What's the lesson, that you can learn anything eventually, or that familiarity means you will lose the ability to accurately evaluate something?
My pre-org notes file was just a giant text file with entries delimited by manually-entered '--------------' lines. I stuck a topic in each entry for searchability and then the rest was freeform text. It worked pretty well.
org mode gives me more power, but it's getting a little unmanageable. I find myself expanding and collapsing sections a lot, especially when just trying to find the right place to add a new entry. (I'm using a hierarchy rather than the flat append-only list.) The file is pretty huge at this point, and I split it up once but that broke my most common usage of just isearching through the entire file, and it was annoying to have to load multiple files to do a complete search. I had links between files, but that didn't help for searching.
I imagine there are tips and tricks to resolve all of my issues and nuisances, but I've never taken the time to figure them out. Is there a good workflow description somewhere that I should be looking at? It's hard to beat a basic text file, but after a decade or so it has gotten pretty big and I'd like to eg be able to cluster related things together so I can purge obsolete stuff.
Maybe my problem is that org mode is intended for organizing things, and my use case is too free-form?
… or Mathematics for Machine Learning
There are YouTube videos for both books:
Axler: https://youtube.com/playlist?list=PLGAnmvB9m7zOBVCZBUUmSinFV...
MML: https://youtube.com/playlist?list=PLiiljHvN6z1_o1ztXTKWPrShr...
On a more serious note, why do ethical vegan proponents feel it is better for an animal to never live at all? To be devoid of purpose due to lack of existence?
Yes, I thought this was clear from my statement.
“Rotation would not make a difference”
It would. The offsets generated by the hash would repeat every 32 shifts, but the absolute addresses given in the collision cases are a random construction based on the history of the tree at that point, so despite the offsets’ repeating, the tree’s invariants along the lookup are likely to be preserved.