On Ohio’s Heartbeat Bill

I think it’s interesting that all of this stuff – transvaginal ultrasounds, making women listen to the heartbeat, the recent Texas law mandating funerary treatment of fetal remains, attempt after attempt at heartbeat legislation, not to mention the protesters with their photos of fingers and toes – does its best to grasp at and run with any physical resemblance between fetuses and fully-developed babies. It’s interesting because it shouldn’t actually matter, legally or morally, if fetuses look like goldfish or gourds or tiny people up to the moment of birth. And yet their resemblance to babies is used again and again in attempts to restrict abortion rights. Why is that? It’s partly because the people doing this stuff think it’s an effective way to guilt women into not getting abortions. But I think it’s also because forcing us, again and again, to encounter and acknowledge the body of the fetus, to focus our attention on its embodiedness, is actually a fairly powerful rhetorical strategy. It’s a way of shifting the discourse, of drawing parallels that slowly push “fetus” into the same meaning space as “person.”

I mention this because, first, I think we on the left should pay more attention in general to what the right does well, if we have any hope of combatting it (I know it’s cathartic to rant about how much they hate women, but I think we need other rhetorical tools in our toolbox as well); and second, the way we act, even when we’re being forced to act that way, can very much shape how we think and what we believe. In addition to fighting tooth and nail to stop bad legislation and protect abortion rights, we should remain aware of this and be crystal clear about the distinctions our camp makes and will continue to make, even as we put on headphones to listen to a heartbeat or fill out funeral forms for an eight-week miscarriage.

Birth control and Foucault

Why do conservatives who have a moral objection to abortion seem so determined to also block access to birth control? Common feminist answers to this include “they hate women” and “they want to punish women for having sex.” While it’s a totally understandable response to these dillweeds, this has always seemed a bit under-powered to me; one can merely hate women (and/or sex) without engaging in this specific strategy. Today, when the latest iteration of this came up, I realized that Foucault’s ideas of governmentality and biopower help us think about a framework in which conservatives might be working.

Governmentality is the idea that modern regimes, and particularly neoliberal ones, outsource much of the governance of their subjects to the subjects themselves, through both state and non-state power structures and institutions (the school, the prison, the medical system) that teach and enable citizens to control and discipline themselves in ways that serve the regime.

To Foucault, population is a central interest of all modern states, and the development of ‘biopower’ – the power to manage populations and the processes of life – requires the administration, organization, regulation and optimization of these processes.

In the context of governmentality and biopower, it makes sense that states have an interest in getting women to control their fertility. Subjects who reproduce at the “right” time and in the “right” ways – for example, in stable marriages with the economic means to provide for all of the child’s needs that the regime has designated the responsibility of the family – produce new subjects who do not usually create special expense or trouble for the state and its institutions.

It seems to me that the positions of US liberals and conservatives on this are fairly similar; both take as given that fertility should be regulated by individuals (or couples) according to their preferences, which are shaped and constrained by society. The end goal is modern, rational, orderly and predictable production of new citizens. The key difference is that conservatives believe that fertility regulation can and should be enacted through abstinence from sex. In this framework, unwanted births become the means of discipline by which women learn to control their sexuality. Provision of free birth control only stops people from learning the discipline they need: to not have sex if they aren’t ready to have a baby. (That this burden falls solely on women does not concern them; it’s simply an artifact of the fact that women have the relevant biological capacity that needs to be brought under control.) To liberals, on the other hand, the free birth control is the tool for the discipline people need.*

In any case, the conservative argument here, though cheaper in the short run, is bad public policy and also wrong. I can only imagine a few things that are less “pro-life” than using babies as human punishments, and that’s only because my state just voted to speed up the death penalty. Also, obviously, people are bad at not having sex.

*I haven’t thought much about whether conservatives in general tend more toward explicit individual self-regulation and liberals to solutions that simplify self-governance as much as possible, but it sounds right.


What life expectancy isn’t, and why

If you are using the following phrases in your writing on life expectancy, you are wrong. Don’t feel bad; almost no one uses this concept correctly, including seasoned science journalists and actual scientists who aren’t trained in demography. What’s worse, there are almost no resources to help you figure it out. Maybe I can be that resource?

Wrong: “the life expectancy for the average [woman/man/person] is…”

Why: because life expectancy is a composite measure that takes current age-specific mortality rates and summarizes them in one handy number. So what it tells us is how long a hypothetical person living their entire remaining life under this year’s mortality conditions would live, not the actual lifespan of any real or “average” person. Both real people, and non-real statistically average people, live each year of their life under a different year’s mortality conditions.

Better: avoid using “the average person” in any form.

Wrong: “A person aged X today (or: born today) can expect to live Y more years”

Why: because life expectancy contingent upon reaching age X is a composite measure that tells how long a hypothetical person who is age X this year would live, if they lived the rest of their life under this year’s mortality conditions. (This is true even if X is 0 – that’s life expectancy at birth.) However, that hypothetical person will actually live the rest of their life under the mortality conditions of next year, then the year after that, then the year after that, etc., until they die. So goes the march of time.

Better: although the very term “life expectancy” sets you up to do this, don’t use any variant of “expect to live.” It is never right.

Not wrong: “life expectancy has improved, which means people are living longer on average” or “life expectancy in country X is higher than in country Y, which means people in country X live longer on average.”

Sorry. At least in popular press, this is pretty much all life expectancy is good for: comparisons of mortality conditions in different times or places. Another bummer is that it obscures the components that make up these differences – for example, you can’t tell just by looking whether an increase in life expectancy is driven by a drop in infant mortality or old-age mortality, fewer infectious diseases or better cardiovascular care.

Important caveat: cohort life expectancy is a measure of how long the average person in a given cohort lived, and almost nothing I’ve said here applies to it. But you can’t calculate it until the whole cohort is dead, so it’s not a measure you encounter very frequently.

And, an N.B.: I wrote this post because I took another look at my previous post on life expectancy and it didn’t seem that clear. But if you don’t find this one very clear, maybe you’ll like the other one better – or you can just bug me on Twitter.

Stable Age Pyramids and Replacement Fertility

Part of my job as a graduate student instructor this term is to answer questions on our class Piazza site. I though I might post some of the answers here as well (since the Piazza is private and will probably be lost to the ether after the semester ends).

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Lecture slide: Viet Nam’s age structure during the demographic transition.

Student question (paraphrased): In lecture, we were asked “Is Viet Nam’s fertility sub-replacement in 2000?” I don’t know how to answer this.

I explained that we can’t tell from the shape of this non-stable age pyramid whether fertility is sub-replacement, only that it’s falling (since the 0-5 cohort is smaller than the 5-10 cohort). The student then clarified that their problem was with the term sub-replacement fertility.

My response:

Oh, okay, sorry for misunderstanding! First we need to understand what a stable population is. A stable population is a population where the proportion of people in each age group stays constant over time, because rates of fertility and mortality in each age group are constant. A stable population can be growing, shrinking, or staying the same size, but whatever it’s doing, it’s doing it at a stable, constant rate. (Stable populations are mathematical ideals, but there are populations in the real world that are close to stability.)

Replacement fertility is the level of fertility needed in a stable population to keep population growth at zero, so the population stays the same size. Above-replacement fertility leads to population growth; sub-replacement fertility leads to population decline.

Numerically, replacement fertility is a total fertility rate (TFR) of 2.1 children per woman. (In populations with lower life expectancy, replacement fertility is higher, because more infants die before they can grow up to have their own children. But 2.1 is the right number to memorize.)

Graphically, a stable age pyramid with replacement fertility and moderate to high life expectancy will tend not to flare out too much at the base, but it also won’t go in. However, the age pyramid for Viet Nam in 2000 is not a stable age pyramid, but an age pyramid for a population that is undergoing changing rates: we can see that women in 2000 are having fewer children than they were a few years ago, because there are more 5-to-10-year-olds than 0-to-5-year-olds. However, we don’t have any information about what the actual level of childbearing is.

It isn’t too important to grasp all the nuances here, but you should know 1) what a stable population is, 2) what the concept of replacement fertility means, and 3) the number 2.1, the TFR for replacement fertility in most contemporary populations. I also encourage you to play around with this app that Prof. Goldstein built, to understand what combinations of life expectancy and fertility lead to positive, negative, and zero (replacement) growth, and what those combinations look like.


Life Expectancy and You (for non-demographers)

It is worth noting, if you use this life expectancy calculator, that the accuracy of your statistical death(??) (“There’s a big difference between statistically dead and all dead! Statistically dead is slightly alive!”) is contingent upon you living out the rest of your life in the year 2015 on repeat, à la Groundhog Day.

Why? Life expectancy as used here is a period measure – it tells us what someone’s average lifespan would be if they were subject to this year’s (or period’s) age-specific mortality rates every year. This might be a good estimation of actual remaining life if mortality rates weren’t changing, but they are.

They aren’t changing that quickly, so an estimate of remaining life for 75-year-olds based on current mortality might not be so far from what we’ll actually see happen to that cohort. But the younger you are, the farther off it’s likely to be. Life expectancy at birth is the wrongest of all. “A boy born now (age 0) can” ABSOLUTELY NOT “expect to live to 76,” despite what WaPo says; not only will mortality patterns change over his lifetime, but we could also talk about whether averages are a good predictor of individual experience.

For example, in this paper by Vladimir Canudas-Romo, Swedish life expectancy improved significantly over the course of the late 19th century, as increased infant survival pulled the average up, but the modal age at death was pretty flat. (Check out Figure 2.) The less variance there is in the age at death – the more we all tend to make it to old ages rather than dying in infancy – the more closely life expectancy at birth will align with median and modal lifespans, but this is a great illustration of what numbers like life expectancy do and don’t tell us.

tl;dr: Any time someone uses “life expectancy” and “how long you can expect to live” together, they are wrong.

The repugnant conclusion

There’s a minor flap going on now about Vox’s decision not to publish a piece on the repugnant conclusion by Swedish philosopher Torbjörn Tännsjö, arguing that we’re morally responsible for having more children (helpfully published by Gawker, for journalistic integrity reasons I’m sure).

I’m very interested in moral arguments for or against childbearing, or rather, in society’s engagement with these arguments. But while I disagree with assessments that the piece itself is stupid, it’s frustrating and not very interesting, and I wouldn’t have published it either.

The problem isn’t that it asks a question we’re interested in and then gives us an answer we don’t want to hear (as the accusation that it’s “upsetting” or “too anti-choice” has it), but that it asks a question we’re interested in, and then gives us a framework for answering it that is so abstracted as to be useless to most of us. That may be good philosophy, but it’s bad journalism and even worse life guidance.

I mean, we could all spend our whole lives on the third paragraph, “see[ing] to it that we do not overpopulate the planet… [by solving] pressing problems such as the one with global warming,” pack up and hike out before ever getting to philosophical questions like, “Would it really be selfish of Adam and Eve not to procreate?” or, “Wait, is total happiness the best measure? What about variance?” or, “Where’s the line between observing that it’s better to have children later and shaming teenage mothers, and why don’t philosophers care about that sort of thing?” Or demographic questions like “What would it look like to profoundly change our reproductive life histories?” or “Could low mortality hold in a highest-high fertility world?” Questions that are not without implication for Tännsjö’s position, I think.

Learning from our elders/locating ourselves in history

This semester, I’m taking an amazing course, Fundamentals of Population Thought, from a social demographer I greatly admire, Jenna Johnson-Hanks. The first day of class was devoted to going over the syllabus, and even this was an intellectually engaging exercise. (Yay!) I was particularly intrigued by two comments she made about the last week of class, which will focus on big data and new frontiers in social demography:

First, she compared Adolphe Quetelet – an astronomer who got into social demography because he happened to live at a time when administrative data on populations was exploding – to our contemporary computer engineers-turned-data scientists. I enjoy the joke that a data scientist is just a statistician with a Mac as much as the next person, but I really liked this comparison, and the implication that a data scientist is actually (often) someone with formal training in a totally different field who is invigorated into doing social science by the times we live in (at least in the optimistic view).

Second, she made a distinction between her generation of social demographers and mine. From about 1985 to 2005, she says, population thinkers were pushing against a prevailing trend in the social sciences toward studying fine-grained connections between covariates at the level of the individual. It hadn’t occurred to me that this is a particular methodological orientation – but of course it is, and this comment immediately illuminated my experience at ICPSR this summer, wherein much of the material assumed this orientation. Although this may still be an assumption at ICPSR (which is dominated by political scientists), the new vogue for big data means that population-level analysis doesn’t have to elbow for a place at the table.

I also thought of this comment this morning when a friend Tweeted, “mixed feelings about anthropology’s absence from the recent rash of “social science is a dumpster fire” pieces.” Maybe part of the reason anthropology (and demography) haven’t been skewered is that run-99-regressions-and-finally-connect-hair-color-and-voting-behavior is what people are laughing at (rightly or not), and that’s not what we do.

Or maybe it’s that no one cares. But if no one cared, we wouldn’t have all these data scientists.