Some computing problems are “easy”* to solve. We call these P.
Some problems let us easily check a proposed solution if we’re given one. We call these NP.
All problems in P are also in NP, since checking a solution proposal works is never harder than solving the problem starting from nothing.
We suspect but can’t prove that some problems in NP are not in P.

It turns out that it’s possible to translate any problem in NP into the boolean satisfiability problem (SAT) using an easy algorithm, so this problem effectively is an upper bound on how hard it could be to solve problems in NP - we could always translate them into SAT and solve that instead if that sequence is easier.
We call SAT, and any problem that it can be translated into easily in the same way, the problem class NP-hard.
NP-complete is just those NP-hard problems which are also in NP, which is many but not all of them.

*: require asymptotically polynomial running time

Or sometimes fold them over trees of objects!

make reapportion something that happens every 10 years with the census

That’s… the current state of affairs? New apportionments of Rep seats to states take effect on the 4th year of each decade and have done so consistently since 1933 and in particular the 1929 Permanent Apportionment Act. It also does little for the major structural issues with voting, which are much more about voting method and the drawing of voting district lines.

Nobody ever considers Eve’s side.

It’s genuinely funny to me that one of O’Keefe’s major sins in the eyes of his conservative donors was being such a theater kid he staged a musical hagiography of himself.

Ah yes, the Bismarck solution.

It’s only 1 year ago Biden signed legislation forcing the railroad unions back to work with only 1 day of paid sick leave per worker per year. While as the author says it “One party is capable of rallying to labor’s side”, that feels very much like putting the bar on the ground.