🖙Not-Recent Media of Interest
It's been a while since the prior (and inaugural) media of interest post, so here's another!
- MythBusters. I recently discovered that MythBusters has posted full-length episodes on YouTube. I enjoyed it growing up, and it holds up, although it definitely is a product of its time (mostly in harmless ways). It is a bit inconvenient to find the full-length episodes because it seems like they've taken a lot of them down.1 It's probably less informative, strictly speaking, than the average documentary, but it is a lot of fun. I think the spirit of thinking through problems and figuring out how to test them safely really shines through. It honestly has some parallels to software and data analysis projects I've worked on2, which I think is less to do with software development specifically and more to do with the overall structure of problem solving.
- Queens at Heart UCLA made this documentary about transfeminine people (not using that term) back in the 1960s. Most of the people profiled seem like they'd use the term "trans women" today. I would love if someone caught up with any one who's still surviving.
- Doppelganger by Naomi Klein is a fascinating book that I am on the verge of finishing. It manages to be both a great analysis of our current era and the initial stages of the pandemic. Its discussion of antisemitism is also very relevant now with both the rising tide of actual antisemitism and disingenuous use to deflect criticism of Israel. There's the occasional thing that perhaps is irrelevant or didn't quite hold up, but that's the risk about writing about very recent events, IMO.
I would be remiss if I didn't mention Grant Imahara, who died in 2020, and was a cast member of MythBusters, or Miss Major, who wasn't featured in any of these media but did survive that era of Queens at Heart and died recently. We're poorer without them.
I don't know if the idea is to have a rotation or they're uploading higher-definition versions or if there's some internal push and pull about how much to make available for free versus how much to withhold for a streaming service.↩
E.g., for some data projects, I've done a "scale model" before pulling down huge amounts of data.↩