The most important thing is that Stephanie Coontz has written another very good, and very important, New York Times essay. It describes a “slippage” in support for gender equality among young people these days, and warns that without improved work-family policies, progress toward egalitarian family arrangements may be imperiled. The piece also announced a package of short papers in a Council on Contemporary Families symposium, which provided the supporting evidence. (This kind of work, incidentally, is why I’m a proud member, and board member, of CCF.) If you haven’t read Stephanie’s essay, I recommend reading it now, and if you forget to come back here that’s fine.
Anyway, an unfortunate confluence of events created some chaos after the piece came out. First, the NYTimes wrote a headline, “Do Millennial Men Want Stay-at-Home Wives?”, that emphasized only one piece of the evidence. It referred to a figure showing General Social Survey data on the trend in very young men and women (ages 18-25) disagreeing with the statement, “It is much better for everyone involved if the man is the achiever outside the home and the woman takes care of the home and family.” (That is the classic FEFAM question, to GSS fans, asked since 1977. I’ve used it myself, and it figures in the key analysis of stalled gender progress by Cotter, Hermsen, and Vanneman.)
This was the figure, showing a marked divergence between men and women:
The second event was the unfortunate timing: between the time Stephanie wrote the piece and the day it appeared, the General Social Survey released its 2016 round of data (it’s been running every two years). The survey is fickle. It’s very good quality and has many great demographic and attitude items running for 40 years, making it the best source for analyzing many social trends. But it’s not that big. In 2014 it had 2,867 respondents, of whom only 141 were ages 18-25. So it wasn’t surprising that the 2016 numbers were different from the 2014 numbers, but the scale of the blip was shocking, as reported independently by Emily Beam and Neal Caren. Here is what the updated trend looks like:
Yikes. As exciting as it is for survey analysts to see such a wild swing, it’s not what anyone wants to see the day after their NYTimes piece drops. We can’t know yet what happened, but on further inspection, at least we can say that it’s not limited to the youngest group and its small sample. Among men ages 26-54, the percentage disagreement with FEFAM also jumped, from 73.7 to 78.3 (women 26-54 were up one point).* In fact, 2014 may have been as big a blip as 2016, you just wouldn’t notice because it continued the trend.
Anyway, back for a minute to the main point. Joanna Pepin, who co-wrote one of the symposium pieces with David Cotter (and who is also an advisee of mine), has pointed out that the divergence between men and women is secondary to the main trend, which is the reversal of progress on FEFAM for both men and women since the mid-1990s. They used the Monitoring the Future survey, and find a big drop in FEFAM disagreement among high school seniors — regardless of gender. Here’s their key figure, with the FEFAM trend shown in green (their full paper is available on SocArXiv):
So that is the most important news: a big reversal among young adults on attitudes toward homemaker-breadwinner family arrangements.
Now, If you’ve now read Stephanie’s piece, and Joanna’s, and you’re back, here’s a little more on the minor kerfuffle that arose over the new data.
When to call a trend a trend
I don’t think Stephanie was wrong to use the GSS trend, although it might have been better to widen the age range, or pool the data over several years. The bigger problem was the headline selling that divergence as the main story, which it wasn’t in the grand scheme. (The fact that so many jumped on the story shows how good they are at headline writing.) But even that wasn’t really wrong, given the information they had. The Op-Ed staff checked the facts, and the facts were the facts. Until yesterday.
To confirm this, I ran some tests on the gender divergence in the data they used (I started with code that Neal shared; it’s at the bottom). I started at 1994, the last peak of the trend, to look for the divergence after that, which is what Stephanie referred to. First, here is what you get if you run a logistic model that controls for race/ethnicity and individual years of age (two things that changed over the last two decades), and enters the years individually in an interaction with gender (those are 95% confidence intervals).
If you stop at 2014, it looks like men are pulling away from women (in the direction of “traditional” attitudes), but it’s not definitive. And obviously 2016 is an issue. To help with the small samples, I ran a linear test of the year trend, that is, entering year as a continuous variable instead of individual years. I did it ended at 2014 and then through 2016. Here are the results:
In the 1994-2014 model, the Male*Year interaction is statistically significant at conventional levels, which in my opinion means it’s legit to say men were pulling away from women. Of course 2016 ruined that; if you had 2016 and didn’t use it, that would be really wrong. There are other ways to slice it, but at some point we have to call a trend a trend and deal with it. It was a reasonable decision. Of course, new data always comes along (until the last trend of all, whatever that is), no trend lasts forever; it’s just a shame when it comes along the next day. In addition, though I’m not showing it because it’s boring, if you didn’t disaggregate the trends by gender, you would also see a significant decline in FEFAM disagreement after 1994, which gets to Joanna’s point.
Anyway, score one for sociology Twitter. People came up with the data, shared code and results, and discussed interpretations. It got back to Stephanie and the NYTimes editors, and within a day they added an addendum to the original piece:
Update: After this article was posted, 2016 data from the General Social Survey became available, adding some nuance to this analysis. The latest numbers show a rebound in young men’s disagreement with the claim that male-breadwinner families are superior. The trend still confirms a rise in traditionalism among high school seniors and 18-to-25-year-olds, but the new data shows that this rise is no longer driven mainly by young men, as it was in the General Social Survey results from 1994 through 2014.
This is pretty much how it’s supposed to work. As the Car Guys used to say, if you never stall you’re wearing out your clutch (sorry, Millennials). If you never overshoot an analysis of trends you’re probably waiting too long to get the information out.
* Note: I originally accidentally described this as “over 25.”
You can get the data here. Here’s the STATA code:
/* recodes */
recode fefam (1/2=0) (3/4=1), gen(fefam_d)
gen young=age>=18&age<=25
recode sex (2=0), gen(male)
/* the model for the figure */
logit fefam_d i.year##i.male i.age i.race if year>=1994 & young==1 [pweight = wtssall]
margins year##male
marginsplot
/* the models for the table */
logit fefam_d c.year##i.male i.age i.race if year>=1994 & young==1 & year<=2014 [pweight = wtssall]
logit fefam_d c.year##i.male i.age i.race if year>=1994 & young==1 [pweight = wtssall]
Family Inequality 
Shouldn’t you be using a hierarchical model, with random effects for the terms with years? That would reduce the size of apparent trends, correcting for sampling error.
If your code were in R, I’d post a fix.
LikeLike
Another thing I worry about is changes in GSS coverage over time. GSS has had a Spanish language version since 2006, so there’s better coverage of the Spanish-speaking population since then. How does that figure in? And how sensitive are trend analyses to how sampling weights are used?
And how about adding quaratic and cubic year terms and interactions and showing that marginsplot (and significance tests)?
LikeLike
Ya. I probably wouldn’t do all that on the 18-25 trend because it’s not that important by itself. But I don’t know.
LikeLike
So, I poked around the GSS site and looked at the questions list. I found the one re: men should work and women should stay home, but I didn’t see any related question either stated in a gender-neutral way or where the genders are reversed. I’m the breadwinner in my family and my husband is a SAHD because we think that everyone is better off if one of the adults in the household is able to be available for the kids full-time.
But if I were being surveyed, and I was only given the option of the question as stated, I would probably answer “agree” but not because I think women should stay home. I think SOMEONE should stay home if possible, but that doesn’t mean you’re bad or wrong if that doesn’t work for your family (for whatever reason).
TL/DR: I think they need to update the question, or at least ask a couple different variations of the question in order to capture some useful information.
P.S. Let me know if I’m missing something.
LikeLike
The issue is that it’s good to be able to track questions over time; that’s why the old questions are important. New questions don’t mean as much because you don’t have the context of the trend, so you have to make assumptions or guess about what they mean. The hope is that the meaning of the questions changes more slowly than the responses, so that changes in the responses tells you something valuable.
LikeLike
A postscript on the problems of getting new GSS data.
For the AJS article Philip notes, my memory is that we had it written and accepted with one “knot” in the time series in the mid 1990s, but they delayed so long in publishing it that we had to add more GSS data. The new data continued the mild post-2000 rebound in gender attitudes, so we had to add a second knot at 2000 and analyze it — which really muddied the story (even thought the post-2000 rebound is very mild and almost entirely cohort replacement).
The question that still fascinates me is that in both Joanna’s MTF high school seniors’ data, and the GSS national data, the turnaround in the mid-1990s appears very abrupt and enduring. So, what was so dramatic then that could turn around a decades-long trend?
LikeLike