Monday, November 11, 2013

A Grad Class -- Maybe

I have a slot for Summer 2014 to teach a special topics graduate-level class at UGA. It can be about anything. In the past I've done summer seminars on the effects of social media, the intersection of humor and politics, and religion and media. This time I'm mulling over something less fun,  a course in secondary analysis. As Wikipedia notes, secondary analysis is "data collected by someone other than the user." The entry continues:
Common sources of secondary data for social science include censuses, organisational records and data collected through qualitative methodologies or Qualitative research. Primary data, by contrast, are collected by the investigator conducting the research.
There are a lot of reasons to like secondary analysis. Someone else has done most of the work, there are no pesky IRBs to deal with, and you get these great national or international samples and therefore terrific generalizability. So what's not to like? You don't always have access to concepts you'd like, measured in ways you'd prefer them measured, and there can be a learning curve when it comes to identifying, downloading, cleaning, and analyzing the data. A steep curve.

Hence ... my possible class, if it can attract students.

There is so much data available. Interested in health? Kids and health? Try getting IRB approval for that. But there's lots of data out there, some collected by the feds, some by others, that even dips into such sensitive topics as drug use. Interested in lifestyle stuff? Internet use? And politics, interested in politics? Oh man, we got your data right here. Well, not here, but at places like GSS, ANES, Pew, Census, and a bunch of federal data best found via ICPSR.

I'm still plotting this class, but basically it'd look something like this:
  •  What is secondary analysis? How it differs from other methods.
  • Read studies that use secondary analysis. Break 'em down.
  • Limitations and strengths of the method.
  • All the different places data exist.
  • Identify concepts students are interested in.
  • How to find your data. 
  • Downloading and cleaning.
  • Your friend, SPSS, for analysis.
  • Recoding variables, getting it right.
  • Running analyses.
  • Writing up your results as a publishable paper.
Okay, that's what I have so far. Most of my scholarly work uses existing data. I'm particularly fond of Pew and ANES, but I've used others.  In fact, I have one dataset right now that must have 10 studies I'll never get around to.

Oh, and the dirty little secret we don't teach students in research methods -- sometimes you skim an interesting dataset and the study will jump out at you. This has happened to me a number of times, including a study that will soon be published in the Journal of Broadcasting & Electronic Media, or the one I'm messing with now where I found a bunch of questions asking what language Latinos prefer to get their news. Having fun with that one and even found a good theoretical base having to do with ties to the ancestral country and political participation. Shhhh, don't mention this to our research methods instructors.

Will the class make? For the academically uninitiated, that means enough students sign up to justify holding the class. All you usually need is five butts in seats, and it's possible it might attract folks from other colleges (political science, maybe, or sociology, or public health).

And of course it all depends on my own single vocal cord getting repaired next month so I can croak out a lecture. Hell, everything rides on that. Luckily, I don't have to make a decision on the class until early Spring.

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