I started this post as a reply to the OrgTheory thread on obesity but it got long enough I decided to move it here.
With all due respect, I think the claim that “obesity is not the problem” is overstated. I suspect that this overstatement is due in part to medical sociology’s tendency to infer from the “social construction of <condition>” that <condition> is not really real (see here for more on that). (Quick disclaimer: I have not yet read Abigail Saguy’s What’s Wrong With Fat?, though I hope to soon.)
Continue reading “is obesity a problem?”
Recently, a student who read my book decided to write in a rather nasty comment on this blog. It wasn’t so much about the entry I’d posted, as an attack on me and my book. This same person posted something roughly equivalent on Amazon. I don’t wish to single out this man, because in fact, I get nasty notes fairly frequently. My immediate response in this case was what it usually is: to dig around and find out who the person is and see where they had read the book. I almost always regret this, as I did in this case, because I usually find it’s a place where I’ve given a lecture, and had a wonderful time with the faculty and students. I want to write the faculty in the department to bring it up – particularly if the attacks are vitriolic. I want to out the person and show their colleagues and boss the kind of person they’re working with. I never do. And I want to write back to the person who has attacked me. I want to say to Mr. Mosser, for example, that it’s an honor to have my book hated by someone who is mean-spirited, angry, and cruel – that I consider it a testament to my work, that I would be more upset if someone with his character actually liked it. But this, of course, is a silly retort to make me feel better, and it plays into the same unhealthy dynamic that upset me in the first place. I’ve learned from the rare occasions where I have tried to productively engage that people simply want to spew more of their rage. Continue reading “dealing with nasty comments”
I’m cross-posting an inquiry from my advisee and collaborator Alex Hanna regarding text parsing to convert qualitative descriptions of events into numerical estimates.
I’ve done this myself in the past, but as a human coder using the text descriptions to do qualitative categorization of group size based on my best judgment reading the whole story. FYI the codes I used for Madison protests in the 1990s were: Tiny (1-5), Very Small (6-15), Small (16-30), Modest (31-99), Medium (100-499), Larger (500-1500), Large (2000-10,000), Very Large (10,000 +), and Huge (100,000+) which we then collapsed into Small (1-15), Medium (16-499), and Large (500+).
The problem here is to use automated text parsing of words like “several”, “scores,” “small,” “large,” etc. to categorize protests. I can find substantial literature on the problem of estimating crowd sizes while looking at a crowd and about the diversity of crowd size estimates from different sources (e.g. police and organizers) and about how news reporters decide which sources to use. But I can’t find anything about this problem of trying to get some rough event size estimate from text parsing. Can anyone point us to a source?
Princeton U Press editor Eric Schwartz has a great idea for this year’s ASA baseball trip. Why not go to a minor league game? Cheaper tickets, better seats, and a chance to see some great baseball. So this year, we have cooked up the following plan:
Staten Island Yankees: Friday, August 9 at 7pm
- tickets that cost no more than $25 plus fees
- two free rides on the Staten Island Ferry, which has the best view of the Statue of Liberty (especially now that you can no longer climb into her head)
- throwback jerseys given away to the first 2,500 fans
- amazing views of the Manhattan skyline
- friendly sociologists hanging out together
If we get a group of 10 together, we can get even cheaper tickets (I know, right?). Please email me at email@example.com if you are interested in joining us. Everyone is welcome; don’t be shy.
From the official professional organization representing American academic sociology:
Perhaps first draft of tweet was “Sociologist proves that conservatives are completely deluded morons for suspecting that sociology could have some bias against them.”
Social workers (9%), elementary and middle school teachers (6%), counselors (4%), managers, all other (4%), lawyers (3%), secretaries and administrative assistants (2%), postsecondary teachers (2%), police and sheriff’s patrol officers (2%), human resources workers (2%), first-line supervisors of office and administrative support workers (2%), social and community service managers (2%), sales representatives, wholesale and manufacturing (2%), and education administrators (2%).
According to the American Community Survey, those are the most common occupations for full-time employed people ages 25-55 who were sociology majors in college. To put this in context, I made a graph showing the links between occupations and majors.
A recent report out of Georgetown’s Center on Education and the Workforce recently highlighted variation in income and unemployment by college major. I’m not a fan of this sort of thing, but it did alert me to the fact that the Census’s American Community Survey includes data on college majors. Over at IPUMS, not only can you get the data in an easy to use form, but you can also link respondents to other people in the household with the click of a button. Obviously, I was interested in figuring out how often undergraduate sociology majors marry each other. Continue reading “but who do they marry?”