Aug 16, 2018 in Falsifiable, Physics, Quick Fix
One of the best things about taking physics classes is that the equations you learn are directly applicable to the real world. Every so often, while reading a book or watching a movie, I’m seized by the sudden urge to check it for plausibility. A few scratches on a piece of paper later and I will generally know one way or the other.
One of the most amusing things I’ve found doing this is that the people who come up with the statistics for Pokémon definitely don’t have any sort of education in physics.
Takes Onix. Onix is a rock/ground Pokémon renowned for its large size and sturdiness. Its physical statistics reflect this. It’s 8.8 metres (28’) long and 210kg (463lbs).
Surely such a large and tough Pokémon should be very, very dense, right? Density is such an important tactile cue for us. Don’t believe me? Pick up a large piece of solid medal. Its surprising weight will make you take it seriously.
May 1, 2018 in Data Science, Economics, Falsifiable
When dealing with questions of inequality, I often get boggled by the sheer size of the numbers. People aren’t very good at intuitively parsing the difference between a million and a billion. Our brains round both to “very large”. I’m actually in a position where I get reminded of this fairly often, as the difference can become stark when programming. Running a program on a million points of data takes scant seconds. Running the same set of operations on a billion data points can take more than an hour. A million seconds is eleven and a half days. A billion seconds 31 years.
Here I would like to try to give a sense of the relative scale of various concepts in inequality. Just how much wealth do the wealthiest people in the world possess compared to the rest? How much of the world’s middle class is concentrated in just a...
Apr 19, 2018 in Data Science, Economics, Falsifiable
The Cambridge Analytica scandal has put tech companies front and centre. If the thinkpieces along the lines of “are the big tech companies good or bad for society” were coming out any faster, I might have to doubt even Google’s ability to make sense of them all.
This isn’t another one of those thinkpieces. Instead it’s an attempt at an analysis. I want to understand in monetary terms how much one tech company – Google – puts into or takes out of everyone’s pockets. This analysis is going to act as a template for some of the more detailed analyses of inequality I’d like to do later, so if you have a comment about methodology, I’m eager to hear it.
Jun 3, 2017 in Economics, Politics
ETA (October 2018): Preliminary studies from Seattle make me much more pessimistic about the effects of the Ontario minimum wage hike. I’d also like to highlight the potential for problems when linking a minimum wage to inflation.
There’s something missing from the discussion about the $15/hour minimum wage in Ontario, something basically every news organization has failed to pick up on. I’d have missed it too, except that a chance connection to a recent blog post I’d read sent me down the right rabbit hole. I’ve climbed out on the back of a mound of government statistics and I really want to share what I’ve found.
Reading through the coverage of the proposed $15/hour minimum wage, I was reminded that the Ontario minimum wage is currently indexed to inflation. Before #FightFor15 really took...