Graphic Sociology

What a man wanted, what a man wants | Boxer, Noonan, and Whelan

What Men and Women Want in a Mate, 1939-2008 | Boxer, Noonan, and Whelan

Update on references

As you can see in the comments, Christie Boxer, the lead author of the journal article behind the Coontz Opinionator piece has contacted me to let us all know that the article is currently in revise and resubmit phase but will be published in Journal of Family Issues shortly.

What works

The graphic is more legible than the chart from which the data originated. I’m guessing the Journal of Family Issues would not allow such a “fancy” series of graphics in the final published piece so I don’t mean this as a critique of the article’s authors. Just pointing out that there is good reason for journals and other publishers to reconsider their policies about how data can most usefully be presented.
I happen to have created a few graphics in this style myself and tend to favor it over the chart (e.g. this one about agricultural subsidies) in the past and think they work well for displaying changes in attitudes over time.

What needs work

Illustrations to Accompany "The M.R.S. and the PhD" by Stephanie Coontz, New York Times

The article from which this news story is drawn clearly provides information on both what women want and what men want in greater detail than what’s seen here. Why did the news story choose to run with less than half the data?
The chart clearly contains information on what men want in a mate AS WELL AS what women want in a mate. I see no reason for going (less than) halfway on this story. In fact, what I find most interesting is the convergence on some things – nobody cares much about chastity in a mate any more – and divergence on other traits – women rank men’s desire for home and children much higher than men rates women’s desire for home and children. That’s a puzzler worthy of thought in a way that a story that reflects only what men want is…well…just not all that interesting. Pair bonding takes two, as I’m sure Coontz knows because she’s been researching marriage for years. It’s unclear if the Times pressured her to come up with a more attention grabbing headline “The M.R.S. and the PhD” or if she chose that on her own or if it was a combination of factors.

I’m glad to see that, at least as far as I can tell from what is available to scholars other than Coontz (who might have an early full-length, unreleased draft of the Boxer, Noonan, Whelan paper), the scholars whose data led to the graphic were not so singly concerned with what men want in a mate. They were looking at how mate selection characteristics have been adjusted over time for both men and women and I hope that their article looks at the consonance and dissonance between the two genders’ mate selection ideals.

I would have preferred more attention paid to the graphic – like, say, the inclusion of what women want or an integrated graphic that displayed the overlaps and distances between what men and women want – and less time put into the accompanying illustrations which I have included to the left. I welcome regular readers of Sociological Images (and others) to comment on the messages coming out of the illustrations.

References

Coontz, Stephanie. (2012) “The M. R. S. and the PhD”. The New York Times, Sunday Review, Opinionator. [Information graphic by Bill Marsh/The New York Times]

Boxer, Christie; Noonan, Mary; and Whelan, Christine. (forthcoming) “Measuring Mate Preferences: A Replication and Extension” Journal of Family Issues. [Table drawn from Christine Whelan's research webpage]

Partnership-driven infrastructure project financing | Creating a formula for success from existing projects

Visualizing Finance

For almost a year I have been working at the Center on Law and Public Finance, a center based at New York University’s Institute for Public Knowledge, which is currently dedicated to research on American infrastructure. Infrastructure has a halo of geeky coolness about it that is a combination of the tinkerers desire to figure out “How Things Work” ala David MacCaulay and the awe of beholding massive public works projects like the Hoover Dam, the Tappan Zee bridge, and New York City’s monumental water delivery system.

Tappan Zee Bridge | ABC Local

Right now, though, the debate in DC and in various states is about how we can pay for the upgrades and extensions of our infrastructure that are badly needed. It’s also about just what counts as infrastructure. We define infrastructure as physical, regulatory, bureaucratic, and behavioral assemblages that are durable over time. This is a fairly academic definition, but it allows for the inclusion of not only of bridges, roads, ports, and mass transit, but also of things like suicide prevention hotlines, manufacturing plants, and educational institutions. Once we broaden the definition to include a more realistic, inclusive set of infrastructures that underpin civic, commercial, and social life, the challenge of explaining how we might pay for these projects gets even harder.

For our most recent report, “Partnership-driven Growth: A bipartisan way forward”, I tried to develop a flexible strategy for demonstrating the reliance on partnerships of monetary and non-monetary support that come together to meet the specific needs of particular projects, while following a loose template adopted by many infrastructure projects. Since infrastructure generally benefits many constituencies, including civic society, the most common successful infrastructure funding is like a collage. Often, successful projects draw on a modest amount of federal support, either in the form of loans, loan guarantees, or (matching) grants. These federal dollars are good at acting as funding anchors (and votes of confidence) which tend to smooth the way for states, local governments, and private investors to commit their own funds and support to the projects.

One of the things I wanted to emphasize with the graphic was that though each project presents a unique ‘flower’, there is a general formula for success. Nobody is out there re-inventing the wheel with respect to financing vehicles even though it might sometimes feel like that for local governments, states, and private investors who haven’t built many financing vehicles. I was also trying to find a way to indicate that not all support for infrastructure projects is monetary support. Sometimes support comes from a willingness to change a zoning law or to create a partnership with a local university where the business, design, or engineering school dedicates time and effort to overcoming challenges within the infrastructure or business plan.

The page you see at the top of the post was the frontis-page for a section in the report that looked at a number of case studies. Each case study contained the same “flower” from the frontispiece with a lengthier description of just how much of which kinds of funding were involved. I’ve included the relevant page of the Tesla case study below, just to demonstrate how the design was developed within the report. I wanted the frontis-page to this section to give readers pause – they had just made it through about 10 pages of prose – and to help them connect individual projects back to a general ‘formula for success’. Hence, I repeated the flower form from the frontis-page in each of the case studies, hoping that a little repetition would help to cement key concepts.

Tesla Fremont partnership project case study

Infrastructure banks

Politically, the reason it is important to understand how infrastructure financing works when it is successful, is that both at the national level and within particular states, lawmakers are considering establishing infrastructure financing authorities (hereafter referred to as infrastructure banks). The exact dimensions of these banks are still being hashed out. Will they fund only certain sectors of infrastructure like transit, energy, and manufacturing or should they include social infrastructure, too? Will they use revenues generated by some of the stronger infrastructure sectors to help support those sectors that are less likely to be self-sufficient? Or, should each project be responsible only for its own bottom line? Since infrastructure has a long time horizon, what is the best way to set up lifecycle-aware financing structures?

Electric Vehicle Charging infrastructure schematic | Schneider Electric

Our current work tries to build a baseline of understanding so that decision makers, including voters, will have a framework within which to advocate properly for their own interests while keeping an open mind about the visionary possibilities of infrastructure banks. This discussion needs to be much bigger than one that only responds to the “we’re in a recession, let’s find a rapid cash infusion from the private sector” frame. A new bank could do much more than that. It could be time to reconsider agency structures and break down silos; it could be time to reexamine the way infrastructure necessary for commerce relates to private sector revenues; it could be time to recognize synergies between sectors that make more sense now than they did in the past (the energy sector and private automotive transportation have something different to say to each other as more cars are electric, for instance. Social infrastructure and broadband supporters have a different conversation now that so many people turn to the internet for social services and broader social support).

There will be more to come in this series. The conversation is just getting started.

Criticism welcome

As always when I present my own work, I invite criticism. Readers of this blog have been generous (and civil) with their comments in the past and I am quite grateful to have such a thoughtful readership.

References

Likosky, Michael and Norén, Laura. (January 2012) “Partnership Driven Growth: A bipartisan way forward” [Report] Center on Law and Public Finance, Institute for Public Knowledge, New York University.

Living Alone by Gender, Age Cohort in the US since 1850

What works

This post is an update to an earlier post about the increasing rate of Americans living alone. The first graph does an excellent job of visualizing the change in Americans’ tendencies to live alone, by age and gender. It’s clear that living alone is on the rise, especially for Americans over 45. It’s interesting that there seems to be a collective slow down in this trend in the decade between 35 and 45 when I suppose some of the late-to-marry people finally settle down and before the marital dissolution rate starts to fire up.

The graphics in this post accompanied an article by Eric Klinenberg in the New York Times Sunday Review that laid out the basic findings in his latest book, “Going Solo” that was based on 300 interviews with people living alone. He finds that while for some, living alone is an unwanted, unpleasant experience, most people who live alone are satisfied with their personal lives more often than not. In fact, they are more social, at least in some ways, than are their counter-parts who live with others. Singletons (his word, not mine. I prefer ‘solos’ in part because it’s an anagram), go to restaurants and other social spaces more often than do those who live with others.

Living alone in Minneapolis

In a number of cities, including Minneapolis, more than 40% of households are single-people households. The article included an interactive map down to the census tract level that shows what percentage of households in that tract were single-person households in 2010. I took a look at Minneapolis and St. Paul and found that the map supported Klinenberg’s qualitative findings. The highest concentration of solos is in the center city areas where opportunities to get out and be social in the community are the highest. The suburbs and rural areas have fewer solos.

I encourage others to use the map and see if their local cities replicate this pattern, that more solos live in ‘happening’ areas than in quieter areas. Of course, this could be caused by a third variable, the presence of households that are affordable for single-earner households…but there isn’t enough analytical power in the map tool to be able to sort out the dependencies.

What needs work

The information about who lives alone by age, marital status, and race that is displayed in the following long skinny stack of datapoints is the right kind of detailed information to use as an entrance into a deeper discussion about living alone, now that we’ve gotten a sense of the view from 30.000 feet. The problem is that this graphic is hard to read, too long for a single computer screen (but in order to make sense of it, one needs to see the whole thing at once), and too optimistic about what color differences are able to do than is reasonable.

The article does a better job of subtly navigating the movement from historical and international context into a detailed, robust analysis. By awkwardly pinning all the data points onto the stalk at once, viewers lose the ability to see patterns within data subsets. Here’s a test. Look at the following data and try to explain to yourself how race and living alone go together. Or how age and living alone go together. The graphic designer was hoping color would be able to do more than it has been able to accomplish here. The color is supposed to tunnel your vision down to a particular color-coded subset so that you can start to understand well just what it is about race or age or marital status that produces particular patterns in living alone. But I had a lot of trouble with the color frame because, quite literally, I had to keep shifting the frame around this graphic – it didn’t fit on my laptop screen. [Graphic designers often work on nice, roomy screens where they end up seeing more at once than their eventual audience who is probably peering at this thing from a web browser on a laptop or occupying half of a monitor somewhere.]

All the clustering around the mean is another problem that could have been avoided had the graphic been organized differently. As it is, all sorts of groups lump on top of one another down around 14%.

I also kind of hate that I can’t add categories together in any meaningful way here. I can tell that being a widow would put someone at high risk for living alone, but that’s kind of a no-brainer, isn’t it? I would have gotten more mileage out of visualizing the absolute numbers of people living alone by marital status, age, and race. Maybe over half of all widows live alone, but I haven’t the faintest idea how many widows there are in America so I don’t know if half of all widows is half a million people? Or 3 million people? Or whether it’s more or less than the 38% of separated people who are living alone. 19% of never married’s live alone, but because these people are likely to be young, maybe that is actually a larger absolute group than the 58% of widows living alone.

Final verdict: There was both a data fail and a graphic design fail.

Who lives alone? A demographic breakdown

References

Going Solo Cover

Klinenberg, Eric. (2012) One’s a Crowd. New York Times Sunday Review.

Weber, Susan and Beveridge, Andrew. (2012) [infographics]
Solo in America graphic Line graph looking of the changing percentage of singleton households in America, 1850-2000
More on their own here…and even more abroad American and International singleton households.
Mapping the US Census: Percentage of Households with only one occupant Interactive graphic of US singleton households by census tract.