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Updated list

I've updated the list of programs and how many years each guarantees its assistantships. In the meantime, Clancy asks some good questions about the ways that programs spin their placement statistics.

Two things occur to me: first, our answer to some of those questions is to keep our alumni page relatively up-to-date. We don't track selectivity or search length, although some of that information would be fairly easy to track as well.

The second thing that occurs to me is that it wouldn't be the worst thing in the world for us to put some pressure on the Consortium to develop a central location for information like this (and like my list). For better or worse, we don't always do a great job of understanding exactly what it is that prospective students want to know about a program. I never shopped for a PhD program, for example. I fell into mine largely by accident. I've gotten better as a DGS of identifying that data, but as of yet, I know of no attempts to gather it together, given that our programs don't overlap completely with the programs tracked by ETS.

So if I'm still missing info, please let me know, particularly if it's online and I've missed it. If it's not online, encourage your programs to put it up there. And give some thought to what kinds of information it might be good to centralize.


Thanks Collin. I think I had a typo on the New Mexico link. the first "P" in the "pandP.pdf" should be capitalized (it's case sensitive).

I'm glad you have the energy and the willingness to do this kind of thing. Did they clone you, incidentally? 'Cause if they did, we could use a copy up here in Fargo.

Job placement data over time would also be good to have (both with individual years and cumulative percentage). If I hear "we have a 100% placement rate," I want to know the time period that covers. I want to know, for example, whether the sample covers placement since the inception of the PhD program, or if it just covers the past year or two, when the program might have had a particularly outstanding cohort of graduate students.

Interpreted differently, data over time could make the department look better, especially if it were accompanied with comments from DGSs about mentoring. For instance, the data could show that a program is making positive changes that lead to improvement in its placement statistics.

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