ASA Job Bank, supply/demand, gender

Rebels without a job?

(Spoiler alert: inside-sociology post.)

(With clarifications marked as marked like this.)

The American Sociological Association’s Department of Research & Development has a new report out on the 2010 academic job market. It focuses mostly on the big news, overall trends and so on. I was more interested in the fate of different specializations.

The data are bound to be messy on this, since both jobs and candidates often include multiple specialties. But still, the report concludes that there are “several notable mismatches between the fields of interest of graduate students and the fields in which departmental searches are most common.”

You can look at their table yourself, on page 7, but since I prefer a different way of looking at it, I made these. The first figure is just the percentage of ads that listed an area (x-axis) versus the percentage of applicants PhD candidates who listed the area in their ASA member profiles. The good news is the correlation is positive, at .37.

I condensed the area names, so sue me. I also color-coded them based on the ratio of demand (ads) to supply (apps), which isn’t obvious from the table or graph. All-caps red is Culture — where apps PhD candidates’ percentage outnumbers ad percentage almost 3-to-1 (that is, 24% of PhD candidates list Culture as an area of interest, but 8% of ads list culture). Sex and gender is the next worst at 1.9-to-1. The best ratio is crime/deviance, which earned green type but not all caps, with a ratio of 1.7 jobs per applicant PhD candidate.

Back in June I made some graphs on the gender composition of sections – the organizations of sub-fields within sociology. Now we can see how the gender composition lines up with the supply-demand situation. (Remember these section compositions are for all section members, not just students.) Here are the sections I could match up reasonably well with the ad/app categories, with demand-over-supply on the x-axis versus gender composition. Areas on the right are smooth sailing for job seekers, those on the left are buyer’s markets for hiring departments (correlation = -.26)

It’s always worth checking, but it doesn’t seem like the main story is women crowding into areas with too many applicants per job, though maybe some of that.

Speculation: Maybe one predictor of poor job prospects is anti-establishment perspectives and (not coincidentally) external support, whether from research funding or non-sociology major teaching demand. That’s just stereotyping the difference between culture/sex-gender/inequalities graduate students versus quant/crim students. (Family and enviro are the ones that don’t fit my stereotypes there, but I’m flexible.)

Feel free to add your interpretations.

7 thoughts on “ASA Job Bank, supply/demand, gender

  1. What *is* the main story? That “soft” specialties are in lower demand than “hard” specialties?

    Anyway, do GAO and Bureau Of Labor Statistics break down gender like you did in your last graph when analyzing why men are paid more than women?


  2. Is there a reason economic sociology isn’t included? I’m curious to see if my assumptions about gender breakdown are correct. (Econ != OOW.)

    I liked both graphs, although I’m not sure it is entirely appropriate to include a trend line on the second graph.

    Anyway, nice work!


  3. Interesting post. Just out of curiosity, what graphics-generating software do you use?

    What I find interesting, vaguely, is that the shortage of crim PhDs relative to demand has been going on for decades. Why hasn’t the market cleared? Is it just because the demand for people to train undergraduates who want to go into law enforcement and corrections has expanded far more rapidly than potential crim PhDs can possibly respond?

    Is it because crim PhD programs have, for various reasons (state funding shortages, primarily), not been able to expand to meet demand for their classes / degrees?

    Or, is it a more fundamental mismatch between between the disciplines of sociology and criminology, at least in its narrower sense (i.e., focus on criminals and criminal justice systems, not on neighborhood correlates of crime ala Sampson, or the effects of felon disenfranchisement ala Uggen)? Which is another way of saying, I guess, that sociology PhDs are irrational in their choice of areas, and/or admissions committees are irrational in their choice of students.


    1. I use Excel to make most graphs. Labeling data points like this is cumbersome, though. I first turn on data value for each point, then edit each one to make it the name instead of the number. That’s easier than floating a tiny text box next to each one because at least if I resize the graph the tags follow the points around…

      As for the crim questions – I really don’t know.

      Thanks for writing.


  4. There’s a large mystery category in the jobs data: the number of positions that are posted as “open.” My impression is that roughly 1/4-1/3 of the jobs are listed as open, and they tend to be at higher status schools with larger departments. Now, what are the fields of the job candidates whom they hire. There may not be any good data on this. My friends report that it’s rarely in gender, but this isn’t reliable.
    What do you know?


  5. “open area” hires = juniors who study the same area as the highest status people in the department, and cite them extensively and flatteringly.

    I’m kidding, of course. I’ve never seen this happen, directly. There is, however, a tendency for departments to replicate themselves, like any other organization.

    Slightly OT: An administrator at my uni speculated that the aging of the faculty and the shift to adjuncts has made departments less able to respond to emergent trends in their disciplines. This makes sense: after the expansion of higher ed in the 1960s, young faculty outnumbered — and could outvote — old faculty. Today, roughly 2/3 of tenure-track faculty are full professors, and there is many a department in which the median age is well into the 60s. Not that 60-70 year-olds always vote against hiring in new subfields, or 30-40 year-olds for it, but it seems plausible that there’s a correlation…


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