I started this blog post shortly after writing Let’s scrap the long-form census!, but have only recently finished it. No, this is not about “drafting” or conscripting people to fill out long-form versions of the census. It’s about the draft form of a census; that is, how a long-form census is born and its future relevance.
Last week, I highlighted some points from Professor Mor Harchol-Balter’s talk. This week, I would like to focus on a different point she made related to the academia-industry divide.
Reporting of science in popular media such as newspapers and magazines is, in general, of dubious quality. Journalists that report on science, it appears, need no understanding of science. Causation and correlation; statistical significance and knowing something for certain; hype and expectation: in the minds of many journalists, these appear to be equivalent. Can we blame them, though? Even if a scientist’s work is faithfully reported, can we expect readers to keep these things separate? Probably not, but the blame can then be placed on science education and perhaps a lack of space for an article. Approaching an article on the effectiveness of the suicide barrier on the Bloor Viaduct in the on-line version of the Globe and Mail with my low expectations, I was very pleasantly surprised to find an embedded copy of the original report. Kudos to the author, Anna Mehler Paperny, and kudos to the Globe. I hope more organizations learn from this example.
The Department of Computer Science at the University of Toronto is considering changes to its requirements regarding the number of courses students must complete in various sub-disciplines of computer science in order to obtain an M.Sc. or Ph.D. While I am in moderate opposition to these breadth requirements, I present here an argument partially in favour of breadth; this argument is entirely an academic exercise for the sake of challenging my existing views (okay, it’s also fun) and is presented as a single-sided argument.
In the beginning
My first encounter with the scientific method was in grade 4. Purpose? Check. Hypothesis? Check. Procedure? Check. Results and possible sources of error? Check. Conclusion? Check. Congratulations! You’ve just done science! The approach seemed elegant and had rigour. Scientific rigour, if you will. The beauty of it all was that an 8 year old can grasp it.
Flash forward to the present. I hear phrases such as, “Oh, I don’t buy the results of that study” or its equally-evil twin, “Yeah, it’s true. I read it somewhere.” Do you see what I see? Alack! A lack of understanding of the tenets of the scientific method. Or perhaps some laziness in speech — that is more forgivable. However, it often seems as though it is the former.