A blog by Jay Livingston -- what I've been thinking, reading, seeing, or doing. Although I am a member of the Montclair State University department of sociology, this blog has no official connection to Montclair State University. “Montclair State University does not endorse the views or opinions expressed therein. The content provided is that of the author and does not express the view of Montclair State University.”
How do you turn data into a good graph? Of course you could ask flâneuse . But suppose you wanted to do it yourself.
Here are the results of a study on preferences in TV sports and in politics – 218,000 interviews conducted over a 13-month period. I’m not sure what the questions were that determined the Democratic and Republican index. The other variables, “Likelihood of voting” and being “very interested” in watching the sport on TV, are fairly straightforward.
The data in the table are sorted on the politics column (R-minus-D Index). PGA golf has the most Republican audience, WNBA the most Democratic.
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How would you graph the data?
Here’s one possibility, found at dqydj (which stands for “Don’t quit your day job,” but you knew that already, didn’t you?).
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Blue bars represent political leaning – the difference between the GOP and Democratic indices. Green bars show likelihood of voting. Sports are listed on the x-axis.
Fabio had a great post a few days ago at orgtheory about how authority structures in a hospital can be hazardous to your health. Even fatal. In the incident Fabio recounts, an anaesthesiologist could see that the patient was having a bad reaction to the surgeon’s latex gloves. But the surgeon refused to switch to non-latex gloves. Surgeons outrank anaesthesiologists, and if the anaesthesiologist had not resorted to extreme measures (threatening to disrupt the surgery in order to call the hospital administrators), the patient would have died.
My first reaction on reading this was: What an incredible asshole the surgeon must be. But Fabio’s point is that the problem is organizational not personal.* The authority structure of the hospital creates an institutionalized arrogance among doctors. The hazardous result is that information doesn’t flow upward from those “on the ground.” (Fabio’s post is here. The comments are also well worth reading.)
Then Fabio asks:
On a deeper level, what sort of organization would allow people to develop such toxic relationships?
And his speculative answer is:
. . . .a combination of high professional autonomy and a garbage can structure. Hospitals, as far as I can tell, aren’t organizations that make one product with a centrally controlled assembly line. Instead, they are a place were “problems” (patients) drift from place to place (ICU, regular, OR, etc) where they might be “solved” (stop showing symptoms) by some random assortment of people who have limited attention (the physicians, nurses, and surgeons). Each physician isn’t in charge of a patient, they do specific procedures and pass the problem along to other people.
Hmmm. Something about that description sounded familiar. So I tried a few “global replace” edits, and it came out like this:
. . . a combination of high professional autonomy and a garbage can structure. Universities are not organizations that make one product with a centrally controlled assembly line. Instead, they are a place were “students” drift from course to course where they might be “taught” by some random assortment of people who have limited attention. Each professor isn’t in charge of a student; they teach specific courses and pass the student along to other people.
I am not saying that universities are necessarily like this. But they do have the potential to resemble what Fabio calls a “toxic culture.”
* The book this anecdote comes from is Safe Patients, Smart Hospitals by Peter Pronovost. Note – not Safe Patients, Good Doctors. The problem lies in the institutional arrangements, not the individuals who work in the institution.
In my classes about inequality, I often use income data, and I don’t usually think too much about what “income” is. Much of the data is on “household income.” “Median household income” presumably reflects the economic well-being of the typical person in that category. It’s often used to compare different groups or regions or trends over time. In the last Presidential campaign, Democrats often pointed out that in the Bush years while the rich had gotten much richer, real median household income had fallen.
Since then, the economy has gotten worse. But it’s possible that household income may rise. The problem is in the denominator of the fraction.
Imagine two siblings, each with a home, each with an income of $100,000. So their average personal income and their average household income are both $100,000 Suppose that one of them loses his job, his house is foreclosed, and he moves in with his sister’s family. Eventually he finds a job paying $50,000 – not enough for him to move out.
Their average personal income in this family has decreased – it’s now $75,000. But since they now have only one household, their average household income has increased to $150,000.
I don’t know how economists deal with this sort of thing. Surely they must have some way of adjusting for it so that we have a fuller picture of what’s happening with the typical American. And one of the things that is happening is that people are doubling up in their houses.
The number of households is shrinking. Many owners who lose their homes are not moving to rentals. Despite the three million foreclosures, rental vacancy rates – nearly 11% – are higher than they’ve been in at least 50 years. Instead, people are moving in with someone else. The number of people per household is increasing.
The trend started in the latter part of the Bush era. Between 2005 and 2008, 1.2 million households disappeared (study commissioned by the Mortgage Bankers Association reported at CNN). So the decline in household income was even worse than the Democrats were making it out to be. In 2009, the trend has no doubt continued.
It’s something to keep in mind when we look at data on household incomes.
The research findings on names, alluded to in yesterday’s post, seems absurd at first glance. Do people really make important life decisions – choices about where to live and what career to follow – because their “implicit egotism” makes a place or profession more attractive if it has echoes of their own names?
Even failure, these psychologists claim, can mesh with this egotism. A study of baseball players across 90 years found that players whose names began with a K were slightly more likely to strike out. The authors (Nelson and Simmons), in a press release, put it this way:
Even Karl ‘Koley’ Kolseth would find a strikeout aversive, but he might find it a little less aversive than players who do not share his initials, and therefore he might avoid striking out less enthusiastically.
The difference is small – 18.8% vs. 17.2% – but statistically significant. Still, I wonder about the studies that the authors didn’t report on. Did they see if those K hitters also had slightly higher rates of hitting home runs? Home runs – four-baggers, blasts, clouts, slams, moonshots – are not brought to you by the letter K. But I think that there may be a correlation between HRs and Ks. If so, those K batters (Kiner, Kingman, Kaline, Killebrew, Kluszewki) are not the guys for whom striking out is ego-syntonic. They’re the muscle boys who swing for the fences. Sometimes they connect, but they also tend to strike out more often.* Perhaps that slight difference in both statistics is a matter of ethnicity rather than egotism.
Something else – the article (or at least the press release about it) reports only on batters. There’s no mention of pitchers throwing strikeouts. Did the authors check to see if a K-hurler was more likely to outfan the rest of the alphabet? Or maybe they did, and just didn’t bother to report the results.*
Then there’s Georgia and Florence. One of the studies reported in the article by Pelham, et. al. finds that the number of women named Georgia living in Georgia is well above what we would expect; ditto for Florences in Florida.
Is this a Peach State effect or a Southern effect? I grew up in Pennsylvania, and I went to school in Massachusetts. I don’t recall meeting any girls or women named Georgia. And I haven’t encountered any among all the students I’ve taught over the years in New Jersey. I think Georgia is more popular in the South, and my guess is that you’d find the name over-represented not just in Georgia but in South Carolina and Alabama too. As far as I know, the researchers didn’t run that analysis.
Florence is also a southern name, at least in Florida. I’d bet a lot of money that those Florences are not evenly distributed throughout the Sunshine State. You probably won’t find too many of them in Tallahassee or Tampa or Orlando. You have to go farther south, say to Miami. Again, my guess is ethnicity, not egotism.
I’m reminded of the old Carnak joke. Carnak was a character Johnny Carson did on the Tonight Show – the mystic who could divine the answers to questions before he had even seen them. He would say the answer, then open the envelope and read the question that was inside. This one is from 1989, when the S&L crisis was at its peak.
I still remember this one after all these years:
The answer: Venice, Rome, and Florence.
The question: Name two Italian cities and the president of Hadassah.
* TheSocioBlog’s first ever post, inspired by a joke from Kieran Healy’s blog, was about negative results.
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