I like to name and shame people who are playing fast and loose with numbers. Usually, this involves taking one “true” data point and then using it to make a point which is unwarranted by the data in context. A couple of examples caught my eye last week.
First up: “Students have at most a 1 in 4 chance that the person at the front of the classroom is a full-time faculty member”.
This is the Canadian Centre for Policy Alternative’s (CCPA) Erica Shaker and Robin Shaban, talking about Ontario Colleges and the number of part-timers in the system (see here for my earlier take on this). Now, let’s be generous and say that their 25% estimate is an innocuous rounding-down of the statement (which seems to be true) that “only 30% of all instructors are full-time”; however, it does NOT follow from this that the chances of having a full-time instructor in any given class is 1 in 4.
Take a hypothetical example. Let’s say you have a college with 1000 instructors, 250 FT and 750 PT (like I say, we’ll grant them the rounding down for the moment). Let’s say further that the average full-time instructor teaches 6 classes a year while the average part-timer teaches 2 (I’m pulling these numbers out of the air because as far as I know there is no public data on this, but if you’re following at home, you can substitute your own numbers here if you think you have better ones). Multiply that out: 250 x 6 = 1500 courses run by full-timers and 750 x 2 = 1500 courses run by part-timers. That’s a 50-50 split, not a 75-25 split. And if you run those numbers without the rounding-down (that is, a 30-70 split, not a 25-75 split), it becomes 1800 vs. 1400, or a 63-37 split.
This should be obvious to anyone who has completed ninth-grade math, so I am not sure what excuse CCPA has for publishing this nonsense. This math, by the way, also applies to all discussions about turning sessionals into full-time staff. Most sessionals teach way less than a full load. Holding the number of courses and class sizes constant (which, absent some magical flood of new money, one pretty much has to), every new full-time hire would eliminate between 2 and 3 part-time/sessional positions. Somehow, this point gets passed over in silence whenever we hear faculty unions talk about “fairness”.
(And, to return to another of my hobbyhorses, this CCPA analysis is exactly why Statscan’s proposed new university staff survey is not a great idea; it will prompt people to base discussions on numbers of personnel and not actual division of total workload. This will make for inane policy discussions).
Next: “Record low youth unemployment”
The second example is perhaps more innocuous than the first, but is important nevertheless. It is a claim made in a backgrounder for the Government of Canada’s recent Fall Economic Statement and you may hear a lot of it the next few months. To wit: that Canada is currently experiencing “the lowest youth unemployment on record”. This is true – the 10.3% rate recorded in September is the lowest since records began in 1976, narrowly beating the previous record achieved in July and September of 1989 – but it doesn’t mean youth employment is booming.
Remember what an unemployment rate actually is: it’s People Without Work Looking for Work (PWWLW) divided by the sum of People Working and PWWLW (the denominator there is sometimes described as (“people in the labour market”). People not looking for work because they are in school full time, for instance, are not included in the calculation. A low unemployment rate can thus either mean “employment is booming” or “there aren’t that many people in the labour market”.
It’s therefore instructive to compare the present day with the summer of 1989, the last time youth unemployment was this low. In July and September of that year, youth unemployment was 10.4%, but youth employment – that is, the fraction of all youth with a job – was over 63%. In comparison, this summer the youth employment rate was hovering between 56 and 57%. That’s not too shabby – it’s about average for the last 40 years and it’s certainly better than it was at any point between 1992 and 2000 </genx get off my lawn speech>. But it is not suggestive of a labour market which is in high gear, either.
The likeliest explanation for the paradoxical combination of low unemployment rate/middling employment rate would be: there’s more 15-24 year olds in school (and hence out of the labour market) than there used to be. That’s probably a good thing overall, but it’s not the image people claiming “youth unemployment at lowest rate EVER” want you to have.
Anyways, stay frosty when evaluating claims made using data. People are trying to fool you: don’t make it easy for them.