Work product: Women’s ethnic immigration education work patterns

Five years ago Jen’nan Read and I published an article about women’s employment for 12 different ethnic groups in the U.S. In my Gender, Work, and Family seminar the other day we read it, and because of the timing in the course we were talking about developing and framing research questions. We looked at a couple of the images Jen’nan and I used to work through the many patterns we were trying to sort out in the data, and I thought the sequence might be interesting for blog readers, too. (These use data from the 2000 Census, with “employed” meaning any employment in the year 1999.)

The overall employment rates ranged widely, from 65% (Mexican, Asian Indian) to 84% (Filipina). First thing, break the groups out by education:

That helps a little. At the low end of education, employment rates are low. But at the high end, the spread is great — the line isn’t helpful — with high- and low-employment groups all found above 14 years of average education.

Next step was nativity (where they were born) and year of immigration for those born elsewhere. Looking at the high and low groups, there were distinct patterns:

Mexican women are on a diagonal line, showing a temporal progression from recent immigrants having low education and employment rates, back in time to those born in the U.S. (mostly children of earlier immigrants) with higher levels of both. The Asian Indian women are on a vertical line, with high education but low employment rates for recent immigrants, who may have come as spouses of men who had (or were getting) jobs here. The Filipinas, who are mostly labor migrants — that is, they came for their own jobs — are bunched up at high levels of both employment and education regardless of immigration timing.

This must have been the time Jen’nan hit on the title of “One Size Fits All?”, since the stories clearly diverged, and we decided to fit models of employment predictors for each group separately (details are in the paper).

One other image, a nice idea but hard to read, is also sitting in the old folder (click to enlarge):

Here there’s a dot for each ethnic group for each year of immigration. That is, the dot down in the bottom left is Mexican women who immigrated in 2000 (“M0″). The line is a weighted regression line, so it’s the overall relationship between education and employment rates. You see the Mexican women crowded around the lower left; the Filipinas in the top right; and recent Arab, Japanese, Korean and Asian Indian immigrants along the bottom. (The other initials you see are for Vietnamese, Puerto Rican, White, Chinese, Cuban, and Iranian).

When possible, I like to do this kind of descriptive exploration — making progressive slices in the data and looking at the patterns — before building complicated statistical models with a lot of factors at once. If the descriptive image survives the statistical analysis, there’s a chance of not only getting the story right, but being able to explain it.

FYI

This is cross-sectional data — that is, what each group is doing in 2000, based on the year they arrived. But it is suggestive of different immigration pathways. I’m not expert on the immigration side, but since I brought it up I should give a few pointers to recent literature on “segmented assimilation,” which focuses on such differences. The idea dates to the early 1990s, maybe this article:

• “The New Second Generation: Segmented Assimilation and Its Variants,” by Alejandro Portes and Min Zhou.

These are more recent, and include reviews of the major research:

• “Generation and Earnings Patterns Among Chinese, Filipino, and Korean Americans in New York,” by Sookhee Oh abd Pyong G. Min
• “The social context of assimilation: Testing implications of segmented assimilation theory,” by Yu Xie and Emily Greenman

Feel free to add suggestions for additional resources in the comments.

Pink and blue kid(s)

Jo Paoletti got a nice cover write-up from the UMD magazine Terp, for her new book, Pink and Blue: Telling the Boys from the Girls in America. I especially love the cover photo:

The photo(s) is (are) by John T. Consoli, linked without permission. This is a great exercise for noticing how we internalize gender norms. If you thought even for a moment that one of these kids is a boy and the other is a girl, you’re busted as a product of socialization. (I won’t reveal the “true” answer.)

This is much better than my own crude Photoshop version:

I’ve done a series of posts on color and children, which you can find here. That led me to do a survey on color preferences, which got close to 2,000 responses to the question, “What’s your favorite color.” Based on a simple color chart provided, these were the responses:

More than the gender breakdown, I wanted to see if the nurture-versus-nature element of color preference could be teased out in a single survey. So I asked people if they had children, and the gender of their children — figuring that might reflect some “adult socialization.” And that modest result is what I found. From the abstract:

This study asks whether the gendered social environment in adulthood affects parents’ color preferences. The analysis used the gender of children to represent one aspect of the gendered social environment. Because having male versus female children in the U.S. is generally randomly distributed, it provides something of a natural experiment, offering evidence about the social construction of gender in adulthood. The participants were 749 adults with children who responded to an online survey invitation, asking “What’s your favorite color?” Men were more likely to prefer blue, while women were more likely to prefer red, purple, and pink, consistent with long-standing U.S. patterns. The effect of having only sons was to widen the existing gender differences between men and women, increasing the odds that men prefer blue while reducing the odds that women do; and a marginally significant effect showed women having higher odds of preferring pink when they have sons only. The results suggest that, in addition to any genetic, biological or child-socialization effects shaping adults’ tendency to segregate their color preferences by gender, the gender context of adulthood matters as well.

The paper has been provisionally accepted and should be published in a peer-reviewed journal near you soon.

Jo’s excellent blog is here, where you can read about her new project, exploring the rise and fall of unisex clothing for children.

Grad Seminar: Gender, Work, and Family Syllabus

Here is the reading list for my new seminar, Gender, Work and Family. It’s a required course for grad students at U. Maryland who plan to take the comprehensive exam in GWF. The full syllabus, with assignments, etc., is here. I go back and forth on a handful of issues: breadth versus depth, country case studies versus comparative studies, books versus articles, and including my own research. I’m open to suggestions, and feel free to add your recommendations in the comments.

Anyway, feel free to use it for whatever you like. The links here will mostly hit pay walls unless you’re authenticated with a subscribing university.

January 31 – Research overviews

• Bianchi, Suzanne M. and Melissa A. Milkie. 2010. “Work and Family Research in the First Decade of the 21st Century.” Journal of Marriage and Family 72:705-725. Link
• Ferree, Myra Marx. 2010. “Filling the Glass: Gender Perspectives on Families.” Journal of Marriage and Family 72:420-439. Link

February 7 – Stalled progress toward equality

• Cotter, David, Joan M. Hermsen and Reeve Vanneman. 2011. “The End of the Gender Revolution? Gender Role Attitudes from 1977 to 2008.” American Journal of Sociology 117(1):pp. 259-289. Link
• England, Paula. 2010. “The Gender Revolution: Uneven and Stalled.” Gender & Society 24(2):149-166. Link
• Pettit, Becky and Stephanie Ewert. 2009. “Employment Gains and Wage Declines: The Erosion of Black Women’s Relative Wages since 1980.” Demography 46(3):pp. 469-492. Link

February 14 – The persistence of gender inequality

• Ridgeway: Framed by Gender: How Gender Inequality Persists in the Modern World.

February 21 – Work-family

• Williams: Reshaping the Work-Family Debate: Why Men and Class Matter.

February 28 – Studying work-family decisions

• Cha, YJ. 2010. “Reinforcing Separate Spheres: The Effect of Spousal Overwork on Men’s and Women’s Employment in Dual-Earner Households.” American Sociological Review, 75 (2): 303-329. Link
• Percheski, Christine. 2008. “Opting out? Cohort differences in professional women’s employment rates from 1960 to 2005.” American Sociological Review, 73 (3): 497-517. Link
• Read, Jen’nan G. and Sharon Oselin. 2008. “Gender and the education-employment paradox in ethnic and religious contexts: The case of Arab Americans.” American Sociological Review 73 (2): 296-313. Link
• Read, Jen’nan Ghazal and Philip N. Cohen. 2007. “One Size Fits All? Explaining U.S.-born and Immigrant Women’s Employment across Twelve Ethnic Groups.” Social Forces 85(4):1713-34. Link

March 6 – Race, class and intersectionality

• Furstenberg, Frank F. 2007. “The making of the black family: Race and class in qualitative studies in the twentieth century.” Annual Review of Sociology 33:429-448. Link
• Harknett, Kristen and Arielle Kuperberg. 2011. “Education, Labor Markets and the Retreat from Marriage.” Social Forces 90(1):41-63. Link
• Choo, Hae Y. and Myra M. Ferree. 2010. “Practicing Intersectionality in Sociological Research: A Critical Analysis of Inclusions, Interactions, and Institutions in the Study of Inequalities.” Sociological Theory 28(2):129-149. Link

March 13 – Economics and feminism

• Hartmann, Heidi I. 1981. “The Family as the Locus of Gender, Class, and Political Struggle: The Example of Housework.” Signs 6(3):pp. 366-394. Link
• Nelson, Julie A. “Feminism and Economics.” Journal of Economic Perspectives 9(2):131-148. Link
• Folbre, Nancy and Julie A. Nelson. “For Love or Money – Or Both?” Journal of Economic Perspectives , Vol. 14, No. 4 (Autumn, 2000), pp. 123-140. Link

March 20 – SPRING BREAK

March 27 – Housework studies

• West, Candace and Don H. Zimmerman. 1987. “Doing Gender.” Gender & Society 1(2):125-151. Link
• Sayer, Liana C. 2005. “Gender, time and inequality: Trends in women’s and men’s paid work, unpaid work and free time.” Social Forces 84(1):285-303. Link
• Sayer, Liana C. and Leigh Fine. 2011. “Racial-Ethnic Differences in U.S. Married Women’s and Men’s Housework.” Social Indicators Research 101(2):259-265. Link
• Gupta, Sanjiv. 2007. “Autonomy, Dependence, or Display? The Relationship Between Married Women’s Earnings and Housework.” Journal of Marriage and Family 69(2):399-417. Link

April 3 – The gender pay gap

• O’Neill J. 2003. “The Gender Gap in Wages, circa 2000.” American Economic Review 93(2)309-314. Link
• Budig, Michelle and Melissa Hodges. 2010. “Differences in Disadvantage: Variation in the Motherhood Penalty across White Women’s Earnings Distribution.” American Sociological Review 75(5): 705-728. Link
• Cohen, Philip N. and Matt L. Huffman. 2003. “Individuals, Jobs, and Labor Markets: The Devaluation of Women’s Work.” American Sociological Review 68(3):443-63. Link
• Blau, Francine D. and Lawrence M. Kahn. 2007. “The gender pay gap: Have women gone as far as they can?” Academy of Management Perspectives 21(1):7-23.

April 10 – Occupational segregation

• Cartwright, Bliss, PR Edwards, and Q Wang. 2011. “Job and industry gender segregation: NAICS categories and EEO-1 job groups.” Monthly Labor Review 134(11):37-50. Link
• Charles, Maria and Karen Bradley. 2002. “Equal but Separate? A Cross-National Study of Sex Segregation in Higher Education.” American Sociological Review 67(4):573-599. Link
• Matt L. Huffman, Philip N. Cohen and Jessica Pearlman. 2010. “Engendering Change: Organizational Dynamics and Workplace Gender Segregation, 1975-2005.” Administrative Science Quarterly 55(2):255-277. Link

April 17 – Gender, family and women’s empowerment in Asia

• Desai, Sonalde and Lester Andrist. 2010. “Gender Scripts and Age at Marriage in India.” Demography 47(3):667-687. Link
• Rammohan, Anu and Meliyanni Johar. 2009. “The Determinants of Married Women’s Autonomy in Indonesia.” Feminist Economics 15(4):31-55. Link
• Cohen, Philip N. and Wang Feng. 2009. “The Market and Gender Pay Equity: Have Chinese Reforms Narrowed the Gap?” Pp. 37-53 in Creating Wealth and Poverty in Post-Socialist China, Deborah S. Davis and Wang Feng (eds.). Palo Alto: Stanford University Press. Link

April 24 – Masculinity and fathering

• Connell R.W. and J.W. Messerschmidt JW. 2005. “Hegemonic Masculinity: Rethinking the Concept.” Gender & Society 19(6):829-859. Link
• Parrenas, Rhacel S. 2008. “Transnational fathering: Gendered conflicts, distant disciplining and emotional gaps.” Journal of Ethnic and Migration Studies 34(7):1057-1072. Link
• Milkie, Melissa A., Kendig, SM, Nomaguchi, KM and Denny, KE. “Time with Children, Children’s Well-Being, and Work-Family Balance among Employed Parents.” Journal of Marriage and Family 72(5):1329-1343. Link

May 1 – Generational change in work-family perspectives

• Gerson: The Unfinished Revolution: Coming of Age in a New Era of Gender, Work, and Family.

May 8 – State policy

• Esping-Andersen: The Incomplete Revolution: Adapting to Women’s New Roles. Polity.

Undoing gender math stereotypes

In my opinion, there is no way to administer a math test that will identify inborn ability. So people who think the greater presence of men in high-end math and science positions is a result of the distribution of inborn abilities generally rely on the observation of (a) big gender gaps, (b) long-standing gender gaps, or (c) widespread gender gaps, to make their case.

Big gaps (a) are only useful for creating a big impression. Long-standing gaps (b) are undermined by the scale of change in recent decades. And a new study does a very nice job weakening type-C support.

In “Debunking Myths about Gender and Mathematics Performance,” in the Notices of the American Mathematical Society, Jonathan Kane and Janet Mert study variation both between and within countries to test a variety of hypotheses about the sources male math advantage. They look at the distribution and variance in scores, the association with single-gender schooling, religious context and, most importantly, broader patterns of gender inequality. The main message I get is that gender ability in math differs so much across social contexts that any conclusion about “natural” ability is untenable. Also, gender equality is good.

Here’s my favorite figure from the paper, showing the distribution of eighth-grade scores for boys and girls in three countries:

In the Czech Republic there is no difference in either the means or the distributions for boys versus girls, and the average ability is high. Bahrain shows a much greater variance for boys versus girls — which is sometimes used to explain why to many top achievers are men — but women’s average is higher. Finally, in Tunisia the girls have a higher variance but a lower mean. Where’s the natural ability story?

An important consideration in all of these patterns is the role of selective dropouts. That is a potential problem with any school-based test, but also shows the problem with using any test of school-based knowledge to understand underlying “natural” ability (including SATs). Unless you can test populations with no schooling, or identical schooling experiences, you can’t resolve this.

In the meantime, the great social variability shows us that context matters, and since that’s something we can definitely address, there is no reason to get hung up on the biological stuff — at least as far as policy and practice are concerned.

Here’s a previous post from me on how teacher interactions affect gender patterns of learning, and another writeup on the new study from ScienceBlogs.

Recent reads: Brazil, China, blogging and the Black middle class

In the last few days I tweeted a handful of really interesting articles that might be of interest to Family Inequality readers:

In the Washington Post: Plummeting birthrates in Brazil

The Washington Post reports on Brazil’s fall from more than 6 to less then 2 children per woman in the past 50 years:

It’s a good case study for fertility transitions, featuring a combination of common economic and cultural suspects in accelerated sequence.

In the NY Times: Peggy Orenstein on the ideal of gender-free toys

Rather then seek a gender-free ideal, she argues, consider how children’s environments exacerbate or mitigate the differences between them:

At issue, then, is not nature or nurture but how nurture becomes nature: the environment in which children play and grow can encourage a range of aptitudes or foreclose them. So blithely indulging — let alone exploiting — stereotypically gendered play patterns may have a more negative long-term impact on kids’ potential than parents imagine. And promoting, without forcing, cross-sex friendships as well as a breadth of play styles may be more beneficial. There is even evidence that children who have opposite-sex friendships during their early years have healthier romantic relationships as teenagers.

In Slate: Mara Hvistendahl on C-sections in China

The tradition of natural childbirth was continued by the training of nurses and midwives during the early years of Chinese socialism. Now, the one-child policy combines with the medicalization of childbirth – and the attendant profit motive – to tip the scales toward C-sections. She writes:

For modern expectant women, by contrast, the combination of the one-child policy and feverish economic development has yielded an environment in which they—and the in-laws and husbands who have so much riding on a single birth—fear any potential misstep.

In The Chronicle of Higher Education: Andrea Doucet on scholar-bloggers

As an established scholar who has taken to blogging, she confronts the difference between slow-and-deep versus fast-and-thin, how it affects her reading as well as her writing, and her self image as a scholar. She is “convinced that blogging can and should be part of scholarly life,” but it comes with risks:

At its best, a blog post can move and inspire in what seems like the blink of an eye. The combination of brevity, focused vision, and engaging language creates a storytelling style that could make a scholar green with envy. But blogs also generally call for a form of reading that verges on consumption.

On CNN.com: Kris Marsh on the Black middle class

Kris – a friend and colleague – argues that the Black middle class is being transformed by the growing presence of single adults without children, the “Love Jones Cohort.” Taking this group seriously undermines the narrative of the “failure” of marriage in Black America.

I propose we embrace the reality of a changing black middle class and start taking a serious look at how the Love Jones Cohort is changing the face of black America, changing how we think about middle class, and changing our understanding of being black in America.

Follow the bouncing 1% meme…

This thing is a perfectly designed info-virus. It replicates beautifully in a 140-character environment. It feeds on gullibility and thrives in a numeracy vacuum. I think it will outlive us all. Women will forever own “1% of the world’s wealth.” (Here’s the original debunking.)

September 18, 8:50 pm:

I really wonder how Sudeep Reddy managed to work that 1% thing into this blurb on a World Bank Report. I’m pretty sure it’s not in there.

Someone at WSJ’s Twitter account was asleep at the switch. Don’t they edit this thing?

Anyway, September 19, 3:45 pm:

By the evening of the 20th, @MsMagazine got on board:

Then I saw this one from Shakesville:

To the credit of the readers there, many raised logical questions — what about me and my husband, who owns our wealth? what about Oprah and Martha Stewart, JK Rowling, the Queen of England? After 46 comments of back and forth — including some heroic logical attempts to imagine how it could be true, and several trips through the WB report — the moderators closed the comments (but left the post up).

And if you look really closely, you can see a faint heartbeat. It will be back.

ASA Job Bank, supply/demand, gender

Rebels without a job?

(Spoiler alert: inside-sociology post.)

(With clarifications marked as marked like this.)

The American Sociological Association’s Department of Research & Development has a new report out on the 2010 academic job market. It focuses mostly on the big news, overall trends and so on. I was more interested in the fate of different specializations.

The data are bound to be messy on this, since both jobs and candidates often include multiple specialties. But still, the report concludes that there are “several notable mismatches between the fields of interest of graduate students and the fields in which departmental searches are most common.”

You can look at their table yourself, on page 7, but since I prefer a different way of looking at it, I made these. The first figure is just the percentage of ads that listed an area (x-axis) versus the percentage of applicants PhD candidates who listed the area in their ASA member profiles. The good news is the correlation is positive, at .37.

I condensed the area names, so sue me. I also color-coded them based on the ratio of demand (ads) to supply (apps), which isn’t obvious from the table or graph. All-caps red is Culture — where apps PhD candidates’ percentage outnumbers ad percentage almost 3-to-1 (that is, 24% of PhD candidates list Culture as an area of interest, but 8% of ads list culture). Sex and gender is the next worst at 1.9-to-1. The best ratio is crime/deviance, which earned green type but not all caps, with a ratio of 1.7 jobs per applicant PhD candidate.

Back in June I made some graphs on the gender composition of sections – the organizations of sub-fields within sociology. Now we can see how the gender composition lines up with the supply-demand situation. (Remember these section compositions are for all section members, not just students.) Here are the sections I could match up reasonably well with the ad/app categories, with demand-over-supply on the x-axis versus gender composition. Areas on the right are smooth sailing for job seekers, those on the left are buyer’s markets for hiring departments (correlation = -.26)

It’s always worth checking, but it doesn’t seem like the main story is women crowding into areas with too many applicants per job, though maybe some of that.

Speculation: Maybe one predictor of poor job prospects is anti-establishment perspectives and (not coincidentally) external support, whether from research funding or non-sociology major teaching demand. That’s just stereotyping the difference between culture/sex-gender/inequalities graduate students versus quant/crim students. (Family and enviro are the ones that don’t fit my stereotypes there, but I’m flexible.)

Feel free to add your interpretations.

When there’s housework to do…

According to the flyer in yesterday’s mail, “Life’s too short to clean your own home.”

Naturally, for the people who work for The Cleaning Authority, life is not to short to clean someone else’s home – and love it, as this woman on the inside flap apparently does:

Maybe she’s happy because she has a job she likes — even though she would be miserable cleaning her own home — like in the 1970s feminist version:

Remember, nobody smiles doing housework but those ladies you see on TV.
Your mommy hates housework,
Your daddy hates housework,
I hate housework too.
And when you grow up, so will you.
Because even if the soap or cleanser or cleaner or powder or paste or wax or bleach
That you use is the very best one,
Housework is just no fun.

Children, when you have a house of your own,
Make sure, when there’s house work to do,
That you don’t have to do it alone.
Little boys, little girls, when you’re big husbands and wives,
If you want all the days of your lives
To seem sunny as summer weather,
Make sure, when there’s housework to do,
That you do it together!

The sociological truth is that it is different to clean someone else’s home. Today’s corporate cleaners are different from an informal cleaning relationship. I once tried to imagine that “keeping house” should be considered a real occupation — which would help reveal the overall gender division of labor, not just the segregation of occupations or housework, which are almost always studied separately.

Corporatizing housework does change its social nature. It’s not the physical labor itself that makes it about gender, after all. That doesn’t mean it’s not unpleasant work. But cleaning the toilet of an anonymous person may be less degrading than cleaning the toilet of someone you have a personal (subordinate) relationship with. On the other hand, maybe people love cleaning toilets for people they really love.

The rationality of market dynamics ideally makes irrelevant the gender of workers in general. Men are more somewhat more likely to cook and clean for money than for free, for example. In that ideal, not real, marketized world, then, maybe there is no such thing as housework — just work and workers. Would that be better?

Addendum:

Maybe it would be better — a genderless world of labor and capital. But as Joan Acker wrote 21 years ago, and reiterated last year, the generic worker in the mind of employers is usually actually male —  in the sense that “he” has no family responsibilities; and if he does, “he’s” not a good worker, committed to the job, and the ones that get promoted are more often actual men.

That makes this ad from Groupon especially ironic (thanks to Ken Kolb for the tip):

How many “man-hours” does a woman at Designer Maid do in an hour?

If you follow the links to Designer Maid, it gets more interesting still. On the home page, the copy reads:

For many upwardly mobile and dual income families today, the home we’ve worked so hard to obtain is a time consuming chore to maintain. We give you more time to do those things you need to do or would rather be doing. So, instead of spending endless hours on mundane housework, Relax… We’ll take care of the rest! (emphasis added)

That’s rich, because on the Employment page – where there is the same picture of the smiling woman doing the backbreaking work — those “endless hours” of “mundane housework” become a fabulous professional opportunity:

Designer Maid is a great place to work… Designer Maid provides all of the equipment and supplies you will need to fulfill your role as a professional house cleaner. In addition, we provide all of the training necessary for for you to achieve the distinction of Certified Professional House Cleaner.

So, just forget what we said about the endless hours of mundane work, and common down to apply!

Birth of a headline

One day this summer I got an email message from a reporter. We had an exchange over email. I was on vacation. Ten days later a story appeared. Here’s my end of the back-story. Pleasantries and personal details omitted.

Her:

I’m a reporter with the News & Observer, and I’m hoping you’ll be able to speak with me for a few minutes today for a story I’m working on. My story is about the latest census data from NC, specifically the male/female ratio throughout age, along with the ways it has changed over time.  I have some specific questions about why the ratio flip-flops in middle age, and why it used to — but no longer does — flip-flop again in late middle age/early old age.

Me:

I’d be happy to try to help you. I’m not familiar with the pattern you’re seeing, however. Can you send me or refer me to the numbers you have?

Her:

I’m … interested in why boys outnumber girls, but then later in life women outnumber men… [info on locating a spreadsheet file with the data, then a list of "driving questions"]:

• Boys outnumber girls – why?
• Women outnumber men – why?
• Why have both trends flattened out in the last few decades?
• What drives variation over time and place?

I looked over the numbers, then wrote back.

This looks quite normal to me. There are about 104 boys born for every 100 girls, naturally. That’s apparently evolution’s answer to the fact that, as the weaker sex, males die more often at all ages. Some of that is from social causes — like violence, war, and drunk driving — but it is also natural biology for humans. So you always have more boys born, and then at some point in the age distribution it crosses over and you have more females living.

So it’s an interesting question what makes that change over time, or vary from place to place. Change over time has to do with mortality. For example, men smoke(d) much more than women, so that’s contributes a few years to the age difference in life expectancy, although that is decreasing now. In North Carolina, I would guess that what is going on has to do with our large military presence, and our immigration flows (though I don’t know which way those skew here).

The general movement of the crossover age from younger ages to older ages reflects declining overall mortality, so everyone lives longer. I don’t know why it would have gone back down from 35 to 25 in the last decade. That’s an interesting question — I wonder if the national data show the same thing? I’m sorry I don’t know off hand.

That was off the top of my head. Hoping to have more time to look into it, I tried to set up a time to call, but she was out of time on the story. 10 days later, on page 1 of the News & Observer, was this:

And the quote from me:

Women giving birth to more boys than girls is “apparently evolution’s answer to the fact that, as the weaker sex, males die more often at all ages,” said Philip Cohen, a professor of sociology at UNC-Chapel Hill.

From, “This looks quite normal to me,” to “What’s happening to all of North Carolina’s men?” That’s something.

Anyway, it doesn’t justify the headline, but there is an interesting pattern here. North Carolina is not unique, but it’s among the states with fewer men from about age 25 to 60. The differences aren’t great, but there has to be a reason, and it’s worth looking at.

Here is the pattern, with North Carolina, California, and New York calculated from the 2010 Census (which isn’t available for every state yet), and the national average from the 2009 American Community Survey:

The News & Observer had a graph, too, but it didn’t show how North Carolina differed from other states:

Nice touch, though: “After age 24, the ratio swings in favor of the ladies.” I know it’s sometimes hard to make demography an attractive subject, but still.

Smurfette? How do they get away with this stuff?

Buy a McDonald’s Happy Meal and get a toy: OK, I didn’t expect it to be enlightening.

But to hear Kevin Newell, the company’s executive vice president and global chief brand officer, tell it, that’s exactly what it should be:

McDonald’s is committed to playing a positive role in children’s well-being. The Smurfs Happy Meal program delivers great quality food choices, fun toys and engaging digital content that reinforces important environmental messages.

Awesome. Granted, the last time I saw a Smurf, it was about 1978, and he looked like this:

And I don’t recall being overly concerned with gendered toy representations at the time. Anyway, now I’m told by the Happy Meal box that, “Smurfs are named after their individual talents: there’s Farmer, Painter and Baker… Know your talent and find your Smurf name!”

The girls both got male Smurf characters, which struck me as interesting, because the counter person had asked us if the Meals were for boys or girls. Then I looked at the characters on the box. Then I looked at the complete list of them on the website (see the poster version here):

Then I wondered what Smurfette’s “individual talent” was that got her — the only female Smurf – named “Smurfette.” And at that point, if it hadn’t been for all the fat and salt and sugar in my meal, I might have stopped enjoying it.

In context

I’ve commented before on the gender segregation in film making. The gist of it is apparent in this graph from the Celluloid Ceiling report by the Center for the Study of Women in Television and Film. Not many women in charge:

But isn’t it improbable that a blockbuster kids’ movie, which grossed more than $75 million in its first two weeks, could be so blatantly sexist? There are a few women in the cast of the movie version of The Smurfs, but all the Smurfs are still male except Smurfette. Next thing you know they’re going to turn the only female character in this promotion — which, remember, plays a “positive role in children’s well-being” — into an adult sex symbol played by Katy Perry. You’re kidding.

Is sexist even a word anymore?

In fact, sexism used to be a very common word. According to the Google Ngrams database of millions of terms from their vast collection of digitized books in American English, “sexism” was even more common than “bacon” during the 1990s (you can play with this yourself here):

Unfortunately, in my opinion, sexism has retreated from the language, and kids’ stuff seems to be more shamelessly gendered than ever. I think this sad state of affairs is at least partly the result of what you see in that green line above — the backlash against feminism (and anti-racism) that made it seem more unpleasant or unwarranted to make a “big deal” out of sexism than to treat girls like this.

P.S. I haven’t seen the movie. Please tell me it has a hidden feminist message I haven’t heard about.