Category Archives: In the news

Why there are 3.1 million extra young adults living at home

Answer: The COVID-19 pandemic.

UPDATE: A new post updates this analysis for July 2020

Catherine Rampell tweeted a link to a Zillow analysis showing 2.2 million adults ages 18-25 moving in with their parents or grandparents in March and April. Zillow’s Treh Manhertz estimates these move-homers would cost the rental market the better part of a billion dollars, or 1.4% of total rent if they stay home for a year.

We now have the June Current Population Survey data to work with, so I extended this forward, and did it differently. CPS is the large, monthly survey that the Census Bureau conducts for the Bureau of Labor Statistics each month, principally to track labor market trends. It also includes basic demographics and living arrangement information. Here is what I came up with.*

Among people ages 18-29, there is a large spike of living in the home of a parent or grandparent (of themselves or their spouse), which I’ll call “living at home” for short. This is apparent in a figure that compares 2020 with the previous 5 years (click figures to enlarge):

six year trends

From February to April, the percentage of young adults living at home jumped from 43% to 48%, and then up to 49% in June. Clearly, this is anomalous. (I ran it back to 2008 just to make sure there were no similar jumps around the time of the last recession; in earlier years the rates were lower and there were no similar spikes.) This is a very large disturbance in the Force of Family Demography.

To get a better sense of the magnitude of this event, I modeled it by age, sex, and race/ethnicity. Here are the estimated share of adults living at home by age and sex. For this I use just June of each year, and compare 2020 with the pooled set of 2017-2019. This controls for race/ethnicity.

men and women

The biggest increase is among 21-year-old men and 20-year-old women, and women under 22 generally. These may be people coming home from college, losing their jobs or apartments, canceling their weddings, or coming home to help.

I ran the same models but broke out race/ethnicity instead (for just White, Black, and Latino, as the samples get small).

white black latino

This shows that the 2020 bounce is greatest for Black young adults (below age 24) and the levels are lowest for Latinos (remember that many Latinos are immigrants whose parents and grandparents don’t live in the US).

To show the total race/ethnic and gender pattern, here are the predicted levels of living at home, controlling for age:

raceth-gender

The biggest 2020 bounce is among Black men and women, with Black men having the highest overall levels, 58%, and White women having the lowest at 44%.

In conclusion, millions of young adults are living with their parents and grandparents who would not be if 2020 were like previous years. The effect is most pronounced among Black young adults. Future research will have to determine which of the many possible disruptions to their lives is driving this event.

For scale, there are 51 million (non-institutionalized) adults ages 18-29 in the country. If 2020 was like the previous three years, I would expect there to be 22.2 million of them living with their parents. Instead there are 25.4 million living at home, an increase of 3.1 million from the expected number (numbers updated for June 2020). That is a lot of rent not being spent, but even with that cost savings I don’t think this is good news.


* The IPUMS codebook, Stata code, spreadsheet, and figures are in an Open Science Framework project under CC0 license here: osf.io/2xrhc.

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What happens next

Wouldn’t you like to know.

“The pandemic has exposed the messiness of science. … We all want answers today, and science is not going to give them. … Science is uncertainty. And the pace of uncertainty reduction in science is way slower than the pace of a pandemic.” —Brian Nosek

Microsoft PowerPoint - games of chance.pptx

click to enlarge

The math of probability is manageable, up to a point. In principle, you could calculate the odds of, for example (clockwise from top left) getting heads on the fake Trump coin, a novel coronavirus linking up to human proteins, surviving a round of Russian roulette, having someone with COVID-19 at your planned event, rolling 6-6-4-8-20 on the dice, have all the marbles fall under a normal curve on a Galton board, and then surviving a flight from New York to Los Angeles without hitting one of the thousands of other planes in the air. But that doesn’t mean we can tell where humanity will be a year from now.

Of course things are always too complicated to predict perfectly, but “normally” we bracket uncertainty and make simplifying assumptions so we can work with forecasts of say, tomorrow’s weather or next quarter’s economic growth — which are strongly bounded by past experience. These are “the models” we live by. The problem now is not that reality has become objectively harder to predict, it’s that the uncertainties in the exercise (those most relevant to our lives) involve events with such catastrophic consequences that a normal level of uncertainty now includes outcomes so extreme that we can’t process them meaningfully.

Once nominally predicable events start influencing each other in complex ways, the uncertainty grows beyond the capacity of simple math. Instead of crunching every possibility, we simplify the assumptions, based on past experience and the outcomes we consider possible. Today’s would-be predictions, however, involve giant centrifugal forces, so that small deviations can lead to disintegration. For example, if the pandemic further tanks the economy, which provides more unemployed people to populate mass protests, leading to more military crackdown and turning more people against Trump, it might make him lash out more at China, and then they might not share their vaccine with us, and an epidemic wave could overwhelm the election and its aftermath, giving Trump a pretext for nullifying the results. And so on.

To make matters more ungraspable, we personally want to know what’s going on at the intersection of micro and macro forces, where we don’t have the data to use even if we knew what to do with it.

Examples

For example, as individuals try to ballbark their own risks of covid-19 infection, and the likelihood of a serious outcome in that event — given their own health history — they might also want to consider whether they have been exposed to tear gas at the hands of police or the military, which might increase the chance of infection. In that case, both the individual and the state are acting without quantifiable information on the risks. For another example, Black people in America obviously have a reasonable fear of police violence — with potentially immeasurable consequences — but taking the risk to participate in protests might contribute to political changes that end up reducing that risk (for themselves and their loved ones). The personal risks are affected by policy decisions and organizational practices, but you can’t predict (much less control) the outcomes.

Individual risks are affected by group positions, of course, creating diverging profiles that splinter out to the individual level. Here’s an example: race and widowhood. We all know that as a married couple ages, the chance that one of the partners will die increases. But that relationship between age and widowhood differs markedly between Blacks and Whites, as this figure shows:

widowhood probability

Before age 70, the annual probability of a Black woman being widowed is more than twice the chance that White women face. (After that, the odds are higher, but not as dramatically so.) Is this difference big enough to affect people’s decision making, their emotions, their relationships? I think so, though I can’t prove it. Even if people don’t map out the calculation at this level (though they of course think about their own and their partner’s specific health situation), it’s in there somewhere.

For most people, widowhood presents a pretty low annual probability of a very bad event, one that might turn your life upside down. On the other hand, climate change is certain, and observable over the course of a contemporary adult’s lifetime (look at the figure below, from 1980 to 2020). But although climate change presents potentially catastrophic consequences, the risks aren’t easily incorporated into life choices. If you’re lucky, you might have to think about the pros and cons of owning beachfront property. Or you could be losing a coal job, or gaining a windmill job. But I think for most people in the U.S. it’s in the category of background risk — which might motivate political participation, for example, but doesn’t hang over one’s head as a sense of life-threatening risk.

temperature anonamlies trend

If not imminent fear, however, climate change undoubtedly contributes to a climate of uncertainty about the future. Interestingly, there is a robust debate about whether and how climate change is also increasing climate variability. Rising temperatures alone would create more bad storms, floods, and droughts, but more temperature fluctuation would also have additional consequences. I was interested to read this paper which showed models predicting greater change in temperature variability (on the y-axis) for the rest of the century in countries with lower per-capita income (x-axis). When it comes to inequality, it rains and it pours. And for people in poorer countries of the world, it’s raining uncertainty.

tempvar

What comes next

I wrote about unequal uncertainties in April, and possible impacts on marriage rates, and I’ve commented elsewhere on fertility and family violence. But I’m not making a lot of predictions. Are other social scientists? My impression they’re mostly wisely holding off. My sense is also that this may be part of a longer-term pattern, where social scientists once made more definitive predictions with less sophisticated models than we do now that we’re buried in data. Is it the abundance of data that makes predicting seem like a bad business? I don’t think that’s it. I think it’s the diminished general confidence in the overall direction of social change. Or maybe predictions have just become more narrow — less world revolution and more fourth quarter corn prices.

One of the books I haven’t written yet, crappily titled Craptastic when I pitched it in 2017, would address this:

My theory for Craptastic is that the catastrophic thinking and uncontrollable feelings of impending doom go beyond the very reasonable reaction to the Trump shitshow that any concerned person would have, and reflect a sense that things are turning around in a suddenly serious way, rupturing what Anthony Giddens describes as the progress narratives of modernity people use to organize their identities. People thought things were sort of going to keep getting better, arc of the moral universe and all that, but suddenly they realize what a naive fantasy that was. It’s not just terrible, it’s craptastic. …

I suspect that if America lives to see this chapter of its decline written, Trump will not be as big a part of the story as it seems he is right now. And that impending realization is one reason for the Trump-inspired dysphoria that so many people are feeling.

Social science is unlikely anytime soon to be the source of reassurance about the future some people might be looking for — not even the reassurance that things will get better, but just confidence that we know what direction we’re headed, and at what speed. I don’t know, but if you know, feel free to leave it in the comments. (Which are moderated.)

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Rural COVID-19 paper peer reviewed. OK?

Twelve days ago I posted my paper on the COVID-19 epidemic in rural US counties. I put it on the blog, and on the SocArXiv paper server. At this writing the blog post has been shared on Facebook 69 times, the paper has been downloaded 149 times, and tweeted about by a handful of people. No one has told me it’s wrong yet, but not one has formally endorsed it yet, either.

Until now, that is. The paper, which I then submitted to the European Journal of Environment and Public Health, has now been peer reviewed and accepted. I’ve updated the SocArXiv version to the journal page proofs. Satisfied?

It’s a good question. We’ll come back to it.

Preprints

The other day (I think, not good at counting days anymore) a group of scholars published — or should I say posted — a paper titled, “Preprinting a pandemic: the role of preprints in the COVID-19 pandemic,” which reported that there have already been 16,000 scientific articles published about COVID-19, of which 6,000 were posted on preprint servers. That is, they weren’t peer-reviewed before being shared with the research community and the public. Some of these preprints are great and important, some are wrong and terrible, some are pretty rough, and some just aren’t important. This figure from the paper shows the preprint explosion:

F1.large

All this rapid scientific response to a worldwide crisis is extremely heartening. You can see the little sliver that SocArXiv (which I direct) represents in all that — about 100 papers so far (this link takes you to a search for the covid-19 tag), on subjects ranging from political attitudes to mortality rates to traffic patterns, from many countries around the world. I’m thrilled to be contributing to that, and really enjoy my shifts on the moderation desk these days.

On the other hand some bad papers have gotten out there. Most notoriously, an erroneous paper comparing COVID-19 to HIV stoked conspiracy theories that the virus was deliberately created by evil scientists. It was quickly “withdrawn,” meaning no longer endorsed by the authors, but it remains available to read. More subtly, a study (by more famous researchers) done in Santa Clara County, California, claimed to find a very high rate of infection in the general population, implying COVID-19 has a very low death rate (good news!), but it was riddled with design and execution errors (oh well), and accusations of bias and corruption. And some others.

Less remarked upon has been the widespread reporting by major news organizations on preprints that aren’t as controversial but have become part of the knowledge base of the crisis. For example, the New York Times ran a report on this preprint on page 1, under the headline, “Lockdown Delays Cost at Least 36,000 Lives, Data Show” (which looks reasonable in my opinion, although the interpretation is debatable), and the Washington Post led with, “U.S. Deaths Soared in Early Weeks of Pandemic, Far Exceeding Number Attributed to Covid-19,” based on this preprint. These media organizations offer a kind of endorsement, too. How could you not find this credible?

postpreprint

Peer review

To help sort out the veracity or truthiness of rapid publications, the administrators of the bioRxiv and medRxiv preprint servers (who are working together) have added this disclaimer in red to the top of their pages:

Caution: Preprints are preliminary reports of work that have not been certified by peer review. They should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.

That’s reasonable. You don’t want people jumping the gun on clinical decisions, or news reports. Unless they should, of course. And, on the other hand, lots of peer reviewed research is wrong, too. I’m not compiling examples of this, but you can always consult the Retraction Watch database, which, for example, lists 130 papers published in Elsevier journals in 2019 that have been retracted for reasons ranging from plagiarism to “fake peer review” to forged authorship to simple errors. The database lists a few peer-reviewed COVID-19 papers that have already been retracted as well.

This comparison suggests that the standard of truthiness cannot be down to the simple dichotomy of peer reviewed or not. We need signals, but they don’t have to be that crude. In real life, we use a variety of signals for credibility that help determine how much to trust a piece of research. These include:

  • The reputation of the authors (their degrees, awards, twitter following, media presence)
  • The institutions that employ them (everyone loves to refer to these when they are fancy universities reporting results they favor, e.g., “the Columbia study showed…”)
  • Who published it (a journal, an association, a book publisher), which implies a whole secondary layer of endorsements (e.g., the editor of the journal, the assumed expertise of the reviewers, the prestige or impact factor of the journal as a whole, etc.)
  • Perceived conflicts of interest among the authors or publishers
  • The transparency of the research (e.g., are the data and materials available for inspection and replication)
  • Informal endorsements, from, e.g., people we respect on social media, or people using the Plaudit button (which is great and you should definitely use if you’re a researcher)
  • And finally, of course, our own assessment of the quality of the work, if it’s something we believe ourselves qualified to assess

As with the debate over the SAT/GRE for admissions, the quiet indicators sometimes do a lot of the work. Call something a “Harvard study” or a “New York Times report,” and people don’t often pry into the details of the peer review process.

Analogy: People who want to eat only kosher food need something to go on in daily life, and so they have erected a set of institutional devices that deliver such a seal (in fact, there are competing seal brands, but they all offer the same service: a yes/no endorsement by an organization one decides to trust). The seals cost money, which is added to the cost of the food; if people like it, they’re willing to pay. But, as God would presumably tell you, the seal should not always substitute for your own good judgment because even rabbis or honest food producers can make mistakes. And in the absence of a good kosher inspection to rely on altogether, you still have to eat — you just have to reason things through to the best of your ability. (In a pinch, maybe follow the guy with the big hat and see what he eats.) Finally, crucially for the analogy, anyone who tells you to ignore the evidence before you and always trust the authority that’s selling the dichotomous indicator is probably serving their own interests as least as much as they’re serving yours.

In the case of peer review, giant corporations, major institutions, and millions of careers depend on people believing that peer review is what you need to decide what to trust. And they also happen to be selling peer review services.

My COVID-19 paper

So should you trust my paper? Looking back at our list, you can see that I have degrees and some minor awards, some previous publications, some twitter followers, and some journalists who trust me. I work at a public research university that has its own reputation to protect. I have no apparent way of profiting from you believing one thing or another about COVID-19 in rural areas (I declared no conflicts of interest on the SocArXiv submission form). I made my data and code available (even if no one checks it, the fact that it’s there should increase your confidence). And of course you can read it.

And then I submitted it to the European Journal of Environment and Public Health, which, after peer review, endorsed its quality and agreed to publish it. The journal is published by Veritas Publications in the UK with the support of Tsinghua University in China. It’s an open access journal that has been publishing for only three years. It’s not indexed by Web of Science or listed in the Directory of Open Access Journals. It is, in short, a low-status journal. On the plus side, it has an editorial board of real researchers, albeit mostly at lower status institutions. It publishes real papers, and (at least for now) it doesn’t charge authors any  publication fee, it does a little peer review, and it is fast. My paper was accepted in four days with essentially no revisions, after one reviewer read it (based on the summary, I believe they did read it). It’s open access, and I kept my copyright. I chose it partly because one of the papers I found on Google Scholar during my literature search was published there and it seemed OK.

So, now it’s peer reviewed.

Here’s a lesson: when you set a dichotomous standard like peer-reviewed yes/no and tell the public to trust it, you create the incentive for people to do the least they can to just barely get over that bar. This is why we have a giant industry of tens of thousands of academic journals producing products all branded as peer reviewed. Half a century ago, some academics declared themselves the gatekeepers of quality, and called their system peer review. To protect the authority of their expertise (and probably because they believed they knew best), they insisted it was the standard that mattered. But they couldn’t prevent other people from doing it, too. And so we have a constant struggle over what gets to be counted, and an effort to disqualify some journals with labels like “predatory,” even though it’s the billion-dollar corporations at the top of this system that are preying on us the most (along with lots of smaller scam purveyors).

In the case of my paper, I wouldn’t tell you to trust it much more because it’s in EJEPH, although I don’t think the journal is a scam. It’s just one indicator. But I can say it’s peer reviewed now and you can’t stop me.

Aside on service and reciprocity: Immediately after I submitted my paper, the EJEPH editors sent me a paper to review, which I respect. I declined because it wasn’t qualified, and then they sent me another. This assignment I accepted. The paper was definitely outside my areas of expertise, but it was a small study quite transparently done, in Nigeria. I was able to verify important details — like the relevance of the question asked (from cited literature), the nature of the study site (from Google maps and directories), the standards of measurement used (from other studies), the type of the instruments used (widely available), and the statistical analysis. I suggested some improvements to the contextualization of the write-up and recommended publication. I see no reason why this paper shouldn’t be published with the peer review seal of approval. If it turns out to be important, great. If not, fine. Like my paper, honestly. I have to say, it was a refreshing peer review experience on both ends.

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How big will the drop in weddings be? Big

With data snapshot addendum at the end.

In the short run, people are canceling their weddings that were already booked, or not planning the ones they were going to have this summer or fall. In the long run, we don’t know.

To look at the short run effect, I used Google Trends to extract the level of traffic for five searches over the last five years: wedding dressesbridal shower, wedding licensewedding shower, and wedding invitations (here is the link to one, just change the terms to get the others). These are things you Google when you’re getting married. Google reports search volume for each term weekly, scaled from 0 to 100.

Search traffic for these terms is highly correlated with each other across weeks, between .45 and .76. I used Stata to combine them into an index (alpha = .92), which ranges from 22 to 87 for 261 weeks, from May 2015 to last week.

For the graph, I smoothed the trend with a 5-week average. Here is the trend, with dates for the peaks and troughs (click to enlarge):

wedding plans searches.xlsx

The annual pattern is very strong. Each year people people do a lot of wedding searches for about two months, from mid-January to early-March, before traffic falls for the rest of year, until after Thanksgiving. There is a decline over these five years, but I don’t put too much stock in that because maybe the terms people use are changing over time.

But this year there is a break. After starting out with a normal spike in mid-January, searches lurched downward into February, and then collapsed to their lowest level in five years — at what should have been the height of the wedding Google search season.

Clearly, there will be a decline in weddings this spring and summer, or until we “reopen,” whatever that means. A lot of people just can’t get married. When you think about the timing of marriage, most people getting married in a given year are probably already planning to at least half a year in advance. So even if no one’s relationships are affected, and their long term plans don’t change, we’ll still see a decline in marriages this year just from canceled plans.

Beyond that, however, people probably aren’t meeting and falling in love as much. People who are dating probably aren’t as likely to advance their relationships through what would have been a normal development – dating, love, kids, marriage, and so on. So a lot of existing relationships – even for people who weren’t engaged – probably aren’t moving toward marriage. Even if they get back on track later, that’s a delay of a year or two or however long. This says nothing about people being stressed, miserable, sick (or worse), and otherwise not in any kind of mood.

In the longer term, what does the pandemic mean for confidence in the future? The crisis will undermine people’s ability to make long term decisions and commitments. Unless the cultural or cognitive model of marriage changes, insecurity or instability will mean less marriage in the future. This could be a long term effect even after the acute period passes.

What about a rebound? Eventually – again, whenever that is – there probably will be some rebound. At least, just practically, some people who put off marriage will go ahead and do it later. Although, as with delayed births, some postponed marriages probably will end up being foregone. On a larger scale, when people can get out and get together and get married again, there might well be a marriage bounce (and also even a baby boom). Presumably that would depend on a very positive scenario: a vaccine, an economic resurgence, maybe a big government boost, like after WWII. A surge in optimism about the future, happiness. That’s all possible. This also depends on the cultural model of marriage we have now, so that good times equals more marriage (and childbearing). In real life, any such effect might be small, dwarfed by big declines from chaos, fear, and uncertainty. I can’t predict how these different impulses might play against each other. However, on balance, my out-on-a-limb forecast is a decline in marriage.

kissing sailor

Data snapshot addendum

I didn’t realize there was monthly data available already. For example, in Florida they release monthly marriage counts by county, and they have released the April numbers. These show a 1% increase in marriages year-over-year in January, a 31% increase in February, then a 31% drop in March and a 72% drop in April [Since I first posted this, Florida added 477 more marriages in April, and a few in the earlier months, changing these percentages by a couple points as on June 5. -pnc.] Here is a scatter plot [updated] showing the count of marriages by county in 2019 and 2020. Counties below the diagonal have fewer marriages in 2020 than they did in 2019. Not surprising, but still dramatic to see it happening in “real time” (not really, just in quickly available data).

florida marriages.xlsx

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COVID lecture for Social Problems class

On March 2, I opened up my Social Problems class to questions on the emerging coronavirus epidemic. One of the things I did was show them a graph of worldwide cases on a log scale, and told them that it implied the world would have a million cases a month later. We hit that number to the day two days ago. Here are my notes from that day:

A month later, with school indeed canceled (which I had given only a 10-20% on March 2, I recorded this 28-minute lecture for them as an update. Feel free to use any part of it any way you like*:


* Two notes, having watched it over myself and gotten some feedback:

  1. At 4:40 I said of the graph shown: “The number of new cases confirmed by testing, every day, in the country, since February.” I should have said, “in the world” (as the figure is labeled).
  2. It’s been pointed out that social distancing and other responses to the outbreak are not the only thing that differentiate trajectories of the different outbreaks around the country. Also relevant is the demography of the area, including age, as well as health status and healthcare infrastructure. Those factors will emerge as the pandemic matures.

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Very important social scientist says — wait, Brad Wilcox did what now?

Last year Brad Wilcox gave a talk at Saint Vincent College, a monastic college just 8 minutes from the glass-lined tanks of old Latrobe. The talk was structured as a critique of Stephanie Coontz and her decadent view that marriage should be freely chosen.

I was skipping through it looking for his current definition of the “Gold Standard” family (“intact, married, biological family”), when I found this amazing piece of sophistry masquerading as incompetence (or maybe the other way around, hard to know). To lighten things up around here, I thought I’d share it.

This is the clip (It’s here on the full video), followed by the transcript:

Stephanie Coontz, who is a very prominent, progressive author, writer and scholar, has argued that ‘marriage has become more joyful, more loving, more satisfying.’ So what’s the evidence tell us about what actually happened? Well, looking just at those folks who were married, from the 70s to the 80s, and the 90s, and actually the 2000s [he’s looking up at his own graph here], there’s no evidence that marriage is becoming more joyful or more loving among those folks who managed both to get married, and in this case, to remain married. So we see a decline. It’s actually particularly precipitous for women, from the 70s to the 2000s. And when you factor in the fact that fewer and fewer folks were getting married, that’s particularly interesting. What’s this is telling us is that a smaller and smaller share of American adults both men and women were in a very happy marriage from the 70s to the 2000s. So, I don’t think there’s a lot of evidence to sort of back up her idea that sort this newer, post-70s model, this more contingent model, was more successful.

Here’s a screengrab of the slide he’s looking at:

urkiddingbrad

Wow, that sure makes it seem like the percent of adults in a very happy marriage is a lot lower than it used to be, although rebounding strongly this decade. It also just doesn’t look anything like the many graphs of marital happiness I have seen, and made, from the General Social Survey, which is the data he’s using here. So, how exactly is Brad Wilcox completely wrong this time?

Two amazingly incompetent and/or disingenuous ways. First, he included people who aren’t married in his denominator, so the decline in “happy marriage” he shows is due to the decline in marriage altogether, not to any change within marriage. That’s like saying the percentage of people who love reading handwritten parchment scrolls has plummeted since the Middle Ages.

Second, that huge drop in the 2000s he shows is entirely due to the fact that most people weren’t asked the question in survey years 2002, 2004, and 2006, and he included them as not in “very happy” marriages. Brad could just as accurately have said the 19,000 happily married people in the GSS are the only happily married people on earth.

Here is the actual trend, with what he showed (which is trivially easy to reconstruct), showing the individual years instead of the decade grouping he used:

urkiddingbrad-twolines

I can’t think of something better to say than just showing this. (I didn’t bother with the gender breakdown, which isn’t the point.)

I hope this helps. Please stay at home if you can, and support those who can’t stay home as best you can.


Update: Stephanie Coontz writes on Facebook:

Thanks to Philip Cohen for showing how Brad Wilcox misuses data to criticize my claim that modern marriages are “more loving, more satisfying” than in the past. What I actually say is that when they work WELL, modern marriages are more intimate, fair & loving than marriages of the past. When they DON’T work well, they are more disappointing and seem less bearable because of our higher expectations. This makes our current crisis especially challenging, because we have to expect more of our partners, and can expect less from others, than usual.

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COVID-19 graphs, with data and code

Updated March 25.

Although I’m not an expert on pandemic analysis, I am naturally following the COVID-19 data as best I can. And because I always understand data better when I make the figures myself, I’ve been making and looking at COVID-19 trend data, and sharing it as I go.

The figures below are the latest I made as of March 18 25 29, but you can click on the images to link to the current version. The figures, as well as data files and code, are in an Open Science Framework project, here: osf.io/wd2n6/, under CC0 license (free to use for any purpose). The project updates automatically as I go, but these figures won’t (because this is an old fashioned blog).

First, across countries:

country cases and deaths

For this one, to put the diverse US in perspective, in included US states in addition to selected countries. These are deaths.

countries and states since 10 deaths

State cases and deaths, per capita:

state cases and death rates bar

Finally, one with commentary: The first month, in numbers and Trump’s winning words:

Microsoft PowerPoint - first month of winning coronavirus.pptx

 

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11 trends for your New Decade’s holiday party

There’s a lot to do this decade, and only a few days to do it. You need to look smart doing it. The best way to look smart is to be smart, and that means ingesting meaningful bits of data and turning them into useful knowledge. When you display data bits at a holiday party, they merge with those from the other people there, to become the common knowledge we need to get things done in the next decade, which we will do.

So here are a few meaningful bits of demographic data, presented with trend lines and easy-to-memorize fact statements. These aren’t the most important or most interesting demographic trends of the decade, but they’re all meaningful and readily interpretable — plus I was able to gather them on short notice between other last-minute decadal deadlines. Feel free to add your own in the comments.

Notes: We don’t have data through the end of the decade for all of these, so I just present the latest data. And I extend them back toward 1999 as far as I can for context. And I scaled them to show the change as clearly as possible, so watch out for y-axes that are compressed to the active range rather than starting at zero (file complaints here). If I don’t specify the time frame in the text, it refers to the last 10 years of data.

So just memorize the facts that interest you, and remember the associated images. Here goes.


Overdose deaths increased more than 80 percent.

od


Chlamydia cases increased by a third.

chlamydia


One-in-six 25-34 year-olds live with their parents

livhome


The share of college graduates majoring in sociology or history fell by more than a third.

histsoc


The percentage of new mothers who are married has risen back over two-thirds.

marbirth


For the first time in decades women over 40 may soon be more likely to have a baby than teenagers.

fertage


The divorce rate has fallen 20 percent.

divorce


People with college degrees are 19 percent more likely to be married than people without.

margap


International adoptions fell by more than two-thirds.

intadopt


Refugee admissions are at their lowest level since before 1980, and falling fast.

refugee


The newspaper industry was cut in half.

news


Happy New Decade!

 

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ASA’s letter against the public interest and our values

youdidwhat

Update 1: I submitted a resolution to the ASA Committee on Publications, for consideration at our January meeting. You can read and comment on it here.

Update 2: The Committee on Publications on January 23 voted to approve the following statement: “The ASA Committee on Publications expresses our opposition to the decision by the ASA to sign the December 18, 2019 letter.”

The American Sociological Association has signed a letter that profoundly betrays the public interest and goes against the values that many of us in the scholarly community embrace.

The letter to President Trump, signed by dozes of academic societies, voices opposition to a rumored federal policy change that would require federally funded research be made freely available upon publication, rather than according to the currently mandated 12-month embargo — which ASA similarly, bitterly, opposed in 2012. ASA has not said who made the decision to sign this letter. All I know is that, as a member of the Committee on Publications, I wasn’t consulted or notified. I don’t know what the ASA rules are for issuing such statements in our name, but this one is disgraceful.

The argument is that ASA would not be able to make money selling research generated by federal funding if it were required to be distributed for free. And because ASA would suffer, science and the public interest would suffer. Like when Trump says getting Ukraine to help him win re-election is by definition in the American interest — what helps ASA is what’s good for science.

The letter says:

Currently, free distribution of research findings is subject to a 12-month embargo, enabling American publishers to recover the investment made in curating and assuring the quality of scientific research content. … The current 12-month embargo period provides science and engineering society publishers the financial stability that enables us to support peer review that ensures the quality and integrity of the research enterprise.

That is funny, because in 2012 ASA director Sally Hillsman (since retired) said the 12-month embargo policy “could threaten the ability of scholarly societies, including the ASA, to continue publishing journals” and was “likely to seriously erode and eventually jeopardize our financial ability to perform the critical, value added peer review and editorial functions of scientific publishing.”

The current letter, at least with regard to ASA, tell this whopper: “we support open access and have a strong history of advancing open access through a broad array of operational models.” They literally oppose open access, including in this letter, and including the current, weak, open access policy.

The ASA-signed letter is very similar to one sent about the same time by a different (but overlapping) large group of publishers, including Elsevier, and the U.S. Chamber of Commerce, claiming the rumored policy would hurt ‘merica. But there are subtle differences. The ASA letter refers to “the current proven and successful model for reporting, curating and archiving scientific results and advancing the U.S. research enterprise,” which should not be tampered with. The other letter warns of the danger of “step[ing] into the private marketplace” in which they sell research. Knowledge philosopher Peter Suber offered an excellent critique of the market claims here in this Twitter thread:

ASA and the other money-making societies really want you to believe there is no way to do curation and peer review without them. If we jeopardize their business model, ASA says, the services they provide would not happen. In fact, the current subscription models and paywalls stand in the way of developing the cheaper, more efficient models we could build right now to replace them. All we need to do is take the money we currently devote to journal subscriptions and publisher profits, and redirect it to the tasks of curation and peer review without profits and paywalls — and free distribution (which is a lot cheaper to administer than paywalled distribution).

The sooner we start working on that the better. In this effort — and in the absence of leadership by scholarly societies — the university libraries are our strongest allies. This is explained by UNC Librarian Elaine Westbrooks in this Twitter thread:

Compare this forwarding thinking librarian’s statement with Elsevier. In proudly sharing the publishers’ statement, Elsevier vice president Ann Gabriel said, “Imagine a world without scientific, medical societies and publishers who support scholarship, discovery and infrastructures for peer review, data archiving and networks.” Notice two things in this statement. First, she does not mention libraries, which are the academy-owned institutions that do literally all this as well. And second, see how she bundles publishers and societies. This is the sad reality. If instead of “societies and publishers” we had “societies and libraries” maybe we’d be getting somewhere. Instead, our societies, including the American Sociological Association, are effectively captured by publishers, and represent their interests instead of the public interest, and the values of our community.

I remain very pessimistic about ASA, which is run by a professional group with allegiance to the paywall industry, along with mostly transient, naive, and/or ineffectual academics (of which I am certainly one). But I’m torn, because I want to see a model of scholarly societies that works, which is why I agreed to serve of the ASA Committee on Publications — which mostly does busy work for the association while providing the cover of legitimacy for the professional staff.

Letter of opposition

So I posted a letter expressing opposition to the ASA letter. If you are a sociologist, I hope you will consider sharing and signing it. We got 100 signatures on the first day, but it will probably take more for ASA to care. To share the letter, you can use this link: https://forms.gle/ecvYk3hUmEh2jrETA.

It reads:

In light of a rumored new White House Open Access Policy, the American Sociological Association (ASA), and other scholarly societies, signed a letter to President Trump in support of continued embargoes for federally-funded research.

We are sociologists who join with libraries and other advocates in the research community in support of federal policy to make the results of taxpayer-funded research immediately available to the public for free. We endorse a policy that would eliminate the current 12-month waiting period for open access to the outputs of taxpayer-funded scientific research. Ensuring full open access to publicly-funded research contributes to the public good by improving scientific productivity and equalizing access — including international access — to valuable knowledge that the public has already paid for. The U.S. should join the many other countries that already have strong open access policies.

We oppose the decision by ASA to sign this letter, which goes against our values as members of the research community, and urge the association to rescind its endorsement, to join the growing consensus in favor of open access to to scholarship, including our own.

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The continuation of babies

There is no guarantee that a happy, healthy, equal, and harmonious population wants to produce enough children to maintain or grow its total size.

Anna Louie Sussman wrote an essay in the New York Times, given the unfortunate title “The End of Babies” (about which more below). I like a lot of it, and I have substantial disagreements with the framing.

It’s about falling fertility and capitalism. This is a great summary, though I would replace “not necessarily a bad thing” with “usually a very good thing”:

Declining fertility typically accompanies the spread of economic development, and it is not necessarily a bad thing. At its best, it reflects better educational and career opportunities for women, increasing acceptance of the choice to be child-free, and rising standards of living.

At its worst, though, it reflects a profound failure: of employers and governments to make parenting and work compatible; of our collective ability to solve the climate crisis so that children seem a rational prospect; of our increasingly unequal global economy. In these instances, having fewer children is less a choice than the poignant consequence of a set of unsavory circumstances.

Sussman sees the “bigger picture” as this:

Our current version of global capitalism … has generated shocking wealth for some, and precarity for many more. These economic conditions generate social conditions inimical to starting families: Our workweeks are longer and our wages lower, leaving us less time and money to meet, court and fall in love. Our increasingly winner-take-all economies require that children get intensive parenting and costly educations, creating rising anxiety around what sort of life a would-be parent might provide. A lifetime of messaging directs us toward other pursuits instead: education, work, travel.

This paragraph uses a sort of 1% versus 99% framing with is exaggerated but not unreasonable. This, however, is just exaggerated:

It seems clear that what we have come to think of as “late capitalism” — that is, not just the economic system, but all its attendant inequalities, indignities, opportunities and absurdities — has become hostile to reproduction. Around the world, economic, social and environmental conditions function as a diffuse, barely perceptible contraceptive.

Lost in this, by now, is all the good parts about falling fertility mentioned previously. Remember, contraceptives are good, and most people use them deliberately to help control their lives, and they do it because social and environmental conditions have made it possible to have more control over one’s life than ever before, while offering unprecedented opportunities for women beyond child-rearing.

In short, I agree with Sussman’s description of how some people in rich societies would like to have more children than they do, I just don’t think it’s anything like a universal or even general experience in our era. And there is a puzzle confounding the premise: within rich countries, or at least the USA, privileged people, who presumably have more control over their lives and destinies, still have fewer children than those who are more powerless. I once wrote:

There is an argument that Americans are having fewer children than they want to because of our stone age work-family policies, especially poor family leave support and the high costs of good childcare. I’m sure that’s happening to some degree, but it’s still the case that more privileged people, who should be able to overcome those things more readily — people with college degrees and Whites — have lower fertility rates than people who are getting squeezed more.

Like a lot of work in this area, Sussman’s assessment that people want more children — which generates the image of the “reproductive malaise [that] has settled over,” in this case, Denmark — is based on surveys showing people’s “ideal” family size is larger than the average number of children actually born per family. But the interpretation of this gap is not so straightforward. Maybe people think three is the ideal number of children, but they also think a PhD is the ideal amount of education, and so they compromise, with some having one kid and a PhD, and some having three kids and a no college degree. This is an empirical question. What’s historically unprecedented and still so new that we don’t know what to make of it socially is the fact that this is a choice at all for so many people.

As I previously reported, the proportion of US women whose “ideal” number of children is higher than they number they had by age 40 has risen, from less than 15% among women born in the 1930s to almost a quarter for women born in the early 1970s. If you break that trend down by BA/no-BA education level, you can see that women with BA degrees are pushing it upward:

ideal fam size gss ba

So maybe college graduate women are having fewer than their ideal number of children like I’m earning less than the ideal amount of money — I think I could be making more money, but then I wouldn’t be able to sit around in my pajamas blogging with my dog, so I compromise. Of course, like some of the people in Sussman’s piece, a lot of people are justifiably unhappy about this, feeling they can’t compromise between forces pulling them in opposite directions. And so the result is dissatisfaction, maybe even malaise. I just don’t think we know how many people feel that way, or even whether the feeling is much more prevalent than it used to be.

Denmark

Sussman uses Denmark as one case study. This is her summary:

If any country should be stocked with babies, it is Denmark. The country is one of the wealthiest in Europe. New parents enjoy 12 months’ paid family leave and highly subsidized day care. Women under 40 can get state-funded in vitro fertilization. But Denmark’s fertility rate, at 1.7 births per woman, is roughly on par with that of the United States. A reproductive malaise has settled over this otherwise happy land.

But where is the evidence for this malaise? Denmark’s fertility rate has been low and relatively stable, while it is the USA’s that has plummeted since 2007, which is why the countries are now at the same level. The malaise that is settling is here — Denmark’s has already settled.

To elaborate on Denmark: There was a rapid drop in fertility from the mid-1960s through the mid-1980s, followed by a rebound, and then relative stability for about 25 years. During that time, as the population continued to grow slowly, women were reaching age 40 with between 1.8 and 1.9 children on average. Rather than slipping into a chasm, it looks more like the affluent people of Denmark have settled into a moderately low-fertility regime.

denmark.xlsx

“Replacement” fertility, of about 2.1 births per woman, doesn’t mean a society is healthy or happy. Maybe late capitalism with a decent welfare state is not “hostile to reproduction,” maybe it just doesn’t quite get to 2.1.

How bad is that? Like the USA (see my last projections), Denmark will have population decline if they keep on this path, discounting immigration. Because they have been at low fertility for a while, the country is close to seeing actual decline based on birth rates alone. Here is what would happen over the next hundred years if current trends persist and there are no immigrants: The population would eventually contract 31%.

denmark.xlsx

A 31% population drop a century from now would make for a pretty different Denmark (as will another few feet of sea-level rise). But there is time to get there — the drop would only be 6% in the next three decades. And of course if they don’t want this, they could easily cushion the fall with immigration. In any event, there is nothing here that suggests the “end of babies” or the abandonment of reproduction — families would continue having an average of 1.8 children each, as they have for the last several decades.

A population below replacement fertility might seem diseased, but it might also just be the aggregation of a lot of people exercising their newfound freedoms in newly discovered ways, including having fewer or no children. I agree with Sussman when she writes:

The problem, to be clear, is not really one of “population” …. Hundreds of thousands of babies are born on this planet every day; people all over the world have shown they are willing to migrate to wealthier countries for jobs. Rather, the problem is the quiet human tragedies, born of preventable constraints — an employer’s indifference, a belated realization, a poisoned body — that make the wanted child impossible.

To the extent those tragedies occur, we should prevent or ameliorate them. And to the extent they are concentrated among people or groups who already experience marginalization, isolation, or exploitation, it’s a social problem that’s part of our burgeoning inequality suite. Healthcare, housing, education, and family leave all come to mind as helpful, even if they can’t solve the existential crisis of late capitalism. But two cautions. First, I’m not convinced such tragedies are more common than they used to be, just because people are having fewer children than they used to. Remember, we also have fewer people trapped into having large families they don’t want (forced-birther policies notwithstanding).

And second, crucially, even if we address these issues of self-determination, there is no guarantee that a happy, healthy, equal, and harmonious population wants to produce enough children to maintain or grow its total size. We may eventually have to learn to live with fewer people, locally and globally, even if we’re all happy with the number of children we have.

What comes around

In the meantime, I think it’s confusing and ultimately unhelpful to confound what are essentially orthogonal issues. We should care about the problems Sussman raises regardless of population trends.

And that brings me to an aside on New York Times coverage. It was just 11 years ago, in 2008, that a different New York Times story about the existential threat of falling fertility, this one in the Magazine and titled “No Babies?”, singled out Scandinavian countries — with total fertility rates of 1.8 — as positive examples, bucking the trend toward “lowest-low” fertility demonstrated by Southern European countries, due to their “vigorous social-welfare systems.” That’s the same social welfare system, and the same total fertility rate, that Sussman characterizes as a “reproductive malaise” in Denmark today.

And there are illustrations of children playing alone in both cases. Because “the end of babies” and a world with “no babies” is best illustrated with a picture of the last child on earth alone in a playground. Great illustrations — just not of our societies.

nytchildrenalone

That said…

You can’t really pin sudden fertility swings on things like “late capitalism,” which are decades in the making. It was just February of 2009 that I was writing one of my first blog posts, “Why Are American Women Having More Children?” as U.S. total fertility rose to 2.1 for the first time since 1971. I think it was late capitalism, too, but the U.S. TFR was 13% higher than Denmark’s (they are now the same), and everyone was talking about American mothers “opting out” of the labor force to stay home with their four children. On the other hand is socialist Finland — a country with a lot of what I want from social policy, including low inequality and poverty, and lots of family leave — which has seen a fertility decline since 2010 that could reasonably be called a crash. The government estimates the TFR in 2019 is 1.32-1.34, down from 1.86 a decade ago!

Here are the trends in select countries:

country fertilitiy trends.xlsx

Does this mean the people in Finland are suddenly much less happy  relative to those in Denmark, which has seen a recent uptick in fertility rates? I have no idea. I can make population projections if you tell me the fertility rate, but I can’t tell you what the fertility rate will be in the future (and neither can you). A tiny bit humbling, honestly.

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