throwawaygh

The reason that HUGE tracts of OZs make no sense is that the “for development of blighted areas” thing is very thinly veiled bullshit.

The average beneficiary of opportunity zones is generationally wealthy. A pair of tech workers pulling down 7 figures a year are stupidly wealthy and still would probably not have enough capital to be the primary beneficiary of an opportunity fund.

I’m not going to defend the salt deduction because I’m not a fan of it for the reasons you mention, but comparing SALT to opportunity zones is genuinely delusional.

Pitting the lower middle class against the upper middle class over a modestly regressive tax break while folks who haven’t worked in three generations pay a 0% tax rate on the fruits of others’ labor.

I really hope this argument is made in court.

They're people, not gods. People like music.

The psychology driving crypto for the last half decade or so is the same sort of psychology that drives penny stocks and scratch-offs. The only people who don't understand this yet are sitting in SV/NYC/Miami and are totally out of touch.

Stablecoins were sold as "the stability of a savings account with the returns of dogecoin".

>> There's a certain delight [1] in watching increased market volatility exposing how understanding merkle trees and consensus protocols doesn't make you an expert on what the financial system is, how it works and why it is the way it is.

> These comments don't seem very relevant to stablecoins such as this one, which are algorithmic rather than backed

Just... muah. Perfecto.

Berkeley is not a good counter-example.

There are usually several teaching professors doing a full time job behind the scenes -- handling a myriad of student crises, handling a huge quantity of special accommodations, plagiarism and other academic misconduct, behavior issues (on the part of both students and staff!!!), constant question bank maintenance, constant schedule tweaking, interfacing with faculty demands from down-stream courses, and so on. Those are all trivial, though. Most important -- by far -- is training and managing a large course staff most of whom have never taught a recitation or graded a homework assignment!

Scaling up from a class of 1 instructor and 40 students (at Olin 20 or 15 I'd guess?) in one class to class with 40 staff members and 1000+ students and several lecturers is its own skillset. Those instructors are not teachers. They are mid-level managers. It's a different job, and not one that most undergraduates are prepared to take on.

And the face that it's a machine matters. Teaching a few recitations or lab sections and grading homework is not even remotely the same as instructing a course.

It's a bit like saying that you don't need experienced management at a logistics company because, after all, everyone learns how to do the warehouse job within a week. True, but keeping that machine running requires institutional memory and is itself a full time job. And just because you can train cogs quickly doesn't mean many of those cogs would do a particularly good job at designing and operating the underlying machine. Or even a miniature version of that machine.

> but I think you might be underestimating how much better intentionally-designed support resources can make the process.

Having spent time both inside and outside the elite academic institutions, folks who use places like Olin or Berkeley as barometers for "normal" are wildly out of touch with 90+% of the 4,000 colleges and universities in the USA.

Students at places like Olin or Berkeley are already the cream of the cream of the crop. At Olin or Berkeley you have a handful of good student-educators every year. At normal places the acceptance rate is closer to Olin's reject rate, and the applicant pool is way lower quality. At normal places an above average Olin kid comes around once a decade or less, and the annual cream of the crop at Olin or Berkeley simply never pass through.

1. I've worked in gov labs, industry labs, and academic labs. Mostly industry labs. People and culture are the most important thing. The variability in innovation between companies is often WAY higher than the variability between the public and private sector. Gov labs can be insanely innovative or quagmires. Same for industry labs. It's all about the people and culture. Good people and good culture and possible in the public and private sectors. Bad people and bad culture are also possible in the public and private sectors. Anyone telling you otherwise is trolling and/or selling an idiology (sic).

2. The whole point of the above post was that there's ENORMOUS value in the "tried and true". Getting rid of endemic malaria has been possible for the better part of a century. It's a governance problem, not an innovation problem.

They don't have a PR budget, just trucks and sprayers. But they are absolutely the reason that there isn't endemic malaria in your county.

I guess it depends on what you mean by "high". At most institutions, faculty will make $50K-$60K starting, max out at $100K, and often do not have access to a pension. In many states, you're really better off, financially, as a high school teacher or police officer.

Which, I mean, high school teachers are highly paid by some standards. But saying professors command high salaries on a tech forum where even new grads are probably making more than the average full professor is probably misleading.

> but with proper resources and support students can also be very effective instructors... better than professor-taught classes

1. It really depends on the course; undergrad-lead core courses tend to be a disaster.

2. On that note, there's an important confounding factor: undergraduate-lead courses are often "topics" courses outside of the core curriculum, which naturally attract better feedback than "broccoli and spinach" courses regardless of the instructor. E.g., in CS, a course on game design or crypto will always attract higher ratings than "core" courses like Data Structures or especially Intro Programing.

3. Good faculty do a lot more than teach. And I don't even mean research. Industry relations and job placement are huge value adds of a good faculty member.

There's an important split between courses that need careful pedagogy and courses that really just need engagement. For an intro programming course serving all students, you really need a professional educator who is practiced at going through the slog of helping people understand for loops. Sometimes an undergrad will pass through who could totally teach the course, but that tends to be an exceptional student.

Once you have a bunch of juniors/seniors who know how to program, and assuming you're teaching a course that's primarily about applied programming (eg, not a proof-based CS Theory or Algo course), engagement becomes more important than pedagogy.

Student-lead courses can be great, and ARE often way better than prof-lead courses especially for "applied programming" type courses, but it's probably not feasible to run core major requirements with undergraduate instructors as a steady-state.