Neil Degrasse Tyson on being Black, and Women in Science
Why Hacker News recommends it
Linked in diversity-in-tech threads as a personal, thoughtful answer on systemic barriers for minorities and women in science.
What it is
A short clip of Neil deGrasse Tyson answering a question about why there are not more women in science. He describes the resistance he faced as a Black kid pursuing science and the systemic barriers many people encounter.
Recommended by 2 HN commenters across 2 different months, 2014 to 2017.
What Hacker News said
Recommends rflrob · 2014-07 · on “9th Grade Girls Soldering”
While it's true that women and men aren't the same, I think that there are good reasons to believe the level of inequality we have now is not due solely to natural inclination. This video of Neil deGrasse Tyson on minorities and science is apropos: [this video]
Recommends some-guy · 2016-02 · on “Why Tech Degrees Are Not Putting More Blacks and Hispanics into Tech Jobs”
Medicine has many more barriers to entry: schooling, debt, etc. I'm a white high school dropout, but I got a developer position at age 27 after rushing through a CS degree later in live which took about ~3 years. I work 40 hours a week and get a very livable $100k+ salary plus stock and benefits with negligible student debt all things considered (~$30k). My point being, in a vacuum, getting on track to making a good wage as a developer has a lot fewer barriers with the lack of medical school and debt. Not to mention the free time I have outside of work and regular hours. Salary isn't everything. I cannot speak for people of color and their experience who want to go through the same process a
Cites geofft · 2016-02 · on “Slack got four of its black female engineers to accept a startup award”
> They aren't barred in no way in pursuing these kind of careers Admittedly, this is about (academic) science, not tech, but Neil deGrasse Tyson disagrees: [this video]
Cites MattRix · 2017-08 · on “Brief thoughts on the “Google memo””
The problem is that there still are strong systemic biases at work. Once we get that fixed, maybe we can move on to the nitty gritty statistics of exactly what is nature/nurture etc. At this moment it's pointless. It reminds me of this: [this video]