It’s a form of abuse to constantly tell someone things like “No one loves you,” “everyone hates you,” “you’re so awful, no one would ever put up with you,” etc. It’s worse, of course, if the person saying these things is someone the abused trusts, loves, or looks up to, like a parent or spouse.
What happens when someone starts to believe these sorts of lies? If they think that other people hate them or would do horrible things to them when they actually don’t? Would they come to believe that their abuser really was “they only one you can trust” and “just looking out for you”?
Every time something bad happens, they’d internalize it as yet another piece of evidence that the abuser is right: “Of course bad things happen to me–everyone hates me.” They would be afraid of the world, unable to trust anyone. How would they even begin to realize that they’ve been lied to?
It would be pretty awful if people were going around with incorrect ideas about the rates of police violence against them, too.
How many unarmed people did the police kill last year?
This is the total police killings of unarmed people, of all races, over the past 5 years. Of course, some of the “armed” people really weren’t, but we are still talking numbers similar to the number of people killed by bees and wasps each year:
As for race:
This Y-axis is seems like a case of deceptive truncation, but the total number of unarmed Africans killed by the police in 2019 was 9. This is on the same order of magnitude as “killed by lightning” and “drowned in a bucket” (don’t worry, though, if you can read this, you’re too old to fall into a bucket and drown.)
But suppose we zoom out and assume that all of the “armed” suspects shot by the police really weren’t. This is obviously not true, but it constitutes a theoretical upper bound. The police killed about 240 black people total last year. By contrast, over 3,500 people drown each year; over 7,000 black people were murdered by non-police in 2018.
Oh, and these protests are now happening in the midst of a pandemic that has been killing over a thousand people per day. Any argument that police violence is a bigger concern than corona is statistically nuts.
I’ve noticed that, aside from the WAPO article, the exact number of unarmed people shot by the police was not easy to find. Most people want to talk about rates and percentages, rather than absolute numbers. This is understandable if you are trying to figure out if one group is more likely to get killed than another, but bad for figuring out how often something actually happens and whether or not you should be worried about it.
Look, I actually have a fair number of complaints about the police/judiciary/legal system, and there are reasonable arguments about excessive force, over criminalization, and bad prison conditions that I support.
But no one should be told that there is a giant conspiracy out there to kill them when there isn’t.
Welcome back to EvX’s book club. Today we’re reading Chapter 11 of The Code Economy, Education.
…since the 1970s, the economically fortunate among us have been those who made the “go to college” choice. This group has seen its income row rapidly and its share of the aggregate wealth increase sharply. Those without a college education have watched their income stagnate and their share of the aggregate wealth decline. …
Middle-age white men without a college degree have been beset by sharply rising death rates–a phenomenon that contrasts starkly with middle-age Latino and African American men, and with trends in nearly every other country in the world.
It turns out that I have a lot of graphs on this subject. There’s a strong correlation between “white death” and “Trump support.”
White vs. non-white Americans
American whites vs. other first world nations
But “white men” doesn’t tell the complete story, as death rates for women have been increasing at about the same rate. The Great White Death seems to be as much a female phenomenon as a male one–men just started out with higher death rates in the first place.
Many of these are deaths of despair–suicide, directly or through simply giving up on living. Many involve drugs or alcohol. And many are due to diseases, like cancer and diabetes, that used to hit later in life.
We might at first think the change is just an artifact of more people going to college–perhaps there was always a sub-set of people who died young, but in the days before most people went to college, nothing distinguished them particularly from their peers. Today, with more people going to college, perhaps the destined-to-die are disproportionately concentrated among folks who didn’t make it to college. However, if this were true, we’d expect death rates to hold steady for whites overall–and they have not.
Whatever is affecting lower-class whites, it’s real.
Auerswald then discusses the “Permanent income hypothesis”, developed by Milton Friedman: Children and young adults devote their time to education, (even going into debt,) which allows us to get a better job in mid-life. When we get a job, we stop going to school and start saving for retirement. Then we retire.
The permanent income hypothesis is built into the very structure of our society, from Public Schools that serve students between the ages of 5 and 18, to Pell Grants for college students, to Social Security benefits that kick in at 65. The assumption, more or less, is that a one-time investment in education early in life will pay off for the rest of one’s life–a payout of such returns to scale that it is even sensible for students and parents to take out tremendous debt to pay for that education.
But this is dependent on that education actually paying off–and that is dependent on the skills people learn during their educations being in demand and sufficient for their jobs for the next 40 years.
The system falls apart if technology advances and thus job requirements change faster than once every 40 years. We are now looking at a world where people’s investments in education can be obsolete by the time they graduate, much less by the time they retire.
Right now, people are trying to make up for the decreasing returns to education (a highschool degree does not get you the same job today as it did in 1950) by investing more money and time into the single-use system–encouraging toddlers to go to school on the one end and poor students to take out more debt for college on the other.
This is probably a mistake, given the time-dependent nature of the problem.
The obvious solution is to change how we think of education and work. Instead of a single, one-time investment, education will have to continue after people begin working, probably in bursts. Companies will continually need to re-train workers in new technology and innovations. Education cannot be just a single investment, but a life-long process.
But that is hard to do if people are already in debt from all of the college they just paid for.
Auerswald then discusses some fascinating work by Bessen on how the industrial revolution affected incomes and production among textile workers:
… while a handloom weaver in 1800 required nearly forty minutes to weave a yard of coarse cloth using a single loom, a weaver in 1902 could do the same work operating eighteen Nothrop looms in less than a minute, on average. This striking point relates to the relative importance of the accumulation of capital to the advance of code: “Of the roughly thirty-nine-minute reduction in labor time per yard, capital accumulation due to the changing cost of capital relative to wages accounted for just 2 percent of the reduction; invention accounted for 73 percent of the reduction; and 25 percent of the time saving came from greater skill and effort of the weavers.” … “the role of capital accumulation was minimal, counter to the conventional wisdom.”
Then Auerswald proclaims:
What was the role of formal education in this process? Essentially nonexistent.
New technologies are simply too new for anyone to learn about them in school. Flexible thinkers who learn fast (generalists) thus benefit from new technologies and are crucial for their early development. Once a technology matures, however, it becomes codified into platforms and standards that can be taught, at which point demand for generalists declines and demand for workers with educational training in the specific field rises.
For Bessen, formal education and basic research are not the keys to the development of economies that they are often represented a being. What drives the development of economies is learning by doing and the advance of code–processes that are driven at least as much by non-expert tinkering as by formal research and instruction.
Make sure to read the endnotes to this chapter; several of them are very interesting. For example, #3 begins:
“Typically, new technologies demand that a large number of variables be properly controlled. Henry Bessemer’s simple principle of refining molten iron with a blast of oxygen work properly only at the right temperatures, in the right size vessel, with the right sort of vessel refractory lining, the right volume and temperature of air, and the right ores…” Furthermore, the products of these factories were really one that, in the United States, previously had been created at home, not by craftsmen…
“Early-stage technologies–those with relatively little standardized knowledge–tend to be used at a smaller scale; activity is localized; personal training and direct knowledge sharing are important, and labor markets do not compensate workers for their new skills. Mature technologies–with greater standardized knowledge–operate at large scale and globally, market permitting; formalized training and knowledge are more common; and robust labor markets encourage workers to develop their own skills.” … The intensity of of interactions that occur in cities is also important in this phase: “During the early stages, when formalized instruction is limited, person-to-person exchange is especially important for spreading knowledge.”
The ideal Head Girl is an all-rounder: performs extremely well in all school subjects and has a very high Grade Point Average. She is excellent at sports, Captaining all the major teams. She is also pretty, popular, sociable and well-behaved.
The Head Girl will probably be a big success in life…
But the Head Girl is not, cannot be, a creative genius.
Modern society is run by Head Girls, of both sexes, hence there is no place for the creative genius.
Modern Colleges aim at recruiting Head Girls, so do universities, so does science, so do the arts, so does the mass media, so does the legal profession, so does medicine, so does the military…
And in doing so, they filter-out and exclude creative genius.
Creative geniuses invent new technologies; head girls oversee the implementation and running of code. Systems that run on code can run very smoothly and do many things well, but they are bad at handling creative geniuses, as many a genius will inform you of their public school experience.
How different stages in the adoption of new technology and its codification into platforms translates into wages over time is a subject I’d like to see more of.
Auerswald then turns to the perennial problem of what happens when not only do the jobs change, they entirely disappear due to increasing robotification:
Indeed, many of the frontier business models shaping the economy today are based on enabling a sharp reduction in the number of people required to perform existing tasks.
One possibility Auerswald envisions is a kind of return to the personalized markets of yesteryear, when before massive industrial giants like Walmart sprang up. Via internet-based platforms like Uber or AirBNB, individuals can connect directly with people who’d like to buy their goods or services.
Since services make up more than 84% of the US economy and an increasingly comparable percentage in coutnries elsewhere, this is a big deal.
It’s easy to imagine this future in which we are all like some sort of digital Amish, continually networked via our phones to engage in small transactions like sewing a pair of trousers for a neighbor, mowing a lawn, selling a few dozen tacos, or driving people to the airport during a few spare hours on a Friday afternoon. It’s also easy to imagine how Walmart might still have massive economies of scale over individuals and the whole system might fail miserably.
However, if we take the entrepreneurial perspective, such enterprises are intriguing. Uber and Airbnb work by essentially “unlocking” latent assets–time when people’s cars or homes were sitting around unused. Anyone who can find other, similar latent assets and figure out how to unlock them could become similarly successful.
I’ve got an underutilized asset: rural poor. People in cities are easy to hire and easy to direct toward educational opportunities. Kids growing up in rural areas are often out of the communications loop (the internet doesn’t work terribly well in many rural areas) and have to drive a long way to job interviews.
In general, it’s tough to network large rural areas in the same ways that cities get networked.
On the matter of why peer-to-peer networks have emerged in certain industries, Auerswald makes a claim that I feel compelled to contradict:
The peer-to-peer business models in local transportation, hospitality, food service, and the rental of consumer goods were the first to emerge, not because they are the most important for the economy but because these are industries with relatively low regulatory complexity.
No no no!
Food trucks emerged because heavy regulations on restaurants (eg, fire code, disability access, landscaping,) have cut significantly into profits for restaurants housed in actual buildings.
Uber emerged because the cost of a cab medallion–that is, a license to drive a cab–hit 1.3 MILLION DOLLARS in NYC. It’s a lucrative industry that people were being kept out of.
In contrast, there has been little peer-to-peer business innovation in healthcare, energy, and education–three industries that comprise more than a quarter of the US GDP–where regulatory complexity is relatively high.
There is a ton of competition in healthcare; just look up naturopaths and chiropractors. Sure, most of them are quacks, but they’re definitely out there, competing with regular doctors for patients. (Midwives appear to be actually pretty effective at what they do and significantly cheaper than standard ob-gyns.)
The difficulty with peer-to-peer healthcare isn’t regulation but knowledge and equipment. Most Americans own a car and know how to drive, and therefore can join Uber. Most Americans do not know how to do heart surgery and do not have the proper equipment to do it with. With training I might be able to set a bone, but I don’t own an x-ray machine. And you definitely don’t want me manufacturing my own medications. I’m not even good at making soup.
Education has tons of peer-to-peer innovation. I homeschool my children. Sometimes grandma and grandpa teach the children. Many homeschoolers join consortia that offer group classes, often taught by a knowledgeable parent or hired tutor. Even people who aren’t homeschooling their kids often hire tutors, through organizations like Wyzant or afterschool test-prep centers like Kumon. One of my acquaintances makes her living primarily by skype-tutoring Koreans in English.
And that’s not even counting private schools.
Yes, if you want to set up a formal “school,” you will encounter a lot of regulation. But if you just want to teach stuff, there’s nothing stopping you except your ability to find students who’ll pay you to learn it.
Now, energy is interesting. Here Auerswsald might be correct. I have trouble imagining people setting up their own hydroelectric dams without getting into trouble with the EPA (not to mention everyone downstream.)
But what if I set up my own windmill in my backyard? Can I connect it to the electric grid and sell energy to my neighbors on a windy day? A quick search brings up WindExchange, which says, very directly:
Owners of wind turbines interconnected directly to the transmission or distribution grid, or that produce more power than the host consumes, can sell wind power as well as other generation attributes.
So, maybe you can’t set up your own nuclear reactor, and maybe the EPA has a thing about not disturbing fish, but it looks like you can sell wind and solar energy back to the grid.
I find this a rather exciting thought.
Ultimately, while Auerswald does return to and address the need to radically change how we think about education and the education-job-retirement lifepath, he doesn’t return to the increasing white death rate. Why are white death rates increasing faster than other death rates, and will transition to the “gig economy” further accelerate this trend? Or was the past simply anomalous for having low white death rates, or could these death rates be driven by something independent of the economy itself?
Now, it’s getting late, so that’s enough for tonight, but what are your thoughts? How do you think this new economy–and educational landscape–will play out?
Appalachia is a lovely geographic region of low mountains stretching from southern NY state to northeastern Mississippi; as a cultural region, “Greater Appalachia” includes all of West Virginia and Kentucky; almost all of Tennessee and Indiana; large chunks of Texas, Arkansas, Oklahoma, Missouri, Illinois, Ohio, North Carolina, and Virginia; small parts of nearby states like Alabama and Pennsylvania; and a few counties in the northwest Florida (not on the map.) (The lack of correspondence between state boundaries and Appalachia’s boundaries makes most state-level aggregated data useless and forces me to use county level data whenever possible.)
While generally considered part of “the South,” Appalachia is culturally and ethnically distinct from the “Deep South,” generally opposed secession (West Virginia seceded from Virginia following Virginia’s secession from the Union in order to return to the Union,) and never had an economy based on large, slave-owning plantations.
Appalachia is also one of the US’s persistent areas of concentrated poverty (the others are the highly black regions of the Deep South and their migrant diaspora in northern inner-cities; the Mexican region along the Texas border; and Indian reservations.) Almost 100% of the nation’s poorest counties are located in these areas; indeed, the Southern states + New Mexico as a whole are significantly poorer than the Northern ones.
First a note, though, on poverty:
There is obviously a great difference between the “poverty” of someone who chooses a low-income lifestyle in a rural part of the country because they enjoy it and are happy trading off money for pleasure, and someone who struggles to stay employed at crappy, demeaning jobs, cannot make rent, and is miserable. Farming tends not to pay as well as finance, but I don’t think anyone would be better off if all of the farmers parked their tractors and took up finance. Farmers seem pretty happy with their lives and contribute to the nation’s well-being by producing food. By contrast, I’ve yet to talk to anyone employed in fast food who enjoyed their job or wanted to stay in the industry; if they could trade for a job in finance, they’d probably take it.
Unfortunately, Appalachia (and parts of the Deep South) appear to be the most depressed states in the country. (No data for KY and NC, but I bet they match their neighbors.) Given that depression rates tend to be higher for whites than for blacks, I suspect the effect is concentrated among Southern whites, but I wouldn’t be surprised if black people in Mississippi are depressed, too.
Of course, depression itself may just be genetic, and the Scandinavian ancestors of the northern mid-west may have gifted their descendants with a uniquely chipper outlook on life, except that Scandinavians have pretty high suicide rates.
(Note also that Appalachia has higher suicide rates than the black regions of the Deep South, the Hispanic El Norte, and white regions in NY.)
The white death rate is highest in Mississippi, West Virginia, Oklahoma, Alabama, Tennessee, Arkansas, Kentucky, Nevada, and South Carolina, with the greatest increases in death rates in West Virginia and Mississippi.
I have assembled a list of articles and a few quotes discussing the increasing white death rates:
“I hang out in WV fracking country from time to time. The local community college had a 1 year program to learn how to become a “tool handler” (or something). Get your certificate, and go straight to work making $50k / year – good money is a crummy economy. The program was under-subscribed because the majority of the applicants failed the drug test.” — Jim Don Bob
“… SSDI (“disability”) culture has been deeply entrenched in West Virginia for decades, particularly in the southern coal counties where work-related injuries have historically been common…” — Chip Smith
But we will get back to death rates later. For now, given high rates of poverty, depression, suicide, and rising death rates, I’m willing to say that Appalachia sounds like it is in distress. Yes, it’s probably a drugs and obesity problem; the question is why?
The generally accepted explanation in HBD circles for Appalachian poverty is IQ–“West Virginia has an average IQ of 98”–and the personalities of its Scotch-Irish founding population. I find this inadequate. For starters, West Virginia’s average IQ of 98.7 is slightly higher than the national average. And yet West Virginia is the second poorest state in the country, with a per capita GDP of only $30,389 (in 2012 dollars.) (Only Mississippi is poorer, and Mississippi has the lowest IQ in the country.)
If IQ were the whole story, West Virginians would be making about $42,784 a year, the national average.
For that matter, Canada’s IQ is 97, Norway, Austria, Denmark, and France has IQs of 98, and Poland and Hungary are up at 99. Their respective per cap GDPs (in 2014 $s, unfortunately): $44,057, 64,856, 46,223, 44,916, 38,848, 24,745, 24,721 (but Poland and Hungary are former Soviet countries whose economies are believed to have been retarded by years of Communism.)
So IQ does not explain Appalachian poverty. But it is getting late, so I will have to continue this tomorrow.