a short paragraph that shows how wide reaching they were:

The law, which was originally enforced by then-Prime Minister of Australia John Howard, included a number of provisions. For example, it established a temporary firearm buyback program for firearms that where once legal now made illegal, that according to the Council on Foreign Relations bought over 650,000 firearms. This program, which cost $230 million, was paid for by an increase in the country’s taxes. The law also created a national firearm registry, a 28-day waiting period for firearm sales, and tightened firearm licensing rules. The law also required anyone wishing to possess or use a firearm with some exceptions, be over the age of 12. Owners must be at least 18 years of age, have secure storage for their firearms and provide a “genuine reason” for doing so.

The laws have been partially evaluated a few times, were the subject of an excellent John Oliver piece, and have been controversial amongst pro-gun activists for some time, with much debate about whether or not they worked. One big problem with analyzing their impact is that the rate of firearm homicides was already in decline when the laws were enacted, and at the same time the rate of non-firearm suicides began to decline in a sharp turnaround from past trends. This has given a lot of room for people concerned about the laws to argue they had no impact.Chapman et al’s article provides a thorough analysis of all the available data on the laws. The analysis uses nationally-available death and population data from 1979 – 2013, so it can analyze two 17 year periods of data to look for changes in rates. It uses the correct analytical method to handle the low numbers of counts (negative binomial regression), and the models are constructed carefully to enable comparison not just of the changes in deaths that occurred at the time the laws were introduced, but to calculate changes in trends at this point in time, and to test if these trends occurred by chance. They conducted the analyses separately for firearm- and non-firearm suicides and homicides, total homicide deaths and gun homicide deaths with mass shooting-related deaths removed. Their key findings were:

    The rate of decline of firearm homicides accelerated, though this acceleration was not statistically significantThe rate of decline of firearm suicides accelerated, and this change was statistically significantThe increase in non-firearm suicides changed to a decrease, and this change was statistically significant

They conclude that there was no evidence of substitution of suicide methods due to the change in laws. Overall their findings seem to be robust, but actually there is a small flaw of interpretation and modeling in this paper that makes it, in my opinion, a missed opportunity to give a definitive answer to the question of the true effect of these laws.

Several limitations with the paper

The big problem with this paper is its failure to directly compare changes in different rates of death. They fitted separate models for the four kinds of death, when in fact they could have fitted a single model for all four kinds of death, plus time and interactions between the four kinds of death with each other, time and the laws. This model would have been slightly nasty to interpret, but would have the benefit of enabling the reader to identify any additional effect of the law on firearm homicides vs. non-firearm homicides, and firearm suicides vs. non-firearm suicides. Statistically significant terms for these parts would imply that the law had a bigger effect on firearm-related deaths than non-firearm-related deaths. This would also have the advantage of giving the model larger numbers of counts, thus reducing confidence intervals. My suspicion, just looking at the data presented in the paper, is that if this more complex model had been fit the authors would have found that the change in laws affected homicide and non-homicide deaths, and suicide and non-suicide deaths. This probably wouldn’t be as interesting a finding, but it would have been more robust.

The second big problem with the paper is that it doesn’t include a control group. I have previously written a post on this, in which I suggested using New Zealand data as a control group, since NZ is very similar to Australia but didn’t enact gun laws at that time. In that post I found that we would probably need to wait until 2023 to make a definitive conclusion on whether the gun laws prevented mass shootings. I didn’t touch so much on the homicide/suicide analyses but the same rules would apply. By using a control group we can rule out any possible cultural changes that may have happened more broadly at that time.

It’s also worth noting that the study doesn’t adjust for age. As Australia ages we expect to see the rate of homicides decline, since older people don’t shoot each other as much as the crazy young’uns, and this adjustment didn’t happen in the study. Given the conclusion about firearm homicides is primarily one based on trends, and a slowly aging society should see the effect of age through changes in trends, this was a missed opportunity. Similarly, suicide tends to happen in age groups where homicides don’t (above the 30s) and an aging society might be at higher risk of suicide, so adjusting for age might find an even bigger effect of the laws. I think it’s possible that a combination of aging society plus increasing proportions of non-white migrants[1] might explain the sudden cessation in mass shootings, especially if you treat mass shooting as an infectious disease, that is less likely to break out as the period of time between outbreaks increases.

Finally, the study doesn’t appear to have actually analyzed statistically the decline in numbers of mass shootings. Is this because the result was non-significant? It’s a strange omission…

Conclusion

This study provides better evidence than previous studies of the effect of the national firearms agreement on firearms-related deaths in Australia, but it is not conclusive. There is still a possibility that the decline in firearm homicides was non-significant, and that the effect on firearm suicides was coincidental. In the absence of a control group, and without constructing a full interaction model testing differences in trends between suicide methods, it is not possible to definitively conclude that the observed effects were due to the national firearm laws. Also, in the absence of a statistical test of the effect on mass shootings, we also cannot conclude that the national firearms agreement reduced these shootings. Nonetheless, the study provides strong evidence that the laws achieved their intended purpose. A more thorough analysis with proper interaction terms might answer this question definitively, but sadly didn’t happen in this particular paper.


fn1: This is probably a slightly controversial position but I have a suspicion – purely theorizing – that mass shootings start off as an in-group thing, they’re something that the majority population do to themselves. This appears to have historically been the case in the USA, with most shooters being white, but somehow in the last 10 years the disease broke out of this group and into non-white minorities, first Asian and then black Americans. I suspect this is unusual, and requires a long period of regular exposure to shootings by the in-group before it happens. This isn’t meant to say that any particular racial group is more prone to mass shootings than any other, just that it starts in the mainstream group and, while it remains a very rare event, remains there. So as the proportion of the population that this group fills declines, the rate of mass shootings also declines, leading to less and less social contagion both within the in-group and between the in-group and others. The exception to this is the USA, where the easy availability of guns means that there is no brake on the continued high rate of events, and eventually the infection spreads out of its main host[2].

fn2: In case it isn’t clear, I think that mass shootings should be seen as a kind of infectious process, spread by media hype, and have suggested changes in media laws to prevent this.

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