diognesofsinope

> you quickly run out of blood to write in and start writing in "well that could've been worse if the starts had aligned, let's write a rule about it".

I'm also convinced this is a primary driver of "emergency/urgency culture".

Everything is hyped as an emergency to justify bureaucratic meetings/rule writing

There was an article on Bloomberg or WSJ that said the Director in the acquisition had a Teams chat where she said "sometimes you don't need to do due diligence at all" lol

> "we've implemented all best practices, contracted out the hard parts to world-renowned experts, and had third party audits to verify that - there was nothing more we could do, therefore it's not our fault"

The amount of (useless) processes/systems at banks I've seen in my career that boil down to this is incredible, e.g. hundreds of millions spent on call center tech for authentication that might do nothing, but the vendor is "industry-leading" and "best in-class".

> It's just that understanding this explains a lot of paradoxes of cybersecurity as a field. It all makes much more sense when you realize it's primarily about liability management, not about hat-wearing hackers fighting other hackers with differently colored hats.

Bingo. The same situation for most risk departments at banks or healthcare fraud and insurance companies.

I thought risk at a bank was going to be savvy quants, but it's literally lawyers/compliance/box-checking marketing themselves as more sophisticated than they are. Like the KYC review for products never actually follow up and check if the KYC process in the new products works. There's no analytics, tracking, etc. until audit/regulators come in an ask, "our best-in-class vendor handles this". All the systems are implemented incorrectly, but it doesn't matter because the system is built by a vendor and implemented by consultants, and they hold the liability (they don't, but it will take ~5 years in court to get to that point).

Beginning to understand what "bureaucracy" mechanically is.

Vegas and prediction markets consistently had Trump as the favorites.

Polling companies are in the business of media deals and government contracts. They will develop methodology and reporting to that end and the money is in "a close and contested race", even if it won't be.

This is what it feels like -- board is filled with academics concerned about AI security.

Almost more of a "takeover" by the board after it's successful lol

If any level of government funds your institution you should have to releases the data.

The code I write is not my code, it's the banks.

The article is leaving out the fact that the $10k threshold is not at the discretion of the bank. It comes directly from the Bank Secrecy Act (https://en.wikipedia.org/wiki/Bank_Secrecy_Act).

The magic number is not the bank's magic number, it's politician's magic number.

It's much more of a financial intelligence collection operation.

The intelligence community has access to information about every transaction with greater than $10k (lower thresholds for monetary instruments) with at least one party of the transaction identified for over 25 years.

People also miss the fact that FIU operations also often include 314(a)/(b) letters (subpoenas for financial information on specific individuals) alongside their AML operations. Same for OFAC Sanctions monitoring (obvious example is Russian customers and assets).

I think the answer is simpler: people care about their careers and their family first. Think, "If the data says something that gets in the way of my career well I don't care about the data."

Had the same problem when I was an economics researcher -- publication bias for what stakeholders want to hear (often the government) is rampant because that's where funding for the economics department mostly comes from.

I mean, the failure of a lot of experiments to replicate is extraordinarily well documented...

Not to mention the corollaries from the Wikipedia article (https://en.wikipedia.org/wiki/Why_Most_Published_Research_Fi...):

"In addition to the main result, Ioannidis lists six corollaries for factors that can influence the reliability of published research.

Research findings in a scientific field are less likely to be true,

1. the smaller the studies conducted.

2. the smaller the effect sizes.

3. the greater the number and the lesser the selection of tested relationships.

4. the greater the flexibility in designs, definitions, outcomes, and analytical modes.

5. the greater the financial and other interests and prejudices.

6. the hotter the scientific field (with more scientific teams involved)."

These are all reasonable criticisms from my own area of expertise: applied econometrics.

The primary problems arise from (1) mass education and (2) cheating.

Project-based learning can't be managed with 40:1 student teacher ratios. The best learning has always come from projects and apprenticeship/mentorship style systems, but even managing that with 3 classes with a 10:1 student teacher ratio becomes hard. This should make sense, almost all the economic evidence is that parent characteristics are hands down the largest factors in what a kid's future income will be (mentorship).

Cheating is rampant which is why take-home exams rarely exist.

The reality is the world would be far better off with 3 times as many teacher, but you can't keep teachers wages as high as they are with 3 times the supply.

The field of study of occupation licensing: https://en.wikipedia.org/wiki/Occupational_licensing

It's absurd to think someone needs to take a $1k 'Philosophy of Mathematics' class to teach 10th grade geometry.

> In South Dakota and a number of states in the south and rural districts, yes it is another story, and it is bad.

I suspect this is because teaching is arguably the most stable job in rural areas.

Half the reason to be a teacher is because half the job is having fun. Most curricula is set in stone and requirements are nationally standardized (US and Asia). You more or less get summers off (there are conferences and summer school) and there are almost no jobs where you can take ~1.5 months off every year. Teaching is also one of the few steady jobs in rural America.

I feel like most people haven't been in an actual ~5th grade classroom in a long time -- literally half of it is playing games/trying to have fun.

And Youtube, good god has the educational content on Youtube evolved in the last decade.

I don't have a BS in Education (BA in Philosophy), which means you have to go through their M. Ed. program with licensure. You must take Educational Theory/Pedagogy core courses along with required courses in your field -- I had saved money and already taken the calc sequence, linear algebra and differential equations.

Grad school at the UMN is ~$10k a semester (https://onestop.umn.edu/finances/costs/tuition). Would have been ~30 years old, $40k in debt as a beginning teacher in MN. Amazingly, none of that includes actual experience teaching lol.

The teachers union has been waging a war against future teachers to benefit current teachers for 30 years and this is what that looks like after 30 years.

Similar to housing and zoning, education is a government racket.

> 1. For as much as we spend on education, teachers seem to be grossly underpaid - to be getting robbed of their share of the budget. Where does that money go?

Counterpoint: teachers' pay is great, it's just backloaded in pension plans.

> 2. It seems that education degrees are seen as easier to achieve than others.

Yeah, but cost is the same and cost is what's important.

> 4. Many school problems are caused by disruptive children.

Bingo. Half the success of 4-year colleges is that it's the first time the bottom 50% of the students are filtered out.

Story time. I was an ESL teacher for 5 years in Asia and planned on coming home to the USA and getting my teacher's license in Math to teach at international schools. I am not currently a teacher, I'm a quant at a big bank.

Why didn't I end up in teaching? The licensing requirements in Minnesota are insane. Counselor's straight up told me I'd have to borrow ~$50k from the UMN for a MS in Curriculum and Instruction before I could teach.

The labor unions along with politicians have built a structure in which there is artificial scarcity of teachers. Not only is the profession filled with disrespect, but it's outrageously expensive and bureaucratic.

Lastly, the Economics of Education field is wild. Clearly there's value to basic reading/math/science education, but it's not clear at all whether teachers are schools matter than much (wealthy communities/parents matter a lot).

Edit: feel obligated to add that k12 education is financed and administrated at the local level, which means our experiences with this likely vary a lot. Mine are specific to trying to move back to the USA and become licensed in MN.

Federal government literally spends over $1T on healthcare for the elderly.

The healthcare issues in the country have never been about the old.

> The other irony is that likely she does it for exactly the same reasons as why science media is often bad: economics.

Can we all stop blaming 'economics'. Economics says people are largely self-interested, selfish and maximize their own utility (happiness-whatever).

It's not 'economics', it's people. Labor unions are also maximizing their revenue.

For the record, the evidence of 'widespread' fraud is extremely weak:

See Antoinette Schoar's (MIT) work: https://www.nber.org/papers/w20848

It makes for a good news story that regular Americans understand and frankly want to hear (the banks were bad). But if you really dig into the reports, e.g. Financial Crisis Inquiry Report, almost the only fraud comes from misreporting of income which is essentially consumers lying. There could be other documentation issues, but underwriting almost entirely depends on credit score + income, so they're fairly trivial.

> we printed money and it helped.

I mean, did it? What evidence do you have for this claim?

Vaccines absolutely helped. But now everyone's wages are going down -- it was basically ~$3k stimulus checks that were actually loans with a 400% interest rate.

Real workers wages are falling. Inflation fundamentally increases inequality, i.e. people who own assets watch the value of those assets increase while people who work for income watch their income fall.

They are signaling. Push came to shove and the unfortunate reality is that Ukraine isn't that important to most countries and the risk of a greater war is worse.

The lesson here is that every country should learn to defend itself.

American Medical Association (and other medical/pharma/health workers associations) > IBM

> Researchers are incentivized to write papers that seem impressive (and intimidating) rather than clear and intuitive.

Ah, a fellow economist lol. Lack of clarity is a strategic advantage because (1) (as you said) it looks impressive and (2) it's hard to validate that it's correct.

So many papers contain such elementary statistics mistakes such as survivorship bias, e.g. 'returns to education' is almost exclusively measured by asking individuals who graduated (on average 50% of enrolled students don't) and respond back to surveys (good chance of bias).

Pubs are how you get jobs. It's not about science anymore, it's about navigating bureaucracy for an elite job.

Bingo -- they struggle through their 20s until they realize they need to pick a practical career in their early 30s.

I come from the econometrics end of things and Paul Romer (Nobel Prize winner) put it well:

'A fact beats theory every time...And I think economists have focused on theory because it's easier than collecting data.'

When I read this article this is exactly what I thought of -- modeling/researchers always focus on the low hanging fruit which is sitting in their comfy chair in their ~200 year old university developing hyper-complicated models rather than going out and collecting data that would answer their questions.

> strong temporal emotions

Well said. As Jim Jefferies said in his gun control bit referencing suicide -- 'We all have bad days.'

I get why it's used, but I strongly believe people are better off seeing the raw data. Exactly as you said, we can probably infer if there is variation in testing (weekends).

Or at the very least show the 7-period SD so we can see if the confidence intervals overlap.

You can absolutely use averages to hide data points and data quality.

PS: I disagree with your PS -- if we're being wildly theoretical and impractical about this we should just create a second Earth where everyone wears mask and a third Earth where no-one wears masks and compare all the Earths....

And none of what you're saying addresses the core problem I mentioned, which is that the divergence in the series starts before the policy date.

If your point is that looking at counties and assigning mask_mandate = 1 vs mask_mandate = 0 isn't rigorous, agreed.

If you look at the series the different in case rates started before the mandate, making me think it's more about behavior differences in cities vs rural areas than the mandate (makes sense).

Same thought -- makes you think it has less do you with masks/mandates and more with city-folk being cautious as delta surges. Maybe the mandates encourage this behavior shift?

Top points if politicians noticed this difference off the bat and create the mask mandate to engineer the illusion that it was their policy that worked, even though it would've happened anyways -- aka action bias.

In any case, I think we can all agree people need to stop (1) using different random X-day moving averages and (2) give us the data.

edit: there's an entire literature on methodologies (1) Regression Discontinuity Design (RDD) and (2) Difference-in-Difference (DiD) that's designed to address this problem in analysis.