Police Shootings: How Bad Are Things?

Epistemic Status: rough, back-of-envelope

How many people are killed by police in the US? How does this compare to death rates from other causes?

In 2015, the Washington Post counted 990 Americans shot by police, the Guardian counted 1146 killed, and Fatal Encounters reported 1357, while the FBI and BJS’s 7-year average number of police killings per year were 418 and 380, respectively.

In 2012, an estimated 55,400 people were killed or hospitalized by police; 1 in 291 stops or arrests resulted in hospital-treated injury or death.  1063 suffered fatal injuries. Beatings were by far the most common cause of injury, while shooting was the most common cause of death.

I’m inclined to believe the reporters’ numbers over the FBI and BJS’s numbers, and estimate something like 1000-1500 police killings a year, and tens of thousands of police-caused hospitalizations a year.

Comparison to Total Homicides

According to the CDC, there were 15,809 homicides in America in 2014, and 2.1 million emergency room visits for assault in 2011.

This means that 5-10% of all homicides are committed by police.  3% of all severe assaults are committed by police.

There are about 765,000 police in the US. There are about 152 million men, who commit about 90% of homicides; there were 9972 male homicide perpetrators in 2010.  Thus, roughly, a policeman is 30x as likely to kill you as a randomly chosen man is.

Breakdown by Race

According to the Washington Post, 48% of people killed by police are white, while 25% were black. (The remainder were of a different or unknown race.)  This represents an overrepresentation of black people and underrepresentation of white people, since the US is 62% white and 13% black.  Black people are 2.5x as likely as white people to be killed by police.

There’s some research showing that there is no racial disparity in the rate of police killing per encounter, but researching “per encounter” rates of violence hides a lot under the rug.  If police are biased against black people, they are more likely to “encounter” them, looking for a reason to arrest them, and thus are more likely to escalate to violence. On the other hand, black people commit more crimes (per population) than white people.  Teasing out what constitutes police bias and what constitutes justifiable increased policing intensity is a tough subject.  What’s not in doubt is that the burden of police killings falls disproportionately on black people.

Comparison to Lynching

While this may seem an inflammatory comparison, a lynching, like a police killing, is an extrajudicial killing of a suspected or alleged criminal.

According to the Tuskegee Institute, the year with the highest number of lynchings, 1892, saw 61 whites lynched and 161 blacks lynched.

Given that the US population in 1892 was only about 20% of its current size, this means that, adjusted for population, about as many people are killed by police today as were lynched in the 1890s.

Looking at black people specifically, who were 12% of the US population in 1890, just as they are today, the risk of being lynched for a black person was about twice as high in the 1890s than the risk of being shot by a cop for a black person is today. Lynchings were notably more skewed towards black people than police shootings are.

Comparison to Police States

There is absolutely no comparison in magnitude between anything happening in the US criminal justice system and Stalin’s Great Purge, which killed between 600,000 and 1.2 million people, out of a population of roughly 100 million.

As we noticed with hate crimes, looking at serious problems of violence in the US can put into perspective how terrifyingly, unimaginably bad Hitler and Stalin were. Our problems are not trivial, but totalitarian regimes are…a fundamentally different kind of thing.

Augusto Pinochet had an estimated 40,018 people killed, tortured, or forcibly disappeared between 1973 and 1990, or an estimated 2354 per year, out of a population of 10-13 million.  His regime was at least 50x as deadly as US police are.

South Africa under apartheid tried and executed about 134 political prisoners between 1961 and 1989, which is not quite comparable to police killings, but is a lower rate than exists in the US.  However, South African “deaths in police custody” in 1997-2004, immediately after apartheid, averaged 434 deaths a year, while 763 people were killed by the apartheid government’s police in 1985, an unusually violent year.  Police killings in apartheid South Africa were roughly 5x as common per population as they are in the present-day US, while police killings in 1990’s South Africa were roughly 2.5x as common as they are in the present-day US.

According to a recent human rights agency’s report, 323 people have died in Egyptian prison facilities since 2013 after the recent coup, as well as 624 protesters killed.   This is comparable to the number of police killings in the US.

245 people were killed by Venezuelan security and police forces in 2015; per population, this is about twice as many as police killings in America.

Thailand’s war on drugs, which involved 2800 extrajudicial killings in the first three months after it began in 2003, is at least 10x as deadly as police in America are.

200 people died in police custody last year in Russia, about half the rate of police shootings in America per population.

The US is generally, but not always, less deadly to its citizens than typical authoritarian regimes.  The US has similar rates of death due to police as present-day South Africa, Russia, Venezuela, and Egypt.

Comparisons to other causes of death

Like all kinds of homicide, the number of police homicides pales in comparison to the number of deaths due to disease. Cancer kills more than hundreds of times as many people per year than police do. Suicide kills 30-40x as many.  Infant mortality kills more than 15 times as many.  HIV kills six times as many people.   Doctors and medical researchers are still on the front lines against death.

And prison itself probably causes quite a bit more humanitarian damage than police killings do.

However, justice matters too. An innocent person killed by police is wronged, in a way that a person who succumbs to a disease is not. Police killings count towards the vaguely defined but important category of “evidence that we don’t live in a free and just society”, in the same way that torture, detention without trial, mass surveillance, and other civil liberties violations do.

 

If Prison Were a Disease, How Bad Would It Be?

 

Epistemic status: highly uncertain

As of 2013, 2,220,300 adults were incarcerated in US state and federal prisons and county jails.

The majority of these people –about 60% — are incarcerated for nonviolent offenses such as theft, drugs, or public order violations.

How bad is this, in terms of years of life lost?  How much damage is due to being imprisoned?  (ETA: of course, in this context, I am only looking at the harms of prisons, not the benefits due to the deterrent effect of prisons, or the harms of crime. This should not be read as a claim that prison has zero deterrent effect!)

One article attempts to quantify:

African American males can expect to spend 3.09 years lifetime in prison, on average, and Hispanic and Caucasian males will spend on average 1.06 and 0.50 years, respectively.

Comparing life expectancies of people who have and have not gone to prison, as if “prison” were a disability, they compute that white males lose 19,665 person-years of life to prison per 100,000, black males lose 139,507 person-years, and Hispanic males lose 45,766 person-years.

For comparison purposes, here is a table of person-years of life lost to the most common diseases in the US.  Cancer, the top killer, only appears to cost 2882 person-years of life per 100,000.  All causes together only cost 38,211 person-years of life per 100,000.

These numbers are really weird.  They would place prison as being responsible for nearly half of all person-years of life lost.  That would be an utterly shocking result. I’m skeptical.

(ETA: it turns out that the authors of this study were looking at a stock, not a flow, of person-years lost to prison, as Ben notes below. Do not use this study’s numbers to estimate the harms of prison, they don’t make a lot of sense.)

Epidemiologist Ernest Drucker, in his book A Plague of Prisonstried to quantify the years of life lost to imprisonment for drug offenses in New York State.   He estimated a total of 360,000 years of life in prison between 1973 and 2008. This isn’t a fair comparison to diseases, though, because a year living in prison is not as bad as being dead, and prison has harms outside the time actually spent in prison.  If we were to count years in prison as “years of life lost”, however, then, given that there are roughly 19 million people in New York, drug offenses alone cost 55 person-years of life per 100,000, which is a more modest number.  

A study of the dose-response effect of years of prison on mortality found that each additional year in prison (compared to being released on parole) produced a 2-year decline in life expectancy.  For comparison purposes, smokers lose on average 11-12 years of life expectancy compared to nonsmokers.  Getting a diagnosis of colon cancer means losing about 10 years of life expectancy, while getting a diagnosis of testicular cancer means losing 1.3 years of life expectancy.

If we combine these numbers, assume each year in prison is roughly equivalent to two years of life lost, then New York State’s drug incarceration is responsible for about 110 person-years of life per 100,000, which is about half the death rate due to HIV.  This is a more believable number, though it would still make the list of the top 15 causes of death by years of life lost. But it’s only for drug incarceration, which is responsible for only about 1/5 of all incarceration.

If we look at the total number of people incarcerated in New York State, or 77,227, we get an estimated 810 person-years of life lost to prison in New York per 100,000 population, which is more than the national YLL of homicide.  And if we extrapolate to the full 2,220,300 Americans incarcerated, assume 2 years of life lost per year in prison, we get a rate of person-years of life lost due to prison per 100,000 population of 1396, which would make “prison”, if it counted as a cause of death, the sixth worst public health problem in terms of person-years of life lost.

The deadliness of prison, depending on which numbers you use, seems to range from “truly implausibly bad” to “one of the most serious public health problems in America.”

The leading causes of death among former inmates are drug overdose, cardiovascular disease, homicide, and suicide; the highest elevated risks, at 10-12x the population expected rates, were drug overdose and homicide, especially at 0-2 weeks after release. Prison puts people in more danger than they were before.

Some suggested mechanisms for why prison is so dangerous include poor conditions such as overcrowding that expose prisoners to infectious disease; violence within prisons; poor medical care inside prisons; and increased risky behaviors, due to trauma or psychological harm or lack of material opportunities for ex-cons.

For US-centric and present-day-centric utilitarian calculations, prison looks really, really bad. Reducing the prison population seems potentially important on a level comparable to working on Big Problems like cancer, heart disease, diabetes, car accidents, etc.

If nobody were imprisoned for drug crimes, then (aside from any additional risks incurred from the resulting increased drug use) the drop in incarceration alone would save more American lives than eradicating HIV from the US today.

 

 

 

Hate Crimes: A Fact Post

CW: violence, rape, murder, racism.

Epistemic status: a few days’ worth of background reading, way outside my field. This is me “showing my work” in how I orient myself, not a substitute for social science.

Since the Trump election, I’ve been concerned about what, concretely, a resurgence in racism might mean, and how likely it is.  There are people I respect saying “anything could happen” and warning us to stay vigilant and prepared to resist acts of fascist tyranny. There are also people I respect telling everyone to calm down because it’s probably not that bad.

As a grandchild of a resistance fighter against the Nazis, I was raised to believe that it can happen here, and we have to be prepared.  Part of preparation, though, is realism.  What exactly are we facing, and what kind of preparation is appropriate?  The first step is trying to assess the situation accurately.

It may seem naive to start by reviewing hate crime statistics.  The numbers probably aren’t all that accurate; and recorded hate crimes are nowhere near all the harms due to racism.  I’ll be making some attempts to deal with the first issue later in this post.  As for the second, well, this is a very primitive attempt to come to my own conclusions. I would need to be an economist with far more resources and time, in order to, say, estimate the cumulative economic damage of redlining.  For the moment, I want to do the exercise of looking at some numbers and coming to my own conclusions — not because I expect to do that better than social scientists do, but to practice original seeing, which I think is important for getting outside the sway of others’ opinions.

Why hate crime? Because racial violence is one of the concrete “bad outcomes” that we implicitly fear, when we fear a “rise in racism”.  So it makes sense to ask things like how common it is now, and how common it was in the past, or how common it is in other countries, to get a sense of the range of where things can go.

Overview

There are two major data sources in the US for information on hate crimes. One is the Department of Justice’s National Crime Victimization Survey, which is taken from a sample of about 100,000 households, and asks them detailed questions about crimes they’ve been the victims of.  The other is the FBI’s Uniform Crime Reporting database, which collects recorded crimes from police departments across the country. These sources conflict quite a bit.

The US only began recognizing “hate crime” as a legal category in the 90’s, so older information on hate crime is mostly unavailable. For (very rough) comparison purposes, I’m also going to look at statistics on lynching and on race riots, to get a sense of past levels of racial violence. I’ll also briefly compare these to contemporary Russian hate crime statistics, for an example of a country which famously has a severe problem with racial violence.

UCR Data

In 2015, there were 5850 hate crime incidents reported to the FBI by police departments.  

Of these, 36% were motivated by anti-black bias, 13% by anti-gay (male) bias, 12% by anti-white bias, 12% by anti-Jewish bias, 5% by anti-Muslim bias, 4% by anti-LGBT bias excluding gay males, and 2% by anti-Hispanic bias.

(I was surprised to see so low a rate of hate crimes against Hispanics, and so high a rate against whites.)

There were 18 murders and 13 rapes. There were 4482 crimes against persons, of which 41.3% were intimidation, 37.8% assault, and 19.7% aggravated assault.  (That is, a total of 2577 assaults.) The majority of the 2338 hate crimes directed against property were acts of vandalism.

The states with the highest number of hate crimes per capita were:

  • DC
  • Massachusetts
  • North Dakota
  • Montana
  • Kentucky

Southern states in general have lower per-capita rates of hate crime than northern states, according to the UCR; and Mississippi has a grand total of zero hate crimes reported, which is highly suspicious.  There is a serious underreporting problem with hate crimes — several major Southern cities never report hate crimes at all, such as Birmingham, Alabama; Jackson, Mississippi; and Baton Rouge, Louisiana.  So it’s quite likely that these numbers are underestimates.

The UCR has been keeping hate crime stats since 1995. Hate crime rates have been slowly declining in that period.  Anti-black hate crimes are about ⅔ their 90’s level, anti-Jewish hate crimes are about 60% of their 90’s level, anti-white hate crimes are about half, etc.

The number of anti-Muslim hate crimes spiked in 2001, from negligible to about 500, and then declined to a stable but higher-than-before level.

So, clearly, it is possible for current events to cause a spike in hate crimes.  This is a special type of a spike in hate crimes, though: Muslims may have been so small and new a population in the US that they just weren’t a habitual target of bigotry before September 11.  The September 11th hate crimes spike tells us that current events can rapidly create new targets of bigotry, even when they were largely left alone before.

NCVS Data

From 2004-2012, the rate of hate crime victimization in the population, according to the self-reports in the NCVS survey, remained steady at roughly 1 per 1000 persons 12 or older.

This would imply a much higher rate of hate crime than the UCR reports — roughly 260,000 a year — and even if we only count those crimes which survey respondents said they reported to police, that’s still 120,000.  However, according to the NCVS, only 14,380 hate crimes were confirmed by police investigators. Most reports of hate crimes do not result in the police concluding there was a hate crime.  And, of those, we might infer, only a fraction are reported to the UCR, given that the UCR’s hate crime numbers are less than half the number that the NCVS says were confirmed by police.

This low rate of police recording and police reporting is specific to hate crimes, not common across all crime.  The UCR and NCVS also include reporting on non-hate crimes like rape, robbery, aggravated assault, etc. In most of these cases, the number of crimes that the NCVS says were reported to police is comparable to the number of crimes that the UCR says were recorded by police.

Crime # (NCVS 2012) % reported to police (NCVS 2012) # recorded by police (UCR 2012) recording rate
Rape 431840 32.5 90185 0.64
Robbery 578580 60.9 327374 0.93
Aggravated assault 816760 58.4 764449 1.6
Simple assault 3179440 40 n/a n/a
Burglary 2904570 60 1579527 0.91
Motor vehicle theft 564160 83.3 707758 1.5
Theft 11142310 29 5706346 1.76
All hate crime 293790 34 6718 0.067
Violent hate crime 263540 34 4810 0.053

The one exception is hate crime, where only about 5% of hate crimes reported to police are recorded in the UCR.

That this discrepancy exists specifically in hate crimes suggests that police preferentially take hate crimes less seriously than other crimes.  And, indeed, according to the NCVS, police were more likely to take reports and make arrests in non-hate crimes vs. hate crimes.

However, the fact that there are cases where the NCVS numbers significantly undershoot the UCR numbers — giving the nonsensical result that the police record more e.g. motor vehicle thefts than victims report to police — suggests that the NCVS may have some serious sampling bias.

In the NCVS 2012 data, 52% of hate crime victims were white, 13% were black, and 30% were Latino.  This throws some doubt on the much lower rate of anti-Hispanic hate crimes in the UCR data — maybe Latinos/Hispanics are less likely to report hate crimes to the police, or less likely to be taken seriously by the police.

According to the NCVS, 16% of hate crimes were “serious violent crimes” (robbery, aggravated assault, or rape), 44% were “simple assault”, and 22% were property crime.

So How Many Hate Crimes Are There?

The unfortunate fact is that we don’t know how many hate crimes there are, because both our major data sources seem to have serious flaws.

How big a deal is hate crime, in terms of damage to human life? What are the casualty rates?

According to the NCVS,  5% of hate crimes were aggravated assault causing injury, and 10.6% were simple assault causing injury, giving roughly 32,760 injuries a year due to hate crime.

The NCVS doesn’t report murders.  The UCR’s numbers of 18 hate-crime murders a year are probably an underestimate, but also probably not as much of an underestimate as the other types of crime, since I would expect that people are more likely to report murders to the police than other crimes. There were a total of 15,809 homicides in the US in 2011.  If 0.1% of all crimes are hate crimes, as the NCVS reports, and homicide is a representative crime, then this would predict 15 hate-crime homicides a year, which is comparable to the UCR’s numbers.

My tentative order-of-magnitude estimates are that there are 10-20 hate-crime murders a year, and tens of thousands of hate-crime injuries.

Lynchings

According to the Tuskeegee Institute archives, lynchings in 1882-1968 were at most one or two hundred killings a year.

At the peak in 1892, the total number of lynchings in the US was 230, with 161 blacks and 61 whites killed.

Controlling for population growth, and comparing lynchings of black people directly to all hate-crime murders, (yes, obviously this is an imperfect comparison), this means that “hate-crime killings” were roughly 45x as common per population in the late 19th century as they are today.

The NAACP numbers claim there were 3436 people lynched between 1889 and 1922, or an average of 104 lynchings per year.

Lynchings began to decline in the 1920’s, potentially due to a variety of causes: the urbanization of the South, more active anti-lynching efforts by state police and the National Guard, the activism of the NAACP, and the attempt to pass the Dyer Anti-Lynching Bill in 1922. (It passed in the House but failed in the Senate.)

tstr21

(Image from Harry Truman’s report on civil rights.)

It’s worth noting that this is what a climate of lawless terror looks like.

It wasn’t that black people had to use a separate drinking fountain or couldn’t sit at lunch counters, or had to sit in the back of the bus.

You really must disabuse yourself of this idea. Lunch counters and buses were crucial symbolic planes of struggle that the civil rights movement used to dramatize the issue, but the main suffering in the south did not come from our inability to drink from the same fountain, ride in the front of the bus or eat lunch at Woolworth’s.

It was that white people, mostly white men, occasionally went berserk, and grabbed random black people, usually men, and lynched them. You all know about lynching. But you may forget or not know that white people also randomly beat black people, and the black people could not fight back, for fear of even worse punishment.

This constant low level dread of atavistic violence is what kept the system running. It made life miserable, stressful and terrifying for black people.

White people also occasionally tried black people, especially black men, for crimes for which they could not conceivably be guilty. With the willing participation of white women, they often accused black men of “assault,” which could be anything from rape to not taking off one’s hat, to “reckless eyeballing.”

This is going to sound awful and perhaps a stain on my late father’s memory, but when I was little, before the civil rights movement, my father taught me many, many humiliating practices in order to prevent the random, terroristic, berserk behavior of white people. The one I remember most is that when walking down the street in New York City side by side, hand in hand with my hero-father, if a white woman approached on the same sidewalk, I was to take off my hat and walk behind my father, because he had been taught in the south that black males for some reason were supposed to walk single file in the presence of any white lady.

This was just one of many humiliating practices we were taught to prevent white people from going berserk.

I remember a huge family reunion one August with my aunts and uncles and cousins gathered around my grandparents’ vast breakfast table laden with food from the farm, and the state troopers drove up to the house with a car full of rifles and shotguns, and everyone went kind of weirdly blank. They put on the masks that black people used back then to not provoke white berserkness. My strong, valiant, self-educated, articulate uncles, whom I adored, became shuffling, Step-N-Fetchits to avoid provoking the white men. Fortunately the troopers were only looking for an escaped convict. Afterward, the women, my aunts, were furious at the humiliating performance of the men, and said so, something that even a child could understand.

This is the climate of fear that Dr. King ended.

To get that experience, you only need a few dozen actual recorded lynchings per year.  The indirect impact of living under threat of violence far exceeds the literal death count.

This is what it looks like, historically, to have 45x the rate of racial violence of today.

Race Riots

For most of US history before the 1960’s, a “race riot” was racial violence by white people against nonwhite people (usually black, sometimes immigrants such as Filipinos or Mexicans).  Whole towns might be attacked and burned. In the early 20th century, these were extremely bloody: in the Tulsa race riot of 1921, whites literally bombed a black neighborhood from private airplanes, killing about 300 and forcing thousands from their homes.

While lynchings were largely a rural Southern activity, race riots were urban and nationwide.

There is no central repository of race riot casualty statistics that I could find, so I have some quick-and-dirty Internet numbers here; this is not an exhaustive list.

A return to the levels of racial violence of the 1910’s-1920’s would mean, relative to population, roughly a 50x increase in the number of “hate crime” murders compared to today. As with lynching, this is what a climate of terror looks like.

A return to the levels of racial violence of the 1960’s would constitute a roughly 5x jump, compared to the number of hate crime homicides of today. That’s what it looks like to live in what we now remember as a “turbulent” time.

Pre-1963, only 10% of race riots could be attributed to escalation by blacks. Afterwards, most race riots were still started by whites but the proportion became closer to 60/40.

Mass racial violence dissipated through the 70’s and never again reached its 60s peak, with a few exceptions such as the Rodney King riots of 1992, which killed 50 people and caused $1B in property damage.

Hate crimes in Russia

There are estimated tens of thousands of neo-Nazi skinheads in Russia. In 2008, Amnesty International estimated 85,000 neo-Nazis in Russia.  Over the past ten years, there are an average of 56 hate-crime-related deaths a year, and 378 injuries.    Source, from SOVA, a Russian think tank that studies racism and xenophobia in Russia.

Racism in Russia is most commonly directed against Africans, Central Asians, Jews, and Vietnamese. Only a few percent of the Russian population are peoples of the Caucasus, and there are only 186,000 Jews in Russia, so this is a much more intensive campaign of violence than it would be in the US; the US is about 23% nonwhite; so, conservatively, accounting for Russia’s lower total population and lower non-Russian population than the US, racial violence in Russia is maybe 31x as deadly, in terms of risk of being victimized, as it is in the US.  

Once again, this is what a climate of fear and widespread mob violence looks like. Dozens of hate-crime murders per year, more than an order of magnitude more common than hate-crime murder is in the US.

(Anti-LGBT violence is also a serious problem in Russia but we don’t seem to have good statistics on how common it is; one report says 300 attacks per year.)

Did hate crimes in the US increase post-election?

UCR and NCVS numbers come out yearly, so it’s clearly too soon to tell from those sources.

There’s allegedly a 30% jump in NYC hate crimes this year, and the NYPD has instituted a special police unit to fight the uptick.

The SPLC has set up an opportunity for people to report hate crime incidents around the election, but all those they cited were “intimidation” — verbal harassment and threats.  The most common type was anti-immigrant intimidation.  The most common locations were schools.  

Another tracking site for hate crimes reports 79 self-reported incidents of “violence”, but I noted several errors (duplicates, shootings that were apparently non-hate-related, non-violent crimes).

I think that it’s important to be watchful to see if a post-election rise in hate crimes holds up, but we don’t have enough evidence to be confident that there’s been one.

Scenario Planning

The “really bad” scenario for hate crime in the US is a rise of 30-50x in serious mob violence motivated by bigotry and tacitly condoned by the state. This, we know from historical and international evidence, feels from the inside like living in a dangerous, lawless, oppressive place.

I do not think mob violence alone will cause genocide on a much larger scale. The twenty million murders committed by the Nazis are a different, alien, unthinkable scale of operation.  I suspect you need governments for that. Governments that actively want to exterminate a population, not just keep it fearful and subordinate.  Mob violence is much more common than official campaigns of extermination, and is a more likely threat scenario.

One good thing is that it’s probably not possible to jump to 1890’s-1920’s levels of racial mob violence all at once. If that were to happen, we’d see a smaller uptick before it gets that bad.  If we’re watchful, we’ll have warning, and we may be able to counteract the problem.

The SPLC has advice on how to prevent hate crime. I’m not sure how well validated this is, but what they emphasize is community response. Churches and town councils can organize things like prayer meetings, candlelight vigils, public gatherings with marches and speeches, and other public, communal displays of support for the victims of hate crimes and refusal to tolerate hate in the community.  Forming “coalitions for tolerance” to protest hate crimes and support victims of hate can send a forceful message to hate groups that they are not welcome, and potentially prevent future crimes.

I don’t know much about this topic, but I’d probably want to read more on the psychology and dynamics of mob violence, and whether there are known techniques for defusing or preventing it. I’d very much appreciate if more knowledgeable people shared info about this.

 

 

A Return to Discussion

Epistemic Status: Casual

It’s taken me a long time to fully acknowledge this, but people who “come from the internet” are no longer a minority subculture.  Senators tweet and suburban moms post Minion memes. Which means that talking about trends in how people socialize on the internet is not a frivolous subject; it’s relevant to how people interact, period.

There seems to have been an overall drift towards social networks as opposed to blogs and forums, and in particular things like:

  • the drift of political commentary from personal blogs to “media” aggregators like The AtlanticVox, and Breitbart
  • the migration of fandom from LiveJournal to Tumblr
  • The movement of links and discussions to Facebook and Twitter as opposed to link-blogs and comment sections

At the moment I’m not empirically tracking any trends like this, and I’m not confident in what exactly the major trends are — maybe in future I’ll start looking into this more seriously. Right now, I have a sense of things from impression and hearsay.

But one thing I have noticed personally is that people have gotten intimidated by more formal and public kinds of online conversation.  I know quite a few people who used to keep a “real blog” and have become afraid to touch it, preferring instead to chat on social media.  It’s a weird kind of locus for perfectionism — nobody ever imagined that blogs were meant to be masterpieces.  But I do see people fleeing towards more ephemeral, more stream-of-consciousness types of communication, or communication that involves no words at all (reblogging, image-sharing, etc.)  There seems to be a fear of becoming too visible as a distinctive writing voice.

For one rather public and hilarious example, witness Scott Alexander’s  flight from LessWrong to LiveJournal to a personal blog to Twitter and Tumblr, in hopes that somewhere he can find a place isolated enough that nobody will notice his insight and humor. (It hasn’t been working.)

What might be going on here?

Of course, there are pragmatic concerns about reputation and preserving anonymity. People don’t want their writing to be found by judgmental bosses or family members.  But that’s always been true — and, at any rate, social networking sites are often less anonymous than forums and blogs.

It might be that people have become more afraid of trolls, or that trolling has gotten worse. Fear of being targeted by harassment or threats might make people less open and expressive.  I’ve certainly heard many writers say that they’ve shut down a lot of their internet presence out of exhaustion or literal fear.  And I’ve heard serious enough horror stories that I respect and sympathize with people who are on their guard.

But I don’t think that really explains why one would drift towards more ephemeral media. Why short-form instead of long-form?  Why streaming feeds instead of searchable archives?  Trolls are not known for their patience and rigor.  Single tweets can attract storms of trolls.  So troll-avoidance is not enough of an explanation, I think.

It’s almost as though the issue were accountability.  

A blog is almost a perfect medium for personal accountability. It belongs to you, not your employer, and not the hivemind.  The archives are easily searchable. The posts are permanently viewable. Everything embarrassing you’ve ever written is there.  If there’s a comment section, people are free to come along and poke holes in your posts. This leaves people vulnerable in a certain way. Not just to trolls, but to critics.

You can preempt embarrassment by declaring that you’re doing something shitty on purpose. That puts you in a position of safety.  You move to a space for trashy, casual, unedited talk, and you signal clearly that you don’t want to be taken seriously, in order to avoid looking pretentious and being deflated by criticism.  I think that a lot of online mannerisms, like using all-lowercase punctuation, or using really self-deprecating language, or deeply nested meta-levels of meme irony, are ways of saying “I’m cool because I’m not putting myself out there where I can be judged.  Only pompous idiots are so naive as to think their opinions are actually valuable.”

Here’s another angle on the same issue.  If you earnestly, explicitly say what you think, in essay form, and if your writing attracts attention at all, you’ll attract swarms of earnest, bright-but-not-brilliant, mostly young white male, commenters, who want to share their opinions, because (perhaps naively) they think their contributions will be welcomed. It’s basically just “oh, are we playing a game? I wanna play too!”  If you don’t want to play with them — maybe because you’re talking about a personal or highly technical topic and don’t value their input, maybe because your intention was just to talk to your friends and not the general public, whatever — you’ll find this style of interaction aversive.  You’ll read it as sealioning. Or mansplaining.  Or “well, actually”-ing.  And you’ll gravitate to forms of writing and social media where it’s clear that debate is not welcome.

I think what’s going on with these kinds of terms is something like:

Author: “Hi! I just said a thing!”

Commenter: “Ooh cool, we’re playing the Discussion game! Can I join?  Here’s my comment!”  (Or, sometimes, “Ooh cool, we’re playing the Verbal Battle game!  I wanna play! Here’s my retort!”)

Author: “Ew, no, I don’t want to play with you.”

There’s a bit of a race/gender/age/educational slant to the people playing the “commenter” role, probably because our society rewards some people more than others for playing the discussion game.  Privileged people are more likely to assume that they’re automatically welcome wherever they show up, which is why others tend to get annoyed at them and want to avoid them.

Privileged people, in other words, are more likely to think they live in a high-trust society, where they can show up to strangers and be greeted as a potential new friend, where open discussion is an important priority, where they can trust and be trusted, since everybody is playing the “let’s discuss interesting things!” game.

The unfortunate reality is that most of the world doesn’t look like that high-trust society.

On the other hand, I think the ideal of open discussion, and to some extent the past reality of internet discussion, is a lot more like a high-trust society where everyone is playing the “discuss interesting things” game, than it is like the present reality of social media.

A lot of the value generated on the 90’s and early 2000’s internet was built by people who were interested in things, sharing information about those things with like-minded individuals.  Think of the websites that were just catalogues of information about someone’s obsessions. (I remember my family happily gathering round the PC when I was a kid, to listen to all the national anthems of the world, which some helpful net denizen had collated all in one place.)  There is an enormous shared commons that is produced when people are playing the “share info about interesting stuff” game.  Wikipedia. StackExchange. It couldn’t have been motivated by pure public-spiritedness — otherwise people wouldn’t have produced so much free work.  There are ordinary, human, social motivations for this kind of engagement: the desire to show off how clever you are, the desire to be a know-it-all, the desire to correct other people — and their more positive cousins, such as obsession, fascination, and the delight of infodumping. Communication based on sharing interesting things isn’t some higher plane of civic virtue; it’s just ordinary nerd behavior.

But in ordinary nerd behavior, there are some unusual strengths.  Nerds are playing the “let’s have discussions!” game, which means that they’re unembarrassed about sharing their take on things, and unembarrassed about holding other people accountable for mistakes, and unembarrassed about being held accountable for mistakes.  It’s a sort of happy place between perfectionism and laxity.  Nobody is supposed to get everything right on the first try; but you’re supposed to respond intelligently to criticism. Things will get poked at, inevitably.  Poking is friendly behavior. (Which doesn’t mean it’s not also aggressive behavior.  Play and aggression are always intermixed.  But it doesn’t have to be understood as scary, hostile, enemy.)

The advantage of this attitude is that it’s a healthier environment for critical thinking. It’s not nearly enough to get you to a rational utopia beyond bias, of course, but it allows errors to get corrected at all, which is important in an age of abundant misinformation.  And it motivates producing interesting original content, which is how you get the raw material for a shared community knowledge repository.

Nerd-format discussions are definitely not costless. You’ll get discussions of advanced/technical topics being mobbed by clueless opinionated newbies, or discussions of deeply personal issues being overrun by clueless opinionated randos.  You’ll get endless debate over irrelevant minutiae. There are reasons why so many people flee this kind of environment.

But I would say that these disadvantages are necessary evils that, while they might be possible to mitigate somewhat, go along with having a genuinely public discourse and public accountability.

We talk a lot about social media killing privacy, but there’s also a way in which it kills publicness, by allowing people to curate their spaces by personal friend groups, and retreat from open discussions.   In a public square, any rando can ask an aristocrat to explain himself.  If people hide from public squares, they can’t be exposed to Socrates’ questions.

I suspect that, especially for people who are even minor VIPs (my level of online fame, while modest, is enough to create some of this effect), it’s tempting to become less available to the “public”, less willing to engage with strangers, even those who seem friendly and interesting.  I think it’s worth fighting this temptation.  You don’t get the gains of open discussion if you close yourself off.  You may not capture all the gains yourself, but that’s how the tragedy of the commons works; a bunch of people have to cooperate and trust if they’re going to build good stuff together.  And what that means, concretely, on the margin, is taking more time to explain yourself and engage intellectually with people who, from your perspective, look dumb, clueless, crankish, or uncool.

Some of the people I admire most, including theoretical computer scientist Scott Aaronson, are notable for taking the time to carefully debunk crackpots (and offer them the benefit of the doubt in case they are in fact correct.)  Is this activity a great ROI for a brilliant scientist, from a narrowly selfish perspective?  No. But it’s praiseworthy, because it contributes to a truly open discussion. If scientists take the time to investigate weird claims from randos, they’re doing the work of proving that science is a universal and systematic way of thinking, not just an elite club of insiders.  In the long run, it’s very important that somebody be doing that groundwork.

Talking about interesting things, with friendly strangers, in a spirit of welcoming open discussion and accountability rather than fleeing from it, seems really underappreciated today, and I think it’s time to make an explicit push towards building places online that have that quality.

In that spirit, I’d like to recommend LessWrong to my readers. For those not familiar with it, it’s a discussion forum devoted to things like cognitive science, AI, and related topics, and, back in its heyday a few years ago, it was suffused with the nerdy-discussion-nature. It had all the enthusiasm of late-night dorm-room philosophy discussions — except that some of the people you’d be having the discussions with were among the most creative people of our generation.  These days, posting and commenting is a lot sparser, and the energy is gone, but I and some other old-timers are trying to rekindle it. I’m crossposting all my blog posts there from now on, and I encourage everyone to check out and join the discussions there.

 

Industry Matters 2: Partial Retraction

Epistemic status: still tentative

Some useful comments on the last post on manufacturing have convinced me of some weaknesses in my argument.

First of all, I think I was wrong that most manufacturing job loss is due to trade. There are several economic analyses, using different methods, that come to the conclusion that a minority of manufacturing jobs are lost to trade, with most of the remainder lost to labor productivity increases.

Second of all, I want to refine my argument about productivity.

Labor productivity and multifactor productivity in manufacturing, as well as output, have grown steadily throughout the 20th century — but they are slowing down. The claim “we are making more things than ever before in America” is literally true, but there is also stagnation.

It’s also true that manufacturing employment has dropped slowly through the 70’s and 80’s until today.  This is plausibly due to improvements in labor productivity.

However, the striking, very rapid decline of manufacturing employment post-2000, in which half of all manufacturing jobs were lost in fifteen years, looks like a different phenomenon. And it does correspond temporally to a drop in output growth and productivity growth.  It also corresponds temporally to the establishment of normal trade relations with China, and there is more detailed evidence that there’s a causal link between job loss and competition with China.

My current belief is that the long-term secular decline in manufacturing employment is probably just due to the standard phenomenon where better efficiency leads to employing fewer workers in a field, the same reason that there are fewer farmers than there used to be.

However, something weird seems to have happened in 2000, something that hurt productivity growth.  It might be trade.  It might be some kind of “stickiness” effect where external shocks are hard to recover from, because there’s a lot of interdependence in industry, and if you lose one firm you might lose the whole ecosystem.  It might be some completely different thing. But I believe that there is a post-2000 phenomenon which is not adequately explained by just “higher productivity causes job loss.”

Most manufacturing job loss is due to productivity; only a minority is due to trade

David Autor‘s economic analysis concluded that trade with China contributed 16% of the US manufacturing employment decline between 1990 and 2000, 26% of the decline between 2000 and 2007, and 21% over the full period.  He came to this conclusion by looking at particular manufacturing regions in the US, looking at their exposure to Chinese imports in the local industry, and seeing how much employment declined post-2000.  Regions with more import exposure had higher job loss.

Researchers at Ball State University also concluded that trade was responsible for a minority of manufacturing job loss during the period 2000-2010: 13.4% due to trade, and 87.8% due to manufacturing productivity growth.  This was calculated using import numbers and productivity numbers from the U.S. Census and the Bureau of Labor Statistics, under the simple model that the change in employment is a linear combination of the change in domestic consumption, the change in imports, the change in exports, and the change in labor productivity.

Josh Bivens of the Economic Policy Institute, using the same model as the Ball State economists, computes that imports were responsible for 21.15% of job losses between 2000 and 2003, while productivity growth was responsible for 84.32%.

Justin Pierce and Peter Schott of the Federal Reserve Board observe that industries where the 2000 normalization of trade relations with China would have increased imports the most were those that had the most job loss. Comparing job loss in above-median impact-from-China industries vs. below-median impact-from-China industries, the difference in job loss accounts for about 29% of the drop in manufacturing employment from 2000 to 2006.

I wasn’t able to find any economic analyses that argued that trade was responsible for a majority of manufacturing job losses. It seems safe to conclude that most manufacturing job loss is due to productivity gains, not trade.

It’s also worth noting that NAFTA doesn’t seem to have cost manufacturing jobs at all.

Productivity and output are growing, but have slowed since 2000.

Real output in manufacturing is growing, and has been since the 1980’s, but there are some signs of a slowdown.

Researchers at the Economic Policy Institute claim that slowing manufacturing productivity growth and output growth around 2000 led to the sharp drop in employment.  If real value added in manufacturing had continued growing at the rate it had been in 2000, it would be 1.4x as high today.

Manufacturing output aside from computers and electronic products has been slow-growing since the 90’s.  The average annual output growth rate, 1997-2015, in manufacturing, was 12% in computers, but under 4% in all other manufacturing sectors. (The next best was motor vehicles, at 3% output growth rate.)

US motor vehicle production has been growing far more slowly than global motor vehicle production.

Here are some BLS numbers on output in selected manufacturing industries:

As an average over the time period, this growth rate represents about 2.5%-3.5% annual growth, which is roughly in line with GDP growth.  So manufacturing output growth averaged since the late 80’s isn’t unusually bad.

Labor productivity has also been rising in various industries:

However, when we look at the first and second derivatives of output and productivity, especially post-2000, the picture looks worse.

Multifactor productivity seems to have flattened in the mid-2000’s, and multifactor productivity growth has dropped sharply.  Currently, multifactor productivity is actually dropping.

Manufacturing labor productivity growth is positive, but lower than it’s been historically, at about 0.45% in 2014, and a 4-year moving average of 2.1%, compared to 3-4% growth in the 90’s.

Multifactor productivity in durable goods is down in absolute terms since about 2000 and hasn’t fully recovered.

(Multifactor productivity refers to the returns to labor and capital. If multifactor productivity isn’t growing, then while we may be investing in more capital, it’s not necessarily better capital.)

Labor productivity growth in electronics is dropping and has just become negative.

Labor productivity growth in the auto industry is staying flat at about 2%.

Manufacturing output growth has dropped very recently, post-recession, to about 0. From the 80’s to the present, it was about steady, at roughly 1%.  By contrast, global manufacturing growth is much higher: 6.5% in China, 1.9% globally.  And US GDP growth is about 2.5% on average.

In some industries, like auto parts and textiles,  raw output has dropped since 2000. (Although, arguably, these are lower-value industries and losing output there could just be a sign that the US is moving up the value chain.)

Looking back even farther, there is a slowdown in multifactor productivity growth in manufacturing, beginning in the early 70’s. Multifactor productivity grew by 1.5% annually from 1949-1973, and only by 0.3% in 1973-1983.  Multifactor productivity growth today isn’t clearly unprecedentedly low, but it’s dropping to the levels of stagnation we saw in the 1970’s, or even below.

Basically, recent labor productivity is positive but not growing and in some cases dropping; output is growing slower than GDP; and multifactor productivity is dropping. This points to there being something to worry about.

What might be going on?

Economist Jared Bernstein argues that automation doesn’t explain the whole story of manufacturing job loss. If you exclude the computer industry, manufacturing output is only about 8% higher than it was in 1997, and lower than it was before the Great Recession.  The growth in manufacturing output has been “anemic.”  He says that factory closures have large spillover effects. Shocks like the rise of China, or a global glut of steel in the 1980’s, lead to US factory closures; and then when demand recovers, the US industries don’t.

This model also fits with the fact that proximity matters a lot.  It’s valuable, for knowledge-transfer reasons, to build factories near suppliers.  So if parts manufacturing moves overseas, the factories that assemble those parts are likely to relocate as well. It’s also valuable, due to shipping costs, to locate manufacturing near to expensive-to-ship materials like steel or petroleum.  And, also as a result of shipping costs, it’s valuable to locate manufacturing in places with good transportation infrastructure. So there can be stickiness/spillover effects, where, once global trade makes it cheaper to make parts and raw materials in China, there’s incentives pushing higher-value manufacturing to relocate there as well.

It doesn’t seem to be entirely coincidence that the productivity slowdown coincided with the opening of trade with China. The industries where employment dropped most after 2000 were those where the risk of tariffs on Chinese goods dropped the most.

However, this story is still consistent with the true claim that most lost manufacturing jobs are lost to productivity, not trade. Multifactor productivity may be down and output and labor productivity may be slowing, but output is still growing, and that growth is still big enough to drive most job loss.

Vestibular Stimulation and Fat Loss

It is a strange but well replicated fact, that if you leave small animals in a centrifuge for a really long time, they lose a lot of fat.  Many of these experiments were done in the 1960’s and 1970’s as part of the study of the physiological effects of spaceflight.

Centrifugation makes animals smaller, leaner, more muscular, and denser-boned

If you put female rats in a centrifuge for 60 days, at 2.76 and 4.15 G (where G is the strength of Earth’s gravitational field), they lose 10% and 19% of their body weight, respectively, with reductions in the fat fractions of most components and increases in the water fraction of liver and gut.[1]

Female rats exposed to 3.5 or 4.7 G for one year showed “marked depletion of body-fat depots” and “significant decrease in kidney and liver lipids.”[2]

Chickens exposed to 1.75, 2.5, or 3 G for 24 weeks had significantly reduced body fat.[15]  The drop in body fat is linearly increasing in G, and also increases with body mass.[17]

Rabbits exposed to up to 2.5 G had a drop in body fat and increase in body water, even as their food consumption increased.[16]

Female rats centrifuged for 30 days at 2.76 or 3.18 G reduced body fat and fat-free body mass within the first week of centrifugation, without any difference depending on whether they were fed commercial chow, a high-fat diet, a high-protein diet, or fasted.[3]

The drop in body fat from centrifugation can be quite large; chickens went from 13% body fat to 3% body fat at 3G, and mice have a 55% drop in total body fat after 8 weeks of 2G exposure.[18]

Centrifuged mice have a drop in weight during the first few days, but slowly regain it.[10]  Hamsters born in centrifuges have a final body weight of about 30% lower than control hamsters.[13]

Female rats centrifuged for 810 days at 2.76 G grew more slowly than control rats, but had the same absolute muscle mass; they have thicker bones and larger muscles for their size than uncentrifuged rats.[4]  They also have denser bones.[6]  They have a higher proportion of slow-oxidating muscle fibers (the kind used in distance running and other endurance activities).[9]  Centrifuged dogs (subjected to 2G for 3 months) also have denser bones.[11]

Centrifuged rats also had more uptake of glucose into tissues and a stronger response to insulin than uncentrifuged rats; this is the opposite of “insulin resistance.”[5]  Centrifuged chickens also have higher glucose uptake.[14]

Centrifuged rats have a sharp decrease in body temperature at about 3 days, and a subsequent recovery of normal body temperature.[7]

Centrifuged rats have a prolonged decrease in locomotor activity and distorted circadian rhythms.[8]

Centrifugation alters the vestibular system

The vestibular system is involved in balance.

The microscopic structure of the lateral vestibular nucleus (where many vestibular nerve fibers enter the brain) is altered in chronically centrifuged rats.[12]  Centrifuged hamsters have impaired balance during swimming tests.[13]

Knockout mice that lack vestibular linear acceleration organs are known as “head-tilt mice.” They move normally, except for a head tilt, but cannot swim because they cannot orient to the gravitational force vector.  Head-tilt mice, when centrifuged at 2G, do not experience the changes that chronic centrifugation causes in wild-type mice: they do not have a drop in body temperature, body mass, or body fat percentage. While wild-type mice under 2G dropped from 16% to 8% body fat, head-tilt mice started out at 8% before centrifugation and did not change.  This implies that vestibular effects somehow cause the physiological changes associated with higher gravity.

Artificially stimulating the vestibular organs causes fat loss

A pilot study at the University of California San Diego’s Center for Brain and Cognition, one of whose authors was famed neuroscientist Vilayanur Ramachandran, tested galvanic stimulation of the vestibular nerves, a non-invasive procedure that involves passing current over the inner ear, on six overweight and obese subjects, with three controls, for a total of 40 hours, for an hour a day.  There was a significant 8.3% decrease in truncal fat and a nonsignificant decrease in total body fat.  Appetite was reduced, leptin was reduced, and insulin was increased.[19]

This is not a huge reduction in fat.  (It would be something like two pounds on me, over the course of a month.) On the other hand, this is a significantly lower “dose” of vestibular stimulation than centrifuged animals would receive. The animals that had body composition changes were centrifuged continuously over a period of months.  It may be possible to slowly increase the time spent receiving galvanic stimulation.

Vestibular stimulation may affect hormone levels

There are a few case studies from India of “controlled vestibular stimulation” (swinging on a swing) causing various changes in physiology. A college student for whom swinging resulted in significantly lower blood pressure, blood glucose, and cortisol[21], and an 83-year-old diabetic man for whom swinging resulted in significantly lower glucose and blood pressure [22].

The vestibular system modulates autonomic activity, and vestibular stimulation activates vagus nerves in the pancreas which stimulate insulin production. There seems to be a parasympathetic response to vestibular stimulation, which goes with increased insulin production and lower hunger, both of which would reduce fat.  (It also matches the intuitive observation that rocking and swinging is soothing: think of infants and rocking chairs.)

Other Vestibular Stimulation Weirdness

Galvanic vestibular stimulation also seems to reverse face blindness [23].

Conclusion

Galvanic vestibular stimulation is safe, if sometimes uncomfortable (causes motion sickness), and might have significant effects on body fat and other metabolic factors. It is probably worth investigating more on humans.

It’s trivial to set up; people who are interested in virtual reality frequently build their own vestibular stimulation rigs to increase the verisimilitude of immersive games.  This seems like something with a lot of potential for venturesome self-experimenters to try out as well as something to investigate seriously in clinical experiments.

References

[1]Pitts, G. C., L. S. Bull, and J. Oyama. “Effect of chronic centrifugation on body composition in the rat.” American Journal of Physiology–Legacy Content 223.5 (1972): 1044-1048.

[2]Oyama, J., and B. Zeitman. “Tissue composition of rats exposed to chronic centrifugation.” American Journal of Physiology–Legacy Content 213.5 (1967): 1305-1310.

[3]Pitts, G. C., L. S. Bull, and J. Oyama. “Regulation of body mass in rats exposed to chronic acceleration.” American Journal of Physiology–Legacy Content 228.3 (1975): 714-717.

[4]Amtmann, Eduard, and Jiro Oyama. “Effect of chronic centrifugation on the structural development of the musculoskeletal system of the rat.” Anatomy and embryology 149.1 (1976): 47-70.

[5]Daligcon, B. C., and J. Oyama. “Increased uptake and utilization of glucose by diaphragms of rats exposed to chronic centrifugation.” American Journal of Physiology–Legacy Content 228.3 (1975): 742-746.

[6]Jaekel, Erika, Eduard Amtmann, and Jiro Oyama. “Effect of chronic centrifugation on bone density of the rat.” Anatomy and embryology 151.2 (1977): 223-232.

[7]Oyama, J. I. R. O., WILLIAM T. Platt, and VARD B. Holland. “Deep-body temperature changes in rats exposed to chronic centrifugation.” American Journal of Physiology–Legacy Content 221.5 (1971): 1271-1277.

[8]Holley, Daniel C., et al. “Chronic centrifugation (hypergravity) disrupts the circadian system of the rat.” Journal of Applied Physiology 95.3 (2003): 1266-1278.

[9]Martin, W. D. “Time course of change in soleus muscle fibers of rats subjected to chronic centrifugation.” Aviation, space, and environmental medicine 49.6 (1978): 792-797.

[10]WUNDER, CHARLES C. “Survival of mice during chronic centrifugation.” Aerospace Med 33 (1962): 866-870.

[11]Amtmann, Eduard, Jiro Oyama, and Gerald L. Fisher. “Effect of chronic centrifugation on the musculoskeletal system of the dog.” Anatomy and embryology 149.1 (1976): 71-78.

[12]Johnson, J. E., W. R. Mehler, and J. Oyama. “The effects of centrifugation on the morphology of the lateral vestibular nucleus in the rat: a light and electron microscopic study.” Brain research 106.2 (1976): 205-221.

[13]Sondag, H. N. P. M., H. A. A. De Jong, and W. J. Oosterveld. “Altered behaviour in hamsters conceived and born in hypergravity.” Brain research bulletin 43.3 (1997): 289-294.

[14]Evans, J. W., and J. M. Boda. “Glucose metabolism and chronic acceleration.” American Journal of Physiology–Legacy Content 219.4 (1970): 893-896.

[15]Evans, J. W., A. H. Smith, and J. M. Boda. “Fat metabolism and chronic acceleration.” American Journal of Physiology–Legacy Content 216.6 (1969): 1468-1471.

[16]Katovich, MICHAEL J., and ARTHUR H. Smith. “Body mass, composition, and food intake in rabbits during altered acceleration fields.” Journal of Applied Physiology 45.1 (1978): 51-55.

[17]Smith, A. H., P. O. Sanchez, and R. R. Burton. “Gravitational effects on body composition in birds.” Life sciences and space research 13 (1974): 21-27.

[18]Fuller, Patrick M., et al. “Neurovestibular modulation of circadian and homeostatic regulation: vestibulohypothalamic connection?.” Proceedings of the National Academy of Sciences 99.24 (2002): 15723-15728.

[19]McGeoch, Paul D., Jason McKeown, and Vilayanur S. Ramachandran. “Modulation of Body Mass Composition using Vestibular Nerve Stimulation.” bioRxiv (2016): 087692.

[20]Yates, B. J., and A. D. Miller. “Physiological evidence that the vestibular system participates in autonomic and respiratory control.” Journal of Vestibular Research 8.1 (1998): 17-25.

[21]Sailesh, Kumar Sai, and R. Archana. “Controlled vestibular stimulation: A physiological method of stress relief.” Journal of clinical and diagnostic research: JCDR 8.12 (2014): BM01.

[22]Kumar, Sailesh Sai, R. Archana, and J. K. Mukkadan. “Controlled vestibular stimulation: Physiological intervention in diabetes care.” Asian Journal of Pharmaceutical and Clinical Research 8.4 (2015): 315-318.

[23]Wilkinson, David, et al. “Improvement of a face perception deficit via subsensory galvanic vestibular stimulation.” Journal of the International Neuropsychological Society 11.07 (2005): 925-929.

Industry Matters

Epistemic status: tentative

In the wake of the election, I’ve been thinking about the decline of manufacturing in America.

The conventional story, the one I’d been told by the news, goes as follows. Cheap labor abroad competes with US manufacturing jobs; those jobs aren’t coming back; most manufacturing jobs are lost to robots, not trade, anyhow; this is tragic for factory workers who lose their jobs, and perhaps they should be compensated with more generous social services, but overall the US’s shift towards a service economy is for the best.  Opposition to outsourcing, while perhaps an understandable emotional reaction from the hard-hit working class, is simply bad economics.  At best, the goal of keeping manufacturing jobs at home is a concession to the dignity and self-image of workers; at worst, it’s wooly-headed socialism or xenophobia.

But what if that story were not true?

Here’s an alternative story, which I think there’s some data to suggest.

Industry — as in, factories in the US making things like cars and trains — is important to long-run technological innovation, because most commercial R&D is in the manufacturing sector, and because factories and research facilities tend to physically co-locate.

High-tech, high-cost-per-unit industries in particular, like the auto industry, are like keystone species in an industrial ecosystem, because you need many different kinds of technology to support them, and because the high cost per unit makes them the first industries where it’s worth it to invest in new process improvements like robotics.  If you don’t have heavy industry at home, eventually you won’t have innovation at home.

And if you don’t have innovation at home, your economy may eventually stagnate. Foundational technologies, things like integrated circuits or metallurgy, have high fabricatory depth; better microchips give rise to more computing power which gives rise to untold multitudes of software applications. If your economy lives exclusively on the “leaves” of the tech tree, you aren’t going to be able to capture the value from a long future of continued inventions.  There may be high-paying jobs in the service economy, but an entire economy built on services will eventually flatten out.

In other words: maybe industry matters.

And, while industrial jobs may initially leave the US because they’re cheaper elsewhere, foreign labor doesn’t stay cheap forever. As countries industrialize and become wealthier, they gain expertise and advance technologically, and eventually compete on quality, not just on price.  Rich countries hope to “move up the value chain”, outsourcing cheap and crude tasks to poorer countries while focusing their own efforts on higher-tech, higher-priced tasks. The problem is that this doesn’t always work — since collocation matters, it may be that you need at least some of the basic factory work to stay at home in order to be able to do the high-tech work, especially in the long run.

“Industry matters”, if true, might be an argument in favor of tariffs, in a vaguely Hamiltonian industrial policy.  Now, the laws of economics still hold; tariffs will always cause some degree of damage.  I’m not confident that the numbers work out such that even an ideal tariff would be worth it, let alone the trade policy likely to be administered by the actually-existing USG.

“Industry matters” might also be an argument in favor of deregulation designed around making it easier to move around  “atoms not just bits.”  If environmental and labor regulations make it extremely difficult to build factories in the US, and if industry has an outsized impact on long-run growth, then the cost of regulation is even higher than previously assumed. If a factory doesn’t open, the cost is not only borne by the people today who could have worked in or profited from that factory, but by future generations who won’t be able to work at the new companies which would have been produced from innovations downstream of that factory.

If industry matters, it might be worth it to trade a bit of efficiency today for long-run growth. Not as a concession to Rust Belt voters, but as a genuine value-creating move.

The US is transitioning to a service economy

According to the Bureau of Labor Statistics’ Employment Outlook Handbook, occupations with declining employment include:

  • Agricultural workers
  • Clerks (file, correspondence, accounting, etc)
  • Cooks (fast food and short order)
  • Various manufacturing occupations like “machine tool setters” and “electronic equipment assemblers”
  • Railroad-related occupations
  • Drafters, medical transcriptionists
  • Secretaries and administrative assistants
  • Broadcasters, editors, reporters, radio and television announcers
  • Travel agents

while the jobs with the fastest growth rates include:

  • Nurses, home health aides, physician’s assistants, physical therapists
  • Financial advisors
  • Statisticians, mathematicians
  • Wind turbine service technicians, solar photovoltaic installers
  • Photogrammetry (i.e. mapping) specialists
  • Surgeons, biomedical engineers, nurse midwives, anaesthesiologists, medical sonographers
  • Athletic trainers, massage therapists, interpreters, psychological counselors
  • Bartenders, restaurant cooks, food preparers, waiters and waitresses
  • Cashiers, customer service representatives, hairdressers, childcare workers, teachers
  • Carpenters, construction laborers, electricians, rebar workers, masons

Basically, medicine, education, customer service, construction, and the “helping professions” are growing; factory work, farming, and routine office tasks are shrinking, as are industries like news and travel agents that have been disrupted by the internet.

As far as mass layoffs go, in May 2013 the largest sector by number of mass layoffs was manufacturing, where the largest number of people laid off were in “machinery” and “transportation equipment.”  Construction followed, where most layoffs were in “heavy and civil engineering” construction.

By sector, mining and manufacturing are losing employment, while construction, leisure and hospitality, education and health, and financial services, are gaining employment.

This part of the conventional story is true: manufacturing jobs really are disappearing.

US manufacturing productivity and output are stagnating

It’s not just jobs, but also productivity and output, where manufacturing in the US is weakening.  US manufacturing still produces a lot, but its growth is slowing.  We’re not getting better at making things the way we used to.

In the US, the biggest output gains per industry, in billions of dollars, between 2002 and 2012, were in the federal government, healthcare and social assistance, and professional services, at 2.6%, 2.6%, and 2.4% respectively. Manufacturing only grew by 0.2%.

Manufacturing output as a whole between 1997 and 2015 was only growing at 0.8% a year, meaning that it’s slowed down in the last 20 years.  Broken down by subsector, the highest manufacturing growth rates were in motor vehicles and other transportation equipment, at an average of about 2% yearly growth; other kinds of manufacturing, such as textiles and apparel, were stagnant or even declined in output.  By contrast, the largest output growth between 1997 and 2015 was in information tech, at an average of 5.6% yearly growth, probably coinciding with the rise of the Internet economy.

In other words, US manufacturing isn’t shedding jobs merely because it’s becoming ultra-automated and efficient. US manufacturing growth has slowed down a lot in output as well.

US manufacturing also stagnated in labor productivity and multifactor productivity. Multifactor productivity (the efficiency of labor & capital) in manufacturing has declined at an 0.5% rate from 2007-2014, while it was increasing at a 1.7% rate in 2000-2007, 1.9% in 1995-2000, and 1.1% in 1990-1995.  Manufacturing productivity was roughly flat from the 1970’s through 2000.

Manufacturing total factor productivity is still increasing, but has been leveling off.

Manufacturing output, similarly, is still increasing, but has been leveling off in recent decades.

While overall manufacturing productivity is still growing  over the period 1987-2010, manufacturing output flattened in about 2000.

While manufacturing output seems to have grown roughly steadily since the 1950s, with a slow decline or stagnation in employment from about 1970-2000, note how the output curve seems to be bending at around 2000, just as manufacturing employment plummets.

You can also see this slight bend in the curve, beginning in around 2000, in manufacturing value added.

The story of “we’re getting more efficient and thus using fewer workers” is only part true.  We’re getting more efficient, but at a slowing rate. We’re producing more output than we did in the 70’s, but that seems to have leveled off in around 2000. Yes, there’s more output and fewer workers, but it looks like recently, since about 2000, multifactor productivity and output are slowing down.

The Big Three auto manufacturers in the US, between 1987 and 2002, had dropping market share and stock price, largely due to international competition.  They lagged the competition in durability and vehicle quality, so were forced to cut prices. They also had a labor productivity disadvantage relative to Japan.  It took nearly two decades for US car manufacturers to catch up to Japanese production process improvements.

In other words, the story of the decline in US manufacturing jobs is not merely that we’re a rich country with expensive labor, or a high-tech country that uses automation in place of workers.  If that were true, output and productivity would be continuing to grow, and they’re not.  US manufacturing is stagnating in quality and efficiency.

Robots aren’t taking American jobs

The decline in US manufacturing began in the 1970’s and 1980’s, as trade liberalization made it easier to move production abroad, and new corporate governance rules made US managers focus on stock prices and short-term performance (which could be boosted by moving factories to cheaper countries.)

Manufacturing automation, by contrast, is much newer, and can’t account for anywhere near that much job loss.  There are only 1.6 million industrial robots worldwide, mostly in the auto and electronics industries; an automotive company has 10x the roboticization of the average manufacturing company.  That is to say, robots are only being used in the highest-tech sectors of the manufacturing world, and not very widely at that. Industrial robots are a rapidly growing but very recent development; there was a 15% increase in the world’s supply of robots just in 2015.

Moreover, countries with more growth in industrial robotics don’t have more job loss.  Most new robots are actually abroad rather than in the US. The largest market is in China, with 27% of global supply; the second largest market is in Europe.  The US boosted its purchases of robots by only 5% this year, at well below the global rate of robotics growth.

It is simply false that robots are causing any significant part of US manufacturing unemployment. There aren’t very many, they haven’t been around very long, they’re mostly in other countries, and they don’t hurt employment in those countries.

According to the Bureau of Labor Statistics, no US manufacturing layoffs in 2013 were due to automation.

Most of the news articles about the dangers of technological unemployment are based on projections about which jobs are in principle automatable. This is speculative, and doesn’t take into account new industries that may open up as technology improves (basically the argument from Say’s law.)  The “post-work future” is largely science fiction at this point. Lost manufacturing jobs are real — but they weren’t lost to robots.

Trade caused manufacturing job loss

The US-China Relations act in 2000 that normalized trade relations permanently was a “shock” to US manufacturing that US jobs were slow to recover from.  Not only did employment plummet, but manufacturing productivity also dropped steeply.

Only 2% of job losses are due to offshoring. But this understates the true amount: if plants close in the US while companies buy from foreign affiliates, that’s effectively “jobs moving overseas” under a different name.  Foreign affiliates now make up 37% of the total employees of US multinational companies, a figure that has been steadily rising since the 80’s; it was 26% in 1982.

Moreover, trade can also cause US job losses if foreign-owned companies outcompete US companies. The most common reason given for manufacturing layoffs in 2013 was “business demand”, mostly contract completion.  Restructuring and financial problems such as bankruptcy were also common reasons.  The main reason for manufacturing layoffs seems to be failure of US factories — poor demand or poor company performance.  Some portion of this is probably due to international competition.

In short, it’s freer trade and poor competitiveness on the international market, not automation, that has hurt American manufacturing.  It’s not the robots that are the problem — if anything, we don’t have enough robots.

Manufacturing drives the future, and location matters

A McKinsey report on manufacturing notes that while manufacturing is only 16% of US GDP, it’s a full 37% of productivity growth.  77% of commercial research and development comes from manufacturing.  Manufacturing, in other words, is where new technology comes from, and new technology drives growth.  If you care about the future economy, you care about manufacturing.

R&D, especially later-stage development rather than basic academic research, must be physically proximate to the lead factory even if some production is globalized, for reasons of communication and feedback between research and production.  You can’t outsource or trade all your manufacturing without losing your ability to innovate.

Moreover, globalized supply chains have real costs: as trade and outsourcing increase, transportation costs and supply chain risks have also been increasing. Physical proximity places some limits on how widely dispersed manufacturing can be.  Trade growth has outpaced infrastructure growth in the US, driving transportation costs up.  The cost of freight for steel and iron ore is almost as high as the material itself.

Steel production, in particular, has plummeted in industrialized countries since the 70’s and 80’s, as part of the switch to a service economy. China’s steel and cement production since the 80s seems to have grown rapidly, while its car production seems to be growing roughly linearly.  South Korea’s steel production is growing steadily. US car production, by contrast, has been shrinking (in terms of number of units), as has its steel production.  Because (due to their weight) metals have unusually high transportation costs, proximity matters an unusual amount, and so a fall in steel production might mean a fall in heavy industry output generally, which is difficult to recover from.

The main theory here is that, once you cease to be an industrial economy, it’s hard to profitably keep factories at home, which means it’s hard to innovate technologically, which means long-run GDP growth is threatened.

The largest manufacturing industries are machines, electronics, and metals

The largest manufacturing companies in China make cars (SAIC, Dongchen, China South Industries Group), chemicals (Sinochem, Chemchina), metals (Minmetals, Hesteel, Shougang, Wuhan), various engineering (Norinco, China Metallurgical group, Sinomach), electronics (Lenovo), phones (Huawei), ships (China Shipbuilding).

The US’s largest manufacturers are general engineering (GE), automotive (GM, Ford), electronics (HP, Apple, IBM, Dell, Intel), pharmaceuticals (Cardinal Health, Pfizer), consumer goods (Procter & Gamble, Johnson&Johnson), aerospace (Boeing, Lockheed Martin), food and beverage (Pepsi, Kraft, Coca-Cola), construction equipment (Caterpillar), and chemicals (Dow).

Germany’s largest manufacturing companies are automotive (Volkswagen, Daimler, BMW), chemicals (BASF), engineering (Siemens, Bosch, Heraeus), steel (ThyssenKrupp), pharmaceuticals (Bayer), and tires (Continental).

Japan’s largest manufacturers are automotive (Toyota, Nissan, Honda), engineering (Hitachi, Panasonic, Toshiba, Mitsubishi, Mitsui, Sumitomo, Denso), electronics (Sony, Fujitsu, Canon), steel (Nippon Steel, JFE), and tires (Bridgestone).

Korea’s largest manufacturers are electronics (Samsung, LG), automotive (Hyundai, Kia), and steel (POSCO).

Machinery and appliances, and electronics and parts, are by far the largest exports from Mexico.

Top exports from China, at a coarse level of granularity, are machines (48%), textiles (11%), and metals (7.8%).  At a more granular level, this involves computers, broadcasting equipment, telephones, integrated circuits, and office machine parts.

US‘s top exports are machines (24%), transportation (15%), chemicals (13%), minerals (11%), and instruments (6.3%). More granularly, this is integrated circuits, gas turbines, cars, planes and helicopters, vehicle and aircraft parts, pharmaceuticals, and refined petroleum.

Germany‘s top exports are machines (27%), transportation (23%), chemicals (13%), metals (8.1%), or in more detail: cars, vehicle parts, pharmaceuticals, and a variety of smaller machine things (valves, air pumps, gas turbines, etc).

Japan’s exports are machines (37%), transportation (22%), metals (9.8%), chemicals (8.5%), and instruments (7.8%). Or, in more detail: cars, vehicle parts, integrated circuits, and a variety of machines like industrial printers.

South Korea’s exports are machines (37%), transportation (19%), minerals (8.9%), metals (8.5%), plastics (7.1%). In more detail, integrated circuits, phones, cars, ships, vehicle parts, broadcasting equipment, and petroleum.

“Heavy industry” — that is, machines, engineering, automobiles, electronics, and metals — is the cornerstone of an industrial economy.  Integrated circuits are a true “root” of the tech tree, the foundation on which the information economy is built. Capital-intensive heavy industries like automobiles are a “keystone” which is deeply interwoven with the production of machines, parts, robots, electronics, and steel.

It’s a relevant warning sign for Americans that many current developments that seem likely to improve “heavy industry” are not concentrated in the US.

Of the top 5 semiconductor companies, only 2 are American. Some electronics innovations, like flat-screens (developed by Sony) and laser TV’s (developed by LG) were developed by Asian companies, and Mexico is the biggest exporter of flat screen TVs.  Robotics, as discussed above, is being pursued much more intensively in Asia and Europe than in the US. “Smart factories”, in which automation, sensors, and QA data analysis are integrated seamlessly, are being pioneered in Germany by Siemens.  The majority of drones worldwide are produced by Israel.  The Japanese companies Canon and Ricoh, as well as the American HP, are expected to launch 3d printers this year; meanwhile the largest manufacturer of desktop 3d printers, XYZprinting, is Taiwanese.

A positive sign, from a US-centric perspective, is that self-driving cars are being developed by American companies (Tesla and Google.)  Another positive sign is that basic research in physics and materials science — the fundamentals that make a continuation of Moore’s law possible — is still quite concentrated in American universities.

But, to have a strong industrial economy, it’s not enough to be good at software and basic research; it remains important to make machines.

Non-xenophobic, economically literate, pro-industry

Globalization has been a humanitarian triumph; Asia’s new prosperity has vastly reduced global poverty in recent decades. To acknowledge that global competition has been hard on Americans doesn’t preclude appreciating that it’s been good for foreigners, and that foreigners have equal moral worth to ourselves.

Acknowledging harms from trade also doesn’t require one to be a fan of planned economies or a believer in a “zero-sum world.” Trade is always locally a win-win; restricting it always has costs.  But it may also be true that short-term gains from trade can be counterweighted by long-term losses in productivity, especially due to loss of the gains in local skill and knowledge that come from being a manufacturing center.

If you want to live in a vibrantly growing country, you have to make sure it remains a place where things are made.

That’s not mere protectionism, and it’s certainly not Luddite.

I don’t think this is true of, say, agriculture, where vast increases in efficiency have reduced the number of farmers needed to support the global population, but where that’s not really a problem for overall growth. US farming has not lost ground — we produce more food than ever.  We are not getting worse at farming, we just need fewer people to do it.  I suspect we are getting worse at manufacturing.  And since manufacturing has so disproportionate an effect on downstream growth and innovation, that’s a problem for all of us, in a way that it’s not a problem if farmers or travel agents lose their jobs to new technologies.

Pro-Industry, Anti-Corruption

The truly obvious gains from capitalism are actually gains from industry. Cheap, varied, abundant food. Electricity and electric appliances. Fast transportation. The sort of things described in Landsailor.

Other things that show up in GDP are less obviously good for humans. If real estate prices rise, are we really better housed? If stock prices rise, do we really have more stuff?  If we spend more on medicine and education but don’t have better health outcomes or educational outcomes, are we really better cared for and better educated?

The value of firms has dramatically shifted, since 1975, towards the “dark matter” of intangibles — things like brands, customer goodwill, regulatory favoritism, company culture, and other things that can’t be easily measured or copied. US S&P 500 firms are now 5/6’ths dark matter.  How much of the growth in their value really corresponds to getting better at making stuff?  And how much of it is something more like “accounting formalism” or “corruption”?

If you are suspicious of things that cost more money but don’t create obvious Good Things for humans, then you will not consider a shift to a service economy a good outcome, even if formally it doesn’t look too bad in GDP terms. If you take a jaundiced view of medicine, education, the “helping” professions, government, and management — if you see them as frequently doing expensive but unhelpful things — then it is not good news if these sectors grow while manufacturing declines.

If your ideal vision of the future is a science-fiction one, where we cure new diseases, find new fuel sources, and colonize the solar system, then manufacturing is really important.  

The old slogans like “what’s good for GM is good for America” are not as far from the truth as you’d think.

 

On Trying Not To Be Wrong

Epistemic Status: Exhortative

I did not expect Donald Trump to become President.

I did not expect him to win, or even get very far, in the Republican primaries. Like many people, I thought the idea of Donald Trump becoming president was “weird” or “surreal” or “not a thing that happens.”  Like many people, I’ve thought 2016 was a surreal year; the Cubs won the World Series, Hillary Clinton went on television to warn people about white-supremacist memes, Elon Musk has landed rockets on ocean platforms and started an organization to develop Friendly AI.  Surreal, right?

No.

It’s real, not surreal. If reality looks weird, this means our stories about it are wrong.

Did polls and newspapers and social media fail to see this election coming? Then those sources just took a hit in credibility.

On a longer-term note, if you know there’s a replication crisis in scientific research, that should be shaking up your trust in published papers.

There may be a crisis in politics. But before we can do anything sensible about that, we need to understand that there is a crisis in credence. If the world looks weird to you and me today, that is not a matter for rueful laughter, it is a sign that we are probably badly wrong about lots of things.

And being totally wrong about how the world works is a threat to survival.

What this election brought home to me is that I don’t want to be wrong any more.

A lot of things people say and write are not really what they think is true about the world. They’re expressions of emotion or identity or solidarity. Arthur Applebee writes about “the affective center” being the prototypical use of language: gossip, relationship-building, sharing feelings.  Evolutionary biologist Geoffrey Miller thinks that language, as well as the high intelligence needed to navigate social relations, evolved in humans through sexual selection.  We are built for these “soft” uses of language and thought: to relate, to bond, to politick. Doing that feels good and intuitive and healthy. It feels “human”, because it is.

It is, of course, also not truth-seeking. We have a host of cognitive biases, particularly in these normal, social uses of speech.  Much of it is bullshit, in Harry Frankfurt’s terminology: not so much lies as not about truth in the first place.

But it is possible for language to be used in ways that do point towards truth.  Arguments where premises follow from conclusions — when people are reading to check whether premises follow from conclusions and facts are supported by evidence — actually do hold independently of shifting social contexts.

What that requires socially is for people to do something quite unnatural. Instead of going with the flow (relating, politicking, sharing feelings, bonding), it involves breaking the flow. Nitpicking. Disagreeing. Being dry and technical. Fact-checking.

The motto of the Royal Society of London was “Nullius in verba”, or “Take nobody’s word for it.”  The modern scientific tradition was founded by a small group of people defined by the fact that they would call bullshit on things unless they were demonstrated by evidence.  This is inherently disagreeable — literally, it involves disagreeing.

The contemporary flow of social media works to prevent discussion and argument, while earlier internet formats worked to promote it.

A blog and a comments section, or a forum, or an email thread, is set up to encourage discussion.  One has space to write long-form, multi-paragraph essays, which are stored permanently; and then there is ample space for other people to write long-form, multi-paragraph responses to those essays.  One can respond to specific points separately. One can respond to responses, in long nested threads.  It is good form to cite sources (links and hat-tips).  The social reward for writing is getting a response to your writing. The world of blogs and forums provided an alternative to mass media that was more discursive and more intellectual.

Newer forms of social media inhibit discussion and promote simpler affective responses.

Facebook still allows threaded discussions, but the unit of attention is the like. You get socially rewarded when lots of people agree with you; agreement, being cheaper than response, will wind up being more abundant and hence more dominant, in a sort of Gresham’s Law phenomenon.

Twitter doesn’t allow room for long-form content, of course, and the first-class actions are liking and retweeting: approval and copying.  Tumblr allows for paragraph-long posts, but has such poor threading that it’s difficult to hold a discussion, structurally prefers images and videos to text, and makes liking and reblogging first-class actions. Snapchat and Instagram are deeply unfriendly to text.

And all of the above social media platforms have an endlessly scrolling feed, which makes conversations ephemeral and difficult to reference.

The incentives are against discussion and towards response. Instant emotional readouts, approval or disapproval.  Image rather than language. Copying rather than original writing.

The medium is designed for agreement, not disagreement. People who can’t communicate in a way that will rack up “likes” or “favorites” tend to quietly withdraw.  And that feels awkward, like they’re spoiling the party, like a kind of Puritanism.

But I also suspect that these Puritans, these disagreeable people, have something to teach us. Especially now.  Especially when it’s become clear that “believing” things out of mood affiliation leads to very wrong conclusions about the world.

Humans love to socialize. One of the things that we like to do with leisure and technology is talk to each other. I’m not denigrating this normal human urge, which finds expression in social media.

What I’m saying is that one of the remarkable things that can be done with human intelligence, language, and socializing is to have discussions. Arguments. Conversations. Science is a form of conversation, as is philosophy.  Out of the natural “affective center” of gossip can come something that is a bit more unnatural but extraordinarily powerful: you can come to reliable and referenceable common knowledge.  You can refer back to “oh, yeah, on February 15th Bob did this experiment and on February 16th Alice tried it herself and got the same result, and then Carl found a flaw in the design so it turned out Alice and Bob were wrong.”

It’s not about liking a claim, it’s about being convinced by it.

I’m not talking about something that necessarily has to be high-minded and out of reach, or something that will singlehandedly fix the problems we face.

But it seems really useful now to start having discussions again. On blogs, on forums, on email, in contexts where it’s socially rewarding to disagree and pick things apart, rather than to merge into mobs of agreement.

It’s urgent to figure out what is going on in the world and how we can keep it from hurting us.  And that means our errors need to be corrected.

If this seems kind of dutiful and unpleasant, compared to the warm rush of likes and reblogs and image-sharing, consider that it’s actually kind of fun in its own right to have arguments and discussions and to dig into the nitty-gritty. It’s the nerdy kind of fun that gets a kick out of details, out of facts, out of messing around until things click into place satisfyingly.  It’s the mental equivalent of the kind of fun it is to make things with your hands, or to play games.

The Scottish Enlightenment was a little, well, Scottish.  What are the Scottish stereotypes? A little grouchy, a little ornery, a little stingy.  Hard-headedly practical.  Blunt. In other words, there’s a kind of healthy disagreeableness, that says “don’t give me bullshit”, and “don’t rip me off”, and “I’m sure as hell not going to kneel to you” and “I may not be rich or powerful, but I’m honest”, and “I built machines that work, dammit.”  In a world where liking and agreeing is the currency, I think we are likely to underappreciate the virtues that go with disagreeableness.

I’m going to lean more into disagreement and fact-checking. I’m going to try to appreciate the people who say “not exactly” instead of going with the flow. I’m going to aim to have my discussions in contexts that are actually designed for discussion.  I care about not being wrong, now, in a way I really didn’t before.  And I encourage others to consider doing the same.

Ra

Epistemic status: very speculative. This is mythmaking: you’ve been warned.

Ra is the Sun God

The Egyptian god Ra was a symbol of divine kingship, all-powerful and all-seeing.  He’s a good metaphor for a certain kind of psychological phenomenon that involves thought distortions around authority and legitimacy.  A new demon, if you will, in the grimoire that includes Moloch and Azathoth.

The idea of a malign Establishment is somewhat convergent:

The Establishment (attributed to Henry Fairlie in 1950’s Britain, talking about an informal social network of power among prominent, well-connected people)

The Man (e.g. Yippies, Burning Man)

The Combine (Ken Kesey)

Moloch (Allen Ginsberg)

The Beige Dictatorship (Charles Stross)

The Cathedral (Mencius Moldbug)

The Mandarins (Megan McArdle)

Not all of these ideas are coterminous with Ra, or identical to each other.

What they have in common is that the Establishment is primarily an upper-class phenomenon, that it is more about social and moral legitimacy than mere wealth or raw power, and that it is boringly evil — it produces respectable, normal, right-thinking, mild-mannered people who do things with very bad consequences.

What Ra is not

The usual pitfall when using poetic language to define egregores is making them too broad.  There is not one root of all evil that causes all the ills of the world.

Ra is not simply conformity, simply authoritarianism, or simply power-seeking.  Ra is not the same as “bureaucracy” or “capitalism” or “fallen human nature” or all the myriad reasons why your idealistic goal might fail.  Ra is not “everything that is wrong with people who disagree with me.”

As a social phenomenon, Ra is responsible for some dysfunctions in the democratic modern West; it is not, for instance, what was going on with the Nazis, or with terrorists, or with communist revolutionaries, or with the Confederates in the American Civil War.  Ra is not driving people who want to take over the world for some fanatic goal. It’s more like a dissipating, entropic motion, a process that corrupts institutions.

But it’s not merely the most commonly claimed drivers of institutional decay, like “knowledge problems” or “coordination problems”.  People who participate in those problems are following rational self-interest, but wind up contributing individually to collectively harmful outcomes.  Ra is something more like a psychological mindset, that causes people to actually seek corruption and confusion, and to prefer corruption for its own sake — though, of course, it doesn’t feel quite like that from the inside.

Ra is a specific kind of glitch in intuition, which can roughly be summarized as the drive to idealize vagueness and despise clarity.  I’m going to try to define it by extension, using examples from my and others’ personal experiences.

Ra is about generic superlativity.

You know how universal gods are praised with formulas that call them glorious, mighty, exalted, holy, righteous, and other suchlike adjectives, all of which are perfectly generic and involve no specific characteristics except wonderfulness?  That’s what Ra is all about.

The worship of Ra involves a preference for stockpiling money, accolades, awards, or other resources, beyond what you can meaningfully consume or make practical use of; a felt sense of wanting to attain that abstract radiance of “bestness”.

A featureless, powerful organization, something with a name like “Acme Corp”, whose activities you can’t pin down, is archetypally Ra.  Especially if it’s associated with markers of excellence (e.g. very smart high-achieving employees) or fully general capabilities (eg the most powerful computers in the world). OpenAI has a lot of this quality, as does Google, as did Enron before its collapse, as do top management consulting firms and investment banks and Ivy League schools. Effective Altruism, when it’s just “a movement for generic optimal goodness”, has a lot of this quality.  When an organization seems shiny, full of the best and brightest, and is presumed to be potentially good at everything, it is appealing in a very Ra-flavored way.

In my mind I synaesthetically imagine Ra as radiant white light and smoothness (as in “futuristic” computer graphics, or as in mirror-like glossiness.)

Ra is evident in marketing that is smooth, featureless, full of unspecified potential goodness, “all things to all people,” like Obama’s 2008 campaign.  (Note the logo, with its smooth gradient and radiant white sun.)  Apple’s design is also very Ra.

Ra is about legitimacy.

When someone is willing to work for prestige, but not merely for money or intrinsic interest, they’re being influenced by Ra.  The love of prestige is not only about seeking “status” (as it cashes out to things like high quality of life, admiration, sex), but about trying to be an insider within a prestigious institution.  Not only “people like and respect and desire me” but “this abstract, objective Thing full of goodness has sanctioned me.”  People with money or charisma but no prestige read as sleazy (e.g. gamblers, gurus) while people with status and prestige/insiderness read as legitimate (e.g. the rightful king or official priest or licensed professional.)

Ra involves seeing abstract, impersonal institutions as more legitimate than individuals. For instance, I have the intuition that it is gross and degrading to pay an individual person to clean your house, but less so to hire a maid service, and still less so if a building that belongs to an institution hires a janitor.  Institutions can have authority and legitimacy in a way that humans cannot; humans who serve institutions serve Ra.

Seen through Ra-goggles, giving money to some particular man to spend on the causes he thinks best is weird and disturbing; putting money into a foundation, to exist in perpetuity, is respectable and appropriate.  The impression that it is run collectively, by “the institution” rather than any individual persons, makes it seem more Ra-like, and therefore more appealing.

Ra causes avoidance of challenging regulators and establishment hierarchies in significant excess of the actual legal and reputational costs of doing so.  Not just caution, but a sort of unbounded over-caution that makes you willing to throw huge amounts of value away to reduce already small risks.  Selfishness can motivate caution and even conformity; Ra-worship motivates sacrificing excess value to institutions you view as more legitimate than yourself.

Once, the CEO of a hedge fund and a friend of mine were in a heated argument, and the CEO finally pushed his point home by saying “200 PhDs work for me, so I know what I’m talking about.”  This is argument by legitimacy.  It’s just saying “because my institution has piled up a lot of excellence in one place, I get to talk and you have to shut up.”  It’s not an argument from expertise like “My 200 physics PhD’s agree with my point about physics” would be. It’s not even a direct power claim like “My 200 armed security guards will make you shut up.”  The guards would be a practical threat; the PhD’s really aren’t.  But they would be, to someone who believed that they granted legitimacy, that the accumulation of PhDs proved that the CEO had more right to speak and think.

Ra defends itself with vagueness, confusion, incoherence — and then anger.

“Respectability” turns out to be incoherent quite often — i.e. if you have any consistent model of the world you often have to take extreme or novel positions as a logical conclusion from your assumptions. To Ra, disrespectability is damnation, and thus consistent thought is suspect.

Vagueness, mental fog, “underconfidence”, avoidance, evasion, blanking out, etc. are hallmarks of Ra.  If cornered, a person embodying Ra will abruptly switch from blurry vagueness to anger and nihilism.

I have, in Ra-influenced moods, had the intuition “I don’t know if it’s possible to be a consistent economic agent [i.e. von Neumann-Morgenstern] and still be good.” Consistency implies the potential for disobedience. Consistency means you might not be recruitable or available to arbitrary purposes.  It’s the opposite of malleability.  Ra wants its worshippers to be always available, always malleable; and calls it “wicked” to have resistance to that.

One friend of mine discussed having a conversation about the future of humanity with someone, getting the strong sense that this person was being evasive and switching between viewpoints, and also that underneath the evasiveness there was a negative-utilitarian belief that humanity ought to be annihilated. And she worried that if she pushed too hard on insisting the other person make a coherent argument, that he would double down on the negative utilitarianism and become vindictive about it.  This is prototypical Ra behavior.  Smooth, soft vagueness that, when challenged, collapses into angry nihilism.

One symptom of Ra is being offended or upset when friends and allies are not doing things associated with power and status.  Actual insecurity and anger at the sight of someone doing their own thing, behaving in ways that don’t bring them closer to the center of coolness/shininess/power/etc.

Nastasya Philipovna, in The Idiot, demonstrates this kind of anger; when she meets the man who embodies her moral ideal, instead of reaching out to him as a lover, she is outraged that he’s being shabby and noble and ignoring the “way of the world”, and she actively ruins his life. It’s not that she doesn’t appreciate goodness; it’s that it freaks her out.  People ought not be that good. It disturbs the universe.  Myshkin is missing something — it’s not clear what, because if you look at his words and actions explicitly he seems to be behaving quite sensibly and moderately — but he’s missing some intuition about the “way of the world”, and that enrages everyone around him.

I remember being angry at a coworker, once, for attempting to sell a product to big pharma companies, because he was thinking of them too lightly, not appreciating the awesome majesty of the pharma companies that we were barely worthy to submit our ideas to.  He seemed not to understand the unspoken “way of the world”, and that made me angry.  That was classic Ra thinking on my part.

Ra is involved in the sense of “everyone but me is in on the joke, there is a Thing that I don’t understand myself but is the most important Thing, and I must approximate or imitate or cargo-cult the Thing, and anybody who doesn’t is bad.”  E.g. having the intuition that the power to make successful companies lies in things like “complex sales”, without understanding how complex sales works on a nuts-and-bolts level.  If you just associate complex sales guys with power and success, if you have the feeling that they probably know how to become an insider even if you don’t, then you’re engaging in Ra thinking.

Ra causes persistent brain fog or confusion, especially around economic thinking or cost-benefit analysis or quantitative estimates.  E.g. for a while I had a block around the question “How much would it cost to outfit a biology lab?” and thought that this was literally impossible for me to discover the answer to because the information would only be available to properly credentialed biologists or pharma company employees.  I had a weird aversion to seeking information or thinking directly about the problem.  Another time, I had a block around answering the question “How many lives would be saved if all men got HPV vaccines?” because it was epidemiology and people were talking about publishing the results in a journal and I felt unworthy as a non-academic to submit journal articles, so I procrastinated and didn’t even try to do Fermi estimates on the question.

Ra tends to cause confusion and brain fog around modeling preferences, particularly two or more independent agents trying to negotiate mutually beneficial solutions.  When Ra is active, you’ll see a persistent disposition, in otherwise intelligent people, to misunderstand trade or negotiation scenarios as dominance/submission scenarios.

Ra may cause blurriness around objectives. In Drucker’s Management, the purpose of a business (or nonprofit or government agency) is explicitly not to maximize profits or shareholder value, or to produce the best widgets or save the most lives, but to fulfill its function.   But what does that even mean?  It means something like the preservation of the organization — but it’s not specific.

There’s a disinclination to get specific about numbers or negotiations or goals or arguments.  And then an angry sense that people who do get specific are “doing it wrong” or “bad people” and deserve harshness.  An intuition that the really important things in life, the true “ways of the world”, are hidden or mysterious, always unspoken, and must be respected.

Ra hates communication and introspection.

Ra causes a disinclination to express oneself. An impression that a person who is unknown or mysterious is more attractive or favorably received than a person who is an “open book.”  A tendency to prefer private and off-the-record communications. There are many non-Ra reasons for secrecy, privacy, or reservedness (e.g. spies, shy people) — the core Ra quality is not merely the concealment but the idealization of the invisible, an intuition that people who display a smooth surface to the world are better.

Glamour is a related idea (see Virginia Postrel), in particular the glamour of “mystery and illusion.”  Glamorous things or people are idealized precisely because the details are airbrushed out.

There’s also a preference not to engage with people authentically — i.e. being more comfortable asking someone for a pre-packaged response (like “give me money” or “sign this petition”) than asking them to have an open-ended conversation with you.

Ra promotes the idea that optimal politeness conveys as little information as possible. That you should actively try to hide preferences (because if you shared them, you’d inconvenience others by pressuring them to satisfy your preferences).  That all compliments are empty pleasantries.  There’s an interpretation of “politeness” that’s anti-cooperative, that avoids probing for opportunities for genuine mutual benefit or connection and just wants to make the mutual defection process go as smoothly as possible.  Ra prefers this, because it’s less revealing, commits you less, doesn’t pin you down, allows you to keep all your options open and devote everything to the pursuit of Ra.

Ra is involved in intuitions about silence or absence being ideal.  A blank sheet of paper is more beautiful than any art you can put on it, because the art is potentially flawed, while blankness is flawless.  Blankness leaves all the options open. See also The Whiteness of the Whale.

People who write a lot, or enjoy discussions, or spend a lot of time on introspective “inner work”, tend to be less Ra-oriented.  Blogging is very anti-Ra.  Having opinions and making essay-style arguments, for all the flaws of that medium, does promote some degree of coherence and specificity, and promotes people sharing their inner lives.  Having a coherent, specific, shareable inner life means you’re less malleable, less blank, and Ra insists that people’s inner lives be completely malleable and blank.

I’ve had my writing criticized because “when you give your opinion, it sounds like you think you’re smart”.  And I’ve spent a lot of time feeling ashamed of “thinking out loud” in public, because it tarnishes the glossy facade that it’s easy to feel obligated to put up.  I’ve also had my more mainstream, Ivy League friends express surprise that I cared at all or made the slightest effort for friends in trouble.  Being committed or involved in people’s lives is also messy and doesn’t permit the preservation of a flawless impression.  Expressing yourself, thinking speculatively, and relating to people are shameful to the Ra-worshipping mindset, because all mental and emotional resources must be channeled into the quest for prestige.

Gruad Grayface, in the Illuminatus! Trilogy, is one of many figures representing “the Man” or malign technocratic authority, and he is accused of setting people against each other, making them unable to empathize across demographic lines (men and women, black and white), because if they communicated with each other they would realize that they were natural allies and none of them benefited from Gruad’s tyrannical rule.

There’s a persistent theme in the 60’s counterculture ethos that if people just communicated authentically, it would make a big difference to the world. And while this sounds like a platitude, I think it might be an important truth about the nature of Ra. See “The Sound of Silence.”  See Leary’s exhortation to “find the others.”  See the dystopia of perfect conformity that is Camazotz, which is vanquished by human flaws and by the love of specific people. Understanding that everyone has an inner life and nobody is smooth and blank is the antithesis of Ra.

Ra is fake Horus.

Originally, the Egyptian falcon-god Horus was the god representing the Pharaoh’s sovereignty.  The notion of Horus as the pharaoh seems to have been superseded by the concept of the Pharaoh as the son of Ra during the Fifth Dynasty.

Horus was supposed to be literally the Pharaoh; that is, there’s some actual dude in charge, a god-king.  Ra, by contrast, is “father of the Pharaoh”, the un-look-at-able “power behind the throne.”  Instead of sovereignty that rests in an individual, Ra represents the abstract supreme to which the king is subordinate.

If Horus, the far-sighted, kingly bird, represents “clear brightness” and “being the rightful and just ruler”, then Ra is a sort of fake version of these qualities.  Instead of the light that distinguishes, it’s the light too bright to look at.  Instead of clear brightness, it’s smooth brightness.

Instead of objectivity, excellence, justice, all the “daylight” virtues associated with Horus (what you might also call Apollonian virtues), Ra represents something that’s also shiny and authoritative and has the aesthetic of the daylight virtues, but in an unreal form.

Instead of science, Ra chooses scientism.  Instead of systematization and explicit legibility, Ra chooses an impression of abstract generality which, upon inspection, turns out to be zillions of ad hoc special cases.  Instead of impartial justice, Ra chooses a policy of signaling propriety and eliteness and lack of conflicts of interest. Instead of excellence pointed at a goal, Ra chooses virtuosity kept as an ornament.

(Auden’s version of Apollo is probably Ra imitating the Apollonian virtues. The leadership-oriented, sunnily pragmatic, technological approach to intellectual affairs is not always phony — it’s just that it’s the first to be corrupted by phonies.)

Horus is not Ra.  Horus likes organization, clarity, intelligence, money, excellence, and power — and these things are genuinely valuable. If you want to accomplish big goals, it is perfectly rational to seek them, because they’re force multipliers.  Pursuit of force multipliers — that is, pursuit of power — is not inherently Ra.  There is nothing Ra-like, for instance, about noticing that software is a fully general force multiplier and trying to invest in or make better software. Ra comes in when you start admiring force multipliers for no specific goal, just because they’re shiny.

Ra is not the disposition to seek power for some goal, but the disposition to approve of power and to divert it into arbitrariness. It is very much NOT Machiavellian; Machiavelli would think it was foolish.

Ra corresponds to a stage in the corruption of organizations.

Thomas W. Lamont is an excellent example of Ra.  He was a banker at JP Morgan in the 1930’s who was famously gifted at communication, very much one of the club (Harvard and Exeter), somewhat “idealistic” but in a very vague sense that mostly amounted to rationalizing whatever power structure was nearby.  He ended up making major loans to militarist Japan and Mussolini, and was a major apologist for them right up until the situation became intolerably obvious; at which point without any apparent sense of shame he gave up on them, after making sure his friends were taken care of (e.g. negotiating a Morgan banker’s release from Italian imprisonment).

Lamont’s communication to the Japanese and later to Mussolini was all “I know you mean well but it’s getting harder to defend you, here’s some suggestions for how to clear up the obvious misunderstanding.”  He’s not a cynical power-seeker in these letters; he’s genuinely righteously indignant at people doubting his “ideals.”  There’s no master plan to gain power for himself or for an ideology he supports. He just seems to think “clearly the people gaining power must be good!”

The Lamonts of the world generally show up after the founding generation, after people like J. Pierpont Morgan himself, who was a genuine innovator who developed “modernization” techniques to make the businesses he took over profitable.  Vague objectives are only possible once institutions that steadily produce value have already been set in motion.  You see Ra-like figures at around the peak of an institution’s flourishing, when it’s begun to be possible to capture value without producing any, but before the decline is so severe that overtly exploitative behavior is socially acceptable.  Ra has a quality that’s triumphalist and slightly disconnected from reality — “Our institution is so powerful and wonderful that its proper sphere is the whole world!  And its job is to perpetuate its own flourishing!”

Ra is easy to overcome

As forces in the human psyche go, Ra is a pretty mild one. It’s not a powerful biological drive like aggression, or a difficult-to-treat problem like depression, or a highly optimized energy-saving structure like the standard cognitive biases.

Ra is hard to pin down, but vulnerable to open communication and introspection.  If you can talk and think about what you want, or how you feel, or why you believe what you do, and you don’t dodge the question, Ra will dissolve like mist. The illusion of smooth impersonal perfection doesn’t survive long after you get to know particular human beings. The subjective impression of something being like a vague glowy ball of positive affect doesn’t survive explicit discussion or analysis.  The sensation of total unknowability doesn’t survive the attempt to actually find things out.

It’s so faint and wispy that many people might say “Ra doesn’t have any part in my life!”  And you might be right.  Or it might be hidden in hard-to-find places, in certain questions you don’t ask and tasks you delay starting. It’s very, very rare for people to say “yes, I totally experience these things.”  But if you notice them, and are aware that they don’t make sense, then the fog yields to sunlight.

Cross-Sex Hormone Therapy: Female Hormones

Scope Of Report

For the purposes of this report, we’re looking at cross-gender hormone therapy for assigned-male-at-birth individuals — that is, estrogen and anti-androgens, as they are generally taken by transgender women and others seeking to feminize their bodies.  I’ll look into the evidence for the medical and psychological risks and benefits of these drugs.

Bottom Lines

  • hormone therapy consisting of estrogen and an anti-androgen is mostly safe: the biggest risk is cardiovascular problems
  • the anti-androgen cyproterone acetate is riskier than other anti-androgens: it’s associated with venous thromboembolism, hyperprolactinemia, and possibly impaired mood and cognitive ability. It can be substituted with spironolactone, or in some cases with no anti-androgen at all.
  • hormone therapy for trans women improves mood and agreeableness, reduces gender dysphoria, and has some feminizing effects on appearance
  • hormone therapy does change brain size but doesn’t impair cognitive performance
  • trying to get an “androgynous” outcome by taking anti-androgens without estrogen is a bad idea and does cause cognitive impairment and depression.

Risks of Hormone Therapy: Venous Thromboembolism

The most common risk of hormone therapy in trans women is venous thromboembolism. This is when a blood clot in a vein breaks loose and travels in the blood; if it reaches the lungs it is called a pulmonary embolism and can be very dangerous. About 5% of people with venous thromboembolisms die.[1]

In the largest study, 1076 individuals, the rate of venous thromboembolism is 1%; smaller studies find 5-6% rates.[2]  Some small studies (162 individuals) suggest that transdermal estrogen has less risk of venous thromboembolism than oral estrogen.

The risk of venous thromboembolism is also elevated in hormonal birth control, which, like hormone therapy, contains female hormones.  Current users of estrogen-containing birth control have about double the yearly risk of venous thromboembolism of female non-users. Birth control containing the progestin cyproterone acetate is associated with 1.88x the venous thromboembolism risk of birth control with other progestins.[3]  This is relevant because cyproterone acetate is also an anti-androgen sometimes used in cross-gender hormone therapy; avoiding cyproterone acetate could reduce the risk of venous thromboembolism.

Risks of Hormone Therapy: Osteoporosis

Estrogen is associated with osteoporosis: 25% of 100 transgender women had osteoporosis after more than 10 years of HRT, whereas transgender men did not.[2]

Risks of Hormone Therapy: Hyperprolactinemia

The anti-androgen cyproterone acetate can cause hyperprolactinemia.

High levels of the hormone prolactin can cause symptoms such as breast discharge, erectile dysfunction and reduced libido, infertility, breast growth, decreased body hair and muscle mass, and headaches. (Not all of these may be undesirable for trans women, of course.)  It is not otherwise dangerous, and can be treated with dopamine agonists such as bromocriptine.

In a total of 1109 trans women across six studies, there were elevated prolactin levels in 19.5%. [5]  Trans women on hormone therapy have much higher rates of migraine than the baseline population: 26% out of 50, as opposed to a baseline rate of 6%.  This may be due to higher prolactin levels.[6] 14/47, or 30% of trans women reported new sources of pain after going on hormones, in particular headaches, breast pain, and musculoskeletal pain.[7] This may also be a result of hyperprolactinemia, or it may be related to other hormonal-balance issues (women generally are more pain-sensitive than men.)

Cyproterone acetate increases prolactin levels; spironolactone does not. (p = 0.0002).[8]  Avoiding cyproterone acetate seems likely to reduce the risk of hyperprolactinemia.

Risks of Hormone Therapy: Infertility

Estrogen therapy usually eliminates the production of sperm.  In 7 out of 10 trans women on estrogen, there was no spermatogenesis.[53] A single male given estrogen had a pronounced drop in sperm motility and density by 4 weeks of estrogen treatment, though it did recover after discontinuation of treatment.[54] As of 2009, there have been no studies of restoration of spermatogenesis after prolonged treatment with estrogen. [52]

Benefits of Hormone Therapy: Improved Mood

Hormone treatment (transdermal estradiol + cyproterone acetate) reduced anxiety and depression scores (p < 0.001) in a cohort study of 107 trans women.[16]

Estrogen has a complex relationship to mood even in cis women.  One credible model is that estrogen fluctuations (for example, around the menstrual cycle, or around the start of menopause) cause mood disorders.  Increased vulnerability to depression in women begins with puberty and ends with menopause, though the perimenopause period is associated both with new onset of depression and increased depression symptoms. [17]  For this reason, estrogen supplementation in cis women is sometimes an effective treatment for mood disorders associated with hormone fluctuations. Estrogen has been consistently shown to be effective as a treatment for PMS, for postpartum depression, and for the milder mood problems associated with menopause, but not with severe menopausal depression or non-reproductive-related major depressive disorder.[18]

Higher doses of estrogen, on the other hand, tend to make mood problems in cis women worse. 3 mg estradiol vs. 2 mg estradiol in HRT for perimenopausal women significantly (p < 0.001) increased tension, irritability, and depressed mood, and decreased friendliness. [19] In postmenopausal women treated with 2 mg/day estrogen or placebo for three months, there was no difference in baseline mood, but the estrogen-treated group had stronger negative emotion responses to a social stress test.[20]  Chronic administration of E2 to ovariectomized female rats and mice at much higher than physiologic doses increases anxious and depressive behaviors.[21]  It’s not clear how this translates to trans women, but it may be preferable to err on the side of lower estrogen doses when possible.

The anti-androgen spironolactone is used to treat symptoms of PMS in cis women, such as irritability, depression, feeling of swelling, breast tenderness, and food craving. Unlike other anti-androgens such as cyproterone acetate or finasteride, it has not been connected with negative effects on mood or cognition.[22]

Benefits of Hormone Therapy: Reduced Gender Dysphoria

Cross-hormone therapy resulted in less body uneasiness in trans women, in a study of 125 subjects.[23]  Adolescents (mean age 17) treated vs. rejected for cross-sex hormone therapy had less gender dysphoria at follow-up in both groups, but significantly less in the treated group.  The treated group were more satisfied with their bodies.[24]

Benefits of Hormone Therapy: Higher Agreeableness

Androgen deprivation and estrogen supplementation in males (e.g. treated for prostate cancer) correlates with higher agreeableness on the Big Five personality test.[25]

Benefits of Hormone Therapy: Altered Sexual Patterns

Estrogen treatment inhibits sexual activity, spontaneous erections, and nocturnal penile tumescence.[4]   Androgen deprivation therapy in cis men (as part of treatment for prostate cancer) consistently causes reduced libido and lower frequency of early morning erections, p < 0.0001.[51] However, trans women have no higher rates of hypoactive sexual desire syndrome than cis women[47]; it may simply be that estrogen causes a more female-typical sex pattern.

Benefits of Hormone Therapy: Physical Appearance Changes

Estrogen and anti-androgens reduce hair on the trunk and limbs, but don’t completely remove it on the face; electrolysis or shaving is still usually necessary.[26]

Breast growth is usually present, with a mean hemicircumference of 18 cm after a year of hormone therapy — this is still a few centimeters less than the mean for cis women.[26]  Most trans women are dissatisfied with the final size of their breast development.[30]

Hormone therapy significantly (p < 0.01, Cohen’s d = 1) improved the “physical appearance score” for gender compatibility of transgender people, a composite made of hair, facial hair, larynx, voice, figure, height, skin, hands/feet, muscularity, chin, nose, jaw, speech, and gestures/movement.[27]

Breast growth, redistribution of body fat, and decrease in muscle mass begin at 3-6 months and peak at 2 years; decreased hair growth begins at 6-12 months and peaks at >3 years.[28]

Trans women, compared to cis men, had similar BMI but higher body fat percentage: 29% vs. 21%, p < 0.001. They also had lower grip, biceps, and quadriceps strength (p < 0.001).[29]

Non-Effects of Hormone Therapy: Cognitive Ability

A study of 35 trans men and 15 trans women at the beginning of hormone treatment, as well as 20 control (cis) men and 20 cis women, found that the trans men’s spatial rotation ability increased during 12 weeks of hormone treatment, while the trans women’s spatial rotation ability slightly declined (p < 0.01), from an average score of 101.9 to 98.5, or a 3% drop.  In this study, trans women were treated with with 100 ug/day of ethinyl estradiol and 100 ug/day of cyproterone acetate.[31]

A study of 51 trans people given hormone therapy and 29 cis controls found no effect on cognitive abilities of hormone treatment over the course of a year. Trans women were given 100 ug/day of oral ethinyl estradiol.[32]

A study of 103 trans women, treated with conjugated equine estrogens or ethinyl estradiol, and in some cases cyproterone acetate and/or medroxyprogesterone acetate, found a slight improvement in digit span after going on estrogen (6.70 on estrogen, 6.00 off estrogen), and a slight improvement in a visual recall test after going off estrogen, but mostly found no effect on a large battery of cognitive tests.[34]

The anti-androgens leuprorelin, goserelin, and cyproterone acetate, when given to men with prostate cancer, caused a drop in one or more cognitive tests in 24/50 men randomized to active treatment, compared to none of the men randomized to placebo.[33]  However, when men treated with anti-androgens were subsequently given estrogen, their memory performance improved.[50]

It seems likely that estrogen has little or no effect on cognitive abilities. Cyproterone acetate taken alone has a negative effect on cognition in cis men, and may contribute to a slight drop in spatial rotation ability in the context of hormone therapy for trans women.

Non-Effects of Hormone Therapy: All-Cause Mortality

In a retrospective study of 816 trans women and 293 trans men, all-cause mortality was not different than in the general population.[47]  In a long-term follow-up study of 2236 trans women and 876 trans men, there was no elevated mortality compared to the general population.[49] In a cohort study of 966 trans women and 365 trans men, the trans women group had 51% higher mortality than the general population, due mostly to suicide, cardiovascular disease, AIDS, and drug abuse; but the use of estrogen among trans women was not an independent predictor of mortality generally or of any cause of mortality except for cardiovascular disease. In other words, trans women are an at-risk population for problems like suicide, drug abuse, and AIDS, but hormone users are at no higher risk than non-users.[48]

Neutral Effects of Hormone Therapy: Brain Morphology

Men and women have structural brain differences. Men have larger brain volumes (and smaller ventricles) than women; they have larger hypothalamuses; and they have a higher fraction of white matter relative to gray matter.

In a study of eight trans women and six trans men, receiving estrogen and cyproterone acetate, and testosterone, respectively, as well as 9 cis male and 6 cis female controls, the trans women had significantly reduced brain and hypothalamus volume, while the trans men had significantly increased brain volume.  Brain volume decreased by a mean of 25 mL in trans women, from 1300 mL to 1275 mL, or about a 2% drop, leaving brain volume somewhere between that of cis men and cis women.[35]  Another study, of 15 trans men on testosterone and 14 trans women on estrogen and an anti-androgen, found that testosterone increased cortical thickness while estrogen and anti-androgens decreased it and increased ventricle size.[36]

While brain volume correlates with IQ,[37] and while some studies find slightly higher mean IQ in men than women (about 3.63 IQ points, extrapolated from the differences in SAT scores in a sample of 100,000)[38], the more common position among IQ researchers is that there are no significant sex differences in mean IQ.[39]  It’s not at all clear that hormone therapy’s effect on shrinking brain volume significantly impairs cognition.

Nonstandard Cases of Cross-Gender Hormone Use

Anti-Androgens May Not Be Necessary

Lower estrogen doses (0.625 mg conjugated estrogen daily) without cyproterone acetate, given to trans women, are sufficient to keep estrogen levels in the normal range for premenopausal women.[9]  7/10 trans women on estrogen alone, without anti-androgens, had testosterone levels drop into the normal female range.[10]  Given that anti-androgens, particularly cyproterone acetate, are responsible for many of the negative side effects of hormone therapy, taking estrogen alone may be a lower-risk approach to hormone therapy.

Risks of Anti-Androgens Without Estrogen: Depression and Cognitive Impairment

Men being treated for prostate cancer are regularly given anti-androgens to suppress the tumor. These men experience significantly elevated rates of anxiety and depression. (This is in contrast to trans women given anti-androgens along with estrogen, who generally experience significant psychological benefit.)

Chemical castration in men significantly reduces estrogen and testosterone levels, and causes significant increases in depression and anxiety scores (though generally subclinical.)[11]  Compared to controls, prostate cancer patients treated with anti-androgens had significant drops in spatial reasoning and executive function, more depressed mood and irritability, less energy and vigor.[12]

The anti-androgen finasteride, given to men as a treatment for hair loss, produced depressive symptoms in 64% of users and 0% of controls in responses to an internet survey (though there may be significant response bias in who chooses to take the survey); finasteride users reported sexual dysfunction, problems with attention and memory, anxiety, depression, and suicidality.[13]  An Iranian prospective study on finasteride found that it increased scores on the Beck depression inventory (p < 0.001) and HADS depression scores (p = 0.005)[14]  A meta-analysis of randomized trials found that finasteride increased the rate of erectile dysfunction, with a relative risk of 2.22 compared to placebo.[55]

Cyproterone acetate in men treated for prostate cancer is associated with declines (compared to placebo) in attention and memory.[15]

Tamoxifen

Tamoxifen is an selective estrogen-receptor modulator; its primary use is as a breast cancer drug, but it also prevents gynecomastia related to estrogen or anti-androgen use.[40]  It might in principle be possible that if one combines tamoxifen with estrogen, one can get some of estrogen’s feminizing effects without growing breasts, but I couldn’t find any case studies of this being done successfully.

Tamoxifen taken alone does not have feminizing effects on men.  It increases both serum estrogen and testosterone levels in men, and increases sperm count.[41]

Female Hormone Use in Men

Male cross-dressers do sometimes use female hormones, and in past decades the social concept of “transgender” was less sharp than it is today. In early-1990’s radical contexts, “transgender” was considered an umbrella term that would include transvestites, drag queens, feminine gay men, butch lesbians, and other gender-nonconforming people who would not usually be considered “trans” today.[43]

In a 1992 sample of 1032 male cross-dressers, 43% said they “would like to use” hormones and 9% had used or were using hormones; in a 1972 sample of of 504 male cross-dressers, 50% said they “would like to use” hormones and 9% had used or were using hormones. However, the majority of these people viewed themselves as “a man with a feminine side” rather than “a woman trapped in a man’s body,” and did not plan to live full-time as women.[42]

From a biological standpoint, there’s no strong reason to believe that hormones would have different effects depending on whether they’re taken by a person who identifies as trans or not.  Men given estrogen for medical reasons (coronary heart disease) had similar side effects as trans women do, including breast tenderness and growth, testicular shrinkage, sexual dysfunction, and depression upon discontinuing estrogen,[44] but there was no evidence of psychological disturbance as a result of taking estrogen.[45]

 

References

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[8]Sofer, Yael, et al. “SAT-0111: High Prolactin Levels in Transsexual Women Are Related to the Anti-Androgen Treatment Modality.”

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[11]Almeida, Osvaldo P., et al. “One year follow-up study of the association between chemical castration, sex hormones, beta-amyloid, memory and depression in men.” Psychoneuroendocrinology 29.8 (2004): 1071-1081.

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