Awestruck and Stereotyping

Commenter ACertainDoeBear sent me these two videos, both of which I found quite interesting.

The first video (Silva): Excellent concept, good imagery, delivery a bit hard to understand. And by focusing on trying to pick up the words, one can be distracted from the message he’s trying to convey. A little practice, and it can have even wider impact.

The second (Eagleman): I was amused — as I’m right there. That is indeed my approach to things: Consider all things possible then learn so that you can eliminate (or note as reduced likelihood) various possibilities.

I take this approach, for example, with regard to stereotyping. I do, indeed, stereotype on a regular basis. We all do, but I try to approach this consciously and produce a better outcome.

When I say “we all do,” I am talking about how our brains work: Imagine yourself walking down a sidewalk, and that you look up and realize that the shape approaching you is that of a large bear. Your reaction will be different than if the being approaching was a human like yourself. You are stereotyping.  You are making broad guesses about the situation based on how you understand bears’ likely behavior. The same goes for the human encounter. In the case of the bear, you may not be able to prudently learn much more without risk — a notion informed by your own stereotype of bears.

This notion will be different for an animal trainer that knows bears well and is experienced with them, and such a trainer will feel differently and act differently during the encounter. But the trainer will be aware that there are large individual differences between bears, and will be very careful until learning more.

A common human situation is when you are evaluating another person’s ability to do something, whether it’s babysitting or a mathematical challenge.  In the case of the math, you might have heard that “girls don’t do as well as boys in mathematics,” (which may actually not be true) — but what you should envision is a probability pattern spread far up and down from average — and that the two genders will have similar patterns, but slightly offset centers. So sure, the “average” male may be better than the “average” female on task A, and the reverse might be true on task B, but you are dealing with a single point on the graph, not an average. And that point could be anywhere.

I have a niece, a delightful young lady. Of course, females have less muscle than males — and at fourteen, she could deadlift twice my weight straight over her head. I’d wager that far fewer than one in a million males could pull this off. So, any sterotype you might have had in mind about this gal is likely to be wildly off.

But not all, perhaps: She is reputed to like “My Little Pony.”

===|==============/ Keith DeHavelle