Category: Data

Delusional in Delhi

Last week, the Modi government in Delhi released a draft National Education Plan (NEP).  This is a big deal because the last new NEP came out over 30 years ago, and the Modi government has been promising a new one ever since it was first elected in 2014.  It’s also a big deal because it proposes some very big things, especially in higher education.  But Modi while has a reputation for talking up big goals, his track record on delivery is

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From the Shelves of HESA Towers (III)

As each year passes, it becomes harder to remember what exactly life was like before the internet.  How did we communicate?  How did we store and retrieve information?  (A colleague recently commented on twitter that watching All the President’s Men today feels like an ad for Google because the first hour or so is just people looking through phone books).  And, if you were in a specific technical field like higher education, how did you keep track of what was going on

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Two Important Statscan Papers

Statistics Canada released a couple of papers in the last month which unfairly got zero play in the general media, so thought I would pick them up and amplify them here. The first one, by the ever-excellent Marc Frenette, is called Do Youth From Lower- and Higher-Income Families Benefit Equally From Postsecondary Education? and it’s a pretty important question from a public policy point of view, since a good deal of the rationale for widening access is premised on the

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Who Are Canada’s Research Powerhouses?

Yesterday, the good folks at the Centre for Science and Technology Studies at Leiden University released their 2019 world ranking of university research output.  This is – in my opinion – the best bibliometric ranking out there: it is complete, nuanced and the people putting it out have thought hard and responsibly about what it means to use quantitatively evaluate research.  I thought it was time to have a quick look at the research landscape across Canada. Let’s start with raw

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Performance-Based Funding 101: The Algorithm

The biggest missing piece in the Ontario government’s proposed performance-funding system is any discussion of the algorithm by which data on various indicators gets turned into an actual allocation to institutions.  The lack of such a piece is what leads most observers to conclude that the government has no idea what it’s doing at the moment; however I am a glass-half-full kind of guy and take this as an opportunity to  start a discussion that might impact the government’s thinking

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