methods/use of data

This post originally appeared on Sociological Images in 2009.

Emily D. sent us a link to a post by Flowing Data linking to multiple efforts to visualize crime data. One of them featured an illustration (I split it into four parts for easy viewing).  I’m sure the graphic elides details in the data, but I still think it’s interesting.  I challenged some of my preconceived notions about who dies by gun, and you may find it surprising too.

The data is from 2004.  That year, an average of 81 people died from a gunshot wound each day.  In the figures below, each bullet represents 81 deaths; grey bullets are homicides, pink suicides, and yellow accidents or being killed by a police officer.

(Methodological note: Differences in gun deaths by age group could be a matter of lifecycle or it could be a cohort effect.  Since this data is a snapshot and not longitudinal, it’s hard to tell.  Also, when you’re comparing age groups, it’s important to remember that people in these four age groups are not evenly distributed across the population.)

17

Five percent of the people who died due to guns was age 17 or younger (I say “only” advisedly).  People under 18 make up about 24% of the population.  Black men and white men are murdered at about the same rate (one a day, or one every 30 hours, respectively) which means that blacks are disproportionately victims of murder because they make up 12-13 percent of the population as opposed to the 80 percent of the population that is white.  Men are four times as likely as women to be killed. There were about half as many suicides as there were murders, and half as many accidents/police killings as well.

18-25

About 21 percent of all gun deaths were among people ages 18 to 25.  About 90 percent of all murder victims are men, and about half of those are black men.  Accidents/police action are occurring at about the same rate, but suicides have skyrocketed.  There are five times more suicides among people 18 to 25 than there were among those 17 and under.  Four-fifths of the people who choose to take their own life are white men (who make up less than 40% of the population).

26-391

People 26 to 39 years old accounted for 26 percent of gun deaths.  The murder rate has a similar racial distribution.  Like before, the rate of accidents/police killings have stayed the same.  But suicide rates have continued to climb.  There are nearly twice as many suicides among this age group as there were in the previous one.  The majority of these are white men.  One in nine was a woman.

40

Among those 40 and over (48 percent of all gun deaths occur to someone over 40), there is a stark increase in the number of suicides.  There were 2,430 suicides, compared to 1,215 suicides among all other age groups combined.   Eighty-three percent of these suicides are committed by white men.  Murder has finally decreased and the racial and gender distribution is less uneven than before.  There are twice as many accidents/police killings among this cohort.

Media portrayals of gun violence tends to highlight women who are murdered (especially if you watch crime and law TV shows), black on white violent crime (if you watch the news), youth violence (take your pick), and murder over suicide.   This graphic challenges all of those notions.

This site lets you parse out data for homicides in Philadelphia by gender, age, time of day, and weapon, and this site lets you parse out similar data for homicide in Los Angeles county.

Lisa Wade, PhD is a professor at Occidental College. She is the author of American Hookup, a book about college sexual culture, and a textbook about gender. You can follow her on Twitter, Facebook, and Instagram.

A message written in 1914 and curled into a corked bottle was scooped out of the North Atlantic last month (NatGeo).  Not a love note, but a research instrument.The Glasgow School of Navigation sent 1,890 such bottles adrift, hoping to map deep ocean currents.  They were weighted to float just above the ocean floor.  The message inspires me to contemplate just how far our research methods have come in the last 98 years.

Via BoingBoing.

Lisa Wade, PhD is a professor at Occidental College. She is the author of American Hookup, a book about college sexual culture, and a textbook about gender. You can follow her on Twitter, Facebook, and Instagram.

I watched the first U.S. Presidential debate of the election last night and I noticed something interesting about the coverage at CNN.  Notice that the live viewer information along the bottom includes the degree to which female (yellow) and male (green) Colorado undecided voters like or dislike what each candidate is saying (measured by the middle bar).

By choosing to display data by gender, CNN gives us some idea of how men and women agree or disagree on their evaluations of the candidates, but it also makes gender seem like the most super-salient variable by which to measure support.  They didn’t, for example, offer data on how upper and middle class undecided voters in Colorado perceived the debate, nor did they offer data on immigrant vs. non-immigrant, White vs. non-white, gay vs. straight, or any number of demographic variables they could have chosen from.

Instead, by promoting gender as the relevant variable, they also gave the impression that gender was the relevant variable.  This makes it seem like men and women must be really different in their opinions (otherwise, why would they bother highlighting it), strengthening the idea that men and women are different and, even, at odds.  In fact, men and women seemed to track each other pretty well.

It’s not that I don’t think gender is an interesting variable, it’s just that I don’t think it’s the only interesting one and making it seem so is problematic.  I would have loved to have seen the data parsed in other ways too, perhaps by rotating what variables they highlighted.  This would have at least given us a more nuanced view of public opinion (among undecided voters in Colorado) instead of reifying the same old binary.

Lisa Wade, PhD is a professor at Occidental College. She is the author of American Hookup, a book about college sexual culture, and a textbook about gender. You can follow her on Twitter, Facebook, and Instagram.

Cross-posted at Family Inequality.

You can’t get 18 pages into Hanna Rosin’s blockbuster myth-making machine The End of Men, before you get to this (on page 19):

One of the great crime stories of the last twenty years is the dramatic decline of sexual assault. Rates are so low in parts of the country — for white women especially — that criminologists can’t plot the numbers on a chart. “Women in much of America might as well be living in Sweden,* they’re so safe,” says criminologist Mike Males.

That’s ridiculous, as I’ll show. Rape is difficult to measure, partly because of limiting state definitions, but the numbers are consistent enough from different sources to support the conclusion that reported rape in the United States has become less common in the last several decades — along with violent crime in general. This is good news. Here is the rate of reported “forcible rape” (of women) as defined by the FBI’s crime reporting system, the Uniform Crime Reports.**  See the big drop — and also that the rate of decline slowed in the 2000s compared with the 1990s:

(Source: Uniform Crime Reports, 2010)

The claim in Rosin’s book — which, like much of the book, is not sourced in the footnotes — is almost too vague to fact-check. What is “much of the country,” and what is a number “so low” that a criminologist “can’t plot” it on a chart? (I’m no criminologist, but I have even plotted negative numbers on a chart.)

Even though she makes things up and her publisher apparently doesn’t care, we must resist the urge to just ignore it. The book is getting a lot of attention, and it’s climbing bestseller lists. Just staying with the FBI database of reported rates, they do report them by state, so we can look for that “much of the country” she’s talking about. I made a map using this handy free tool.

(Source: FBI Uniform Crime Reports, 2010, Table 47)

The lowest state rate is 11.2 per 100,000 (New Jersey), the highest is 75 (Alaska). You can also get the numbers for 360 metropolitan areas. For these, the average rate of forcible rape reported was 31.5 per 100,000 population. One place, Carson City, Nevada, had a very low rate (just one reported in 2010), but no place else had a rate lower than 5.1. (you can see the full list here). I have no trouble plotting numbers that low. I could even plot numbers as low as those reported by police in Europe, where, according to the European Sourcebook of Crime and Criminal Justice Statistics, for 32 countries in 2007, the median rate was just 5 per 100,000 — which is lower than every U.S. metropolitan area for 2010 (except Carson City, Nevada).

These police reports are under-counts compared with population surveys that ask people whether they have been the victim of a crime, regardless of whether it was reported to police. According to the government’s Crime Victimization Survey (CVS), 65% of rape/sexual assault is not reported. The CVS rate of rape and sexual assault (combined) was 70 per 100,000 in 2010. That does reflect a substantial drop since 2001 (although there was also a significant increase from 2009 to 2010).

And what about the “for white women especially” part of Rosin’s claim? According to the Crime Victimization Survey (Table 9), the white victimization rate is the same as the national average: 70 per 100,000.

I hope it’s true, as Rosin says, that “what makes [this era] stand out is the new power women have to ward off men if they want to.” But it’s hard to see how that cause is served by inventing an end of rape.

—————————

*That is an unintentionally ironic reference, because Sweden actually has very high (for Europe) rate reported rape, which has been attributed to its broad definition and aggressive attempts at prosecution and data collection.

** Believe it or not, this was their definition: “the carnal knowledge of a female forcibly and against her will. Attempts or assaults to commit rape by force or threat of force are also included; however, statutory rape (without force) and other sex offenses are excluded.” That is being changed to include oral and anal penetration, as well as male victims, but data based on those changes aren’t reported yet.

Check the Hanna Rosin tag for other posts in this series.

I’m supervising senior theses this semester and so I have to be a super stickler about something that makes most students’ eyes roll back in their heads: operationalization.  Wait!  Keep reading!

The term refers to a careful definition of the variable you’re measuring and it can have dramatic influences on what you find.  Dmitriy T.C. sent in a great example.  It involves whether you include church donations in your definition of “charity.”   Friendly Atheist breaks it down.

If you include church donations, the South appears to be the most generous U.S. region:

But if you don’t, everyone looks a whole lot stingier and the Northeast comes out on top:

All you budding sociologists out there remember!  Think long and hard about how to define what you’re measuring.  It can make a huge difference in your results.

Lisa Wade, PhD is a professor at Occidental College. She is the author of American Hookup, a book about college sexual culture, and a textbook about gender. You can follow her on Twitter, Facebook, and Instagram.

Cross-posted at Family Inequality.

In 2010, 28% of wives were earning more than their husbands. And wives were 8-times as likely as their husbands to have no earnings.

I still don’t have my copies of The End of Men, by Hanna Rosin, or The Richer Sex, by Liza Mundy. But I’ve read enough of their excerpts to plan out some quick data checks.

Both Rosin and Mundy say women are rapidly becoming primary earners, breadwinners, pants-wearers, etc., in their families. It is absolutely true that the trend is in that direction. Similarly, the Earth is heading toward being devoured by the Sun, but the details are still to be worked out. As Rosin wrote in her Atlantic article:

In feminist circles, these social, political, and economic changes are always cast as a slow, arduous form of catch-up in a continuing struggle for female equality.

Which is right. So, where are we now, really, and what is the pace of change?

For the question of relative income within married-couple families, which is only one part of this picture — and an increasingly selective one — I got some Census data for 1970 to 2010 from IPUMS.

I selected married couples (called “heterogamous” throughout this post) in which the wife was in the age range 25-54, with couple income greater than $0. I added husbands’ and wives’ incomes, and calculated the percentage of the total coming from the wife. The results show and increase from 7% to 28% of couples in which the wife earns more than the husband (defined as 51% or more of the total income):

(Thanks to the NYTimes Magazine for the triumphant wife image)

Please note this is not the percentage of working wives who earn more. That would be higher — Mundy calls it 38% in 2009 — but it wouldn’t describe the state of all women, which is what you need for a global gender trend claim. This is the percentage of all wives who earn more, which is what you need to describe the state of married couples.

But this 51% cutoff is frustratingly arbitrary. No serious study of power and inequality would rest everything on one such point. Earning 51% of the couple’s earnings doesn’t make one “the breadwinner,” and doesn’t determine who “wears the pants.”

Looking at the whole distribution gives much more information. Here it is, at 10-year intervals:

These are the points that jump out at me from this graph:

  • Couples in which the wife earns 0% of the income have fallen from 46% to 19%, but they are still 8-times as common as the reverse — couples where the wife earns 100%.
  • There have been very big proportionate increases in the frequency of wives earning more — such as a tripling among those who earn 50-59% of the total, and a quadrupling among those in which the wife earns it all.
  • But the most common wife-earning-more scenario is the one in which she earns just over half the total. Looking more closely (details in a later post) shows that these are mostly in the middle-income ranges. The poorest and the richest families are most often the ones in which the wife earns 0%.

Maybe it’s just the feminist in me that brings out the stickler in these posts, but I don’t think this shows us to be very far along on the road to female-dominance.

Previous posts in this series…

  • #1 Discussed The Richer Sex excerpt in Time (finding that, in fact, the richer sex is still men).
  • #2 Discussed that statistical meme about young women earning more than young men (finding it a misleading data manipulation), and showed that the pattern is stable and 20 years old.
  • #3 Debunked the common claim that “40% of American women” are “the breadwinners” in their families.
  • #4 Debunked the description of stay-at-home dads as the “new normal,” including correcting a few errors from Rosin’s TED Talk.
  • #5 Showed how rare the families are that Rosin profiled in her excerpt from The End of Men

Cross-posted at Family Inequality.

It is great to acknowledge and celebrate the increase in father involvement in parenting. But it is not helpful to exaggerate the trend and link it to the myth-making about looming female dominance. Yesterday’s feature in the Sunday New York Times does just that, and reminds me that I meant to offer a quick debunking of Hanna Rosin’s TED talk.

The story is headlined “Just Wait Till Your Mother Gets Home.” The picture shows a group of dads with their kids, as if representing what one calls “the new normal.” Careful inspection of the caption reveals it is a “daddy and me” music class, so we should not be surprised to see a lot of dads with their kids.

The article also makes use of a New Yorker cover, which captures a certain gestalt — it’s a funny exaggeration — but should not be confused with an empirical description of the gender distribution of parents and playgrounds:

Naturally, the story is in the Style section, so close reading of the empirical support is perhaps a fool’s errand. However, I could not help noticing that the only two statistics in the story were either misleading or simply inaccurate. In the category of misleading, was this:

In the last decade, though, the number of men who have left the work force entirely to raise children has more than doubled, to 176,000, according to recent United States census data. Expanding that to include men who maintain freelance or part-time jobs but serve as the primary caretaker of children under 15 while their wife works, the number is around 626,000, according to calculations the census bureau compiled for this article.

The Census Bureau has for years employed a very rigid definition of stay-at-home dads, which only counts those who are out of the labor force for an entire year for reasons of “taking care of home and family.” This may seem an overly strict definition and an undercount, but if you simply counted any man with no job but with children as a stay-at-home dad, you risk counting any father who lost a job as stay-at-home. (A former student of mine, Beth Latshaw, now at Appalachian State University, has explored this issue and published her results here in the journal Fathering.)

In any event, those look like big numbers, but one should always be wary of raw numbers in the news. In fact, when you look at the trend as published by the Census Bureau, you see that the proportion of married couple families in which the father meets the stay-at-home criteria has doubled: from 0.4% in 2000 to 0.8% today. The larger estimate which includes fathers working part-time comes out to 2.8% of married couple families with children under 15. The father who used the phrase “the new normal” in the story was presumably not speaking statistically.

(Source: My calculations from Census Bureau numbers [.xls file]. Includes only married-couple families with children under age 15.)

 

That’s the misleading number. The inaccurate number is here:

About 40 percent of women now make more than their husbands, the bureau’s statistics show, and that may be only the beginning of a seismic power shift, if new books like “The Richer Sex: How the New Majority of Female Breadwinners Is Transforming Sex, Love, And Family,” by Liza Mundy, and “The End of Men: And the Rise of Women,” by Hanna Rosin, are to be believed.

I guess in these troubled times for the newspaper business it might be acceptable to report X and Y statistic “if so-and-so is to be believed.” But it is a shame to do so when the public is paying the salary of people who have already debunked the numbers in question. Just the other day, I wrote about that very statistic: “Really? No. I don’t know why this keeps going around.” Using freely available tables (see the post), I calculated that a reasonable estimate of the higher-earning-wife share is 21%. In fact, on this point Liza Mundy and Hanna Rosin and are not to be believed.

(Source: My graph from Census Bureau numbers.)

 

TED: Misinformation Frequently Spread

There is a TED talk featuring Hanna Rosin from the end of 2010, and I finally got around to watching it. Without doing a formal calculation, I would say that “most” of the statistics she uses in this talk are either wrong or misinterpreted to exaggerate the looming approach of female dominance. For example, she says that the majority of “managers” are now women, but the image on the slide which flashes by briefly refers to “managers and professionals.” Professionals includes nurses and elementary school teachers. Among managers themselves, women do represent a growing share (although not a majority, and the growth has slowed considerably), but they remain heavily segregated as I have shown here.

Rosin further reports that “young women” are earning more than “young men.” This statistic, which has been going around for a few years now, in fact refers to single, child-free women under age 30 and living in metropolitan areas. That is an interesting statistic, but used in this way is simply a distortion. (See this post for a more thorough discussion, with links.)

Rosin also claims that “70% of fertility clinic patients” prefer to have a female birth. In her own article in the Atlantic, Rosin reports a similar number for one (expensive, rare) method of sex selection only (with no source offered) — but of course the vast majority of fertility clinic patients are not using sex selection techniques. In fact, in her own article she writes, “Polling data on American sex preference is sparse, and does not show a clear preference for girls.”

Finally, I don’t think I need to offer statistics to address such claims as women are “taking control of everything”and “starting to dominate” among “doctors, lawyers, bankers, accountants.” These are just made up. Congress is 17% female.

Philip N. Cohen is a professor of sociology at the University of Maryland, College Park, and writes the blog Family Inequality. You can follow him on Twitter or Facebook.

At the journal Epidemiology, John Cunningham published a proof-of-concept article aimed to show that Twitter is a useful and viable method of data collection.

His data captured the incidences of the words “wine,” “beer,” and “vodka” over the course of a week.  The figure shows that people are tweeting about these spirits more-or-less in unison, that they tend to do so increasingly towards the end of each day, and that wine and beer are weekday favorites, but vodka comes out ahead on the weekends, especially as the night wears on:

So, I thought that was kinda neat!  Now we know something about when and what people are (tweeting about) drinking and also that Twitter is good for something other than sending people messages that everyone else can see, but no one else can understand.

*Via Neuroskeptic, from whom I borrowed this great title.

Lisa Wade, PhD is a professor at Occidental College. She is the author of American Hookup, a book about college sexual culture, and a textbook about gender. You can follow her on Twitter, Facebook, and Instagram.