The Economist, Heather Sarsons, doesn't usually think too much about medicine or health care.

When I started my PhD, I was pretty interested in looking at why we still see gender and race

inequality in labor markets. Heather is a professor at the University of British Columbia,

and most of the time, her work focuses on discrimination. A lot of the models in economics

focus on two types of discrimination, taste-based, which is the idea that people just may not like

other people from a certain group and then statistical discrimination. Statistical discrimination

can also be harmful, but in theory, it doesn't arise from prejudice or racial or gender bias.

Instead, it relies on obvious traits, like race or gender, to make generalizations about a person

If you take the example of, say, women studying math, if historically women are less likely to have

invested in maths and science skills, then employers knowing that might hold women to a higher standard,

and so a woman really has to send a strong signal that, I'm very good at math, I've really studied

this. But it can be exhausting to have to send a strong signal. At some point, it becomes

sufficiently costly to have to study so hard, take so many difficult courses, just to signal that

you're as good as men, and basically the employers' beliefs are reinforced. Women don't invest in

those skills, and the employer is correct in thinking that women are less likely to invest in these

skills. The scenario Heather describes is a self-fulfilling one that's often based on perceptions.

It could be perceptions about anything, how hard working someone is, how smart or capable they are,

how affable they are. But the challenging thing about perceptions is that they're hard to prove

with numbers. If you're creative though, it's not an impossible problem to solve.

I was interested in this question about how we attribute success and failure. If someone performs

really well at their job, do we think that that person's really great at this job, or do we think

that they kind of got lucky or got help? If they perform poorly one day, do we think that they just

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