Category: Data

Work in 2030

All models are wrong, but some models are useful.  This phrase, usually attributed to the statistician George Box, is especially apt when it comes to labour market forecasts.  There is an obsession among policymakers about “getting better data” and “getting good labour market projections,” which can in turn (to some extent) drive planning for skills training and post-secondary education.  And it is definitely a phrase that comes to mind when describing the new, bold labour market projection system described in

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Problems in International Institutional Typology

As you all know, a reasonable chunk of my work involves making international comparisons.  This is far from simple in higher education because basic units of analysis differ enormously from one country to another.  Whether you are counting students (do doctoral students count, when in some countries they are classified as employees? How do you equivalize student numbers for part-time status, which exists only in some countries?), or staff (how do you equivalize by rank? Do teaching-only staff count? What

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One Last Thought (Really) on Administrative Bloat, 2020

NOTE: Please see this blog for a correction to the U of T numbers. (I promise this is the last one.) Here is the graph from yesterday and last Wednesday, on academic and non-academic staff numbers, only this time with UBC included because the folks there kindly sent me their numbers. Figure 1: Percentage Growth in Academic vs. A&S Staff numbers, Self-Selected Institutions Which Publish Staffing Data, 2010 to most recent year available              Yesterday, I pointed out that this

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New Enrolment Data. 2017-18. Finally.

Morning all.  There is finally enrolment data from October 2017 for the 2017-18 year.  Praise be StatsCan.  (Some of you think I am a bit hard on the people from Tunney’s Pasture.  Let’s be clear: much of the reason it takes StatsCan so long to put data together is because it takes institutions – particularly community colleges – a long time to compile and submit the data.  My understanding is that part of the reason this year’s release is a couple of years late

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Administrative Bloat, 2020, Part II

After publishing yesterday’s piece, in which I updated a 5-year-old data analysis on spending on academic vs. non-academic salaries, I got a burst of unwarranted optimism and decided to try to do the same thing with another five year-old analysis on the same topic using institutional data – or at least institutional data from the dozen or so institutions who bother to publish this stuff.  Sounds simple, right?  I mean, if they published data before, they must publish it now, right?  How tough

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