Links - 4/21/2014

Think that D in high school math means you can't go into STEM?  Think again.  A Salon article on getting girls to choose, and stick with, STEM careers tries to break down the confidence barrier by highlighting that the MIT alum who now develops the curriculum for Girls Who Code did not do so well in high school math.

On a similar note, challenging yourself is worthwhile, even if your grades aren't perfect.  Google would rather you be a B student in CS than an A+ student in English (NYTimes)

Provide equality of opportunity first before looking for answers in our genes.  Neil deGrasse Tyson answers whether it's possible that there is a genetic reason women (or others) are not as likely to pursue STEM fields.  The video is several years old, but for some reason it has been making the rounds recently. NPR has a good summary for those who can't or don't want to watch the video.

Ban potentially dangerous science fair projects?  Science teacher reportedly suspended for allowing "imitation weapon" science projects.  I seem to recall things a bit more dangerous than that going on when I was in high school.

Skepticism is part of science, but skepticism about science is not a good thing.  Maybe that article from last week's links about avoiding the term "theory" was onto something.

Have more links to share?  Put them in the comments or send them to me directly.

Don't Mess Up (Or Keep Trying Until You Succeed)

There are many awesome things about being a woman in a field dominated by men, but one of the less awesome things is the fear of having your failures held against not just yourself but all women.  Piled Higher and Deeper has a great take on this from the perspective of the woman and xkcd takes it on from the perspective of (some) men:

So obviously, the solution if you are a woman is never to make a mistake.  But let's be honest, you will.  Making mistakes is an important part of learning.  When you make that inevitable mistake or two or ten, it's tempting to give up and walk away.  Don't do it.  If you do, you don't have the opportunity to show everyone that you can get it right.  They'll only be able to remember you for the failure and not the triumph.

Links - 4/14/2014

To tide everyone over while I work on my next few posts, here are some science-related links I found interesting last week.

It is because it has been. Why are there so few women in tech?  This parable has the answer.

Be the egg.  Ever wanted to go through a Rube Goldberg machine?  According to this new GoldieBlox video, that's what happens if you study STEM. Although followers know that I prefer inclusive marketing of tech toys over toys aimed exclusively at girls, this is pretty good.

Wired has a new model for scientific lingo. Wired says the terms "hypothesis," "theory," and "scientific law" should not be used - instead we should talk about "models."  Do you agree?

"People didn't invent this stuff because they were bored." This is quite harsh (and uses some R-rated language), but it makes the point that being bad at math is not a badge of honor.

Oh, YouTube comments. Brain Scoop's Emily Graslie tackles sexism related to her YouTube channel.

Have some good STEM-related links?  Post them in the comment section or send me a message.

The Intern Hiring Conundrum

When I say "STEM is for Everyone," I mean it.  STEM is not just for people who do STEM - problems that come up in our daily lives can be solved with the techniques we learn by studying STEM.  When you hear "economics," don't think "price of wheat in a drought," think "hiring interns."

Here's why.  A friend came to me with a problem her organization is having hiring interns. There are 7 divisions in her organization, and it used to be that each division handled intern hiring independently.  Too often multiple divisions would end up giving offers to the same candidates, which confused the candidates and made it harder for the divisions to predict yield (that is, the percentage of candidates that will accept offers).

So a couple of years ago they switched to a coordinated hiring process, where each of the divisions would select their preferred candidates and representatives from each of the 7 divisions would sit in a room to resolve any conflicts.  But these meetings could get very heated and led to inter-divisional conflicts.  So they want to take emotions out of the process and develop a fair system allocate candidates between the divisions.

Economists will recognize this as a matching problem.  Matching is a very complex problem - indeed, a matching algorithm was one of the accomplishments that led to the 2012 Nobel Prize in Economic Science for Lloyd Shapley and Alvin Roth.  For various reasons, the organization is not going to use candidate preferences in making division assignments, which helps simplify the system to a more traditional resource allocation problem.  Drafts, lotteries, and auctions are all mechanisms for allocating scarce resources.  Picking the right system will help you get the right interns to the right groups.  To figure out which is the right system, you need to understand your objectives and constraints, and how each system handles your situation.  After the jump, I go through some of the possible intern assignment systems and their pros and cons.

I should point out that I have not studied either economics or game theory extensively - I find these issues fascinating, but true experts would have a lot more to say about this.