Crémieux Profile picture
Sep 23, 2024 7 tweets 3 min read Read on X
The FBI has finally released crime statistics for 2023!

Let's have a short thread.

First thing up is recent violent crime trends: Image
Now let's focus in on homicides.

The homicide statistics split by race show the same distribution they have for years. Image
As with every crime, it's still men doing the killing, but it's also largely men doing the dying. Image
What about Hispanics? Their data is still a mess, but here it is if you're interested. Image
The age-crime curve last year looked pretty typical. How about this year?

Same as always. Victims and offenders still have highly similar, relatively young ages. Image
Everything else, from locations to motives to weapons is pretty similar to previous years. What's different is that the OP might show incorrect numbers.

For the past two years, the FBI has silently updated their numbers after about two weeks.

You can use the web archive to see that the data from the OP is the data shown at release last year, and the data from 2023 is the 2022 data with the FBI's suggested reductions (i.e., -11.6% homicides, -2.8% aggravated assaults, -0.3% robberies, etc.).

But you can see on their site now that they've adjusted the numbers up, so the reduction they suggested has brought us down to a figure that's less impressive than my chart shows. The difference isn't huge so I showed the OP without updating to their new data.

For reference, 2022 as reported then had a homicide rate of 6.3/100k, and they silently updated that to 7.48/100k. The 2023 data they provided today actually has a murder rate of 6.61/100k, higher than last year's initially-reported number, but lower than the updated number. To make matters worse, if you use their Expanded Homicides Report, you get a rate of 5.94 for 2022 and 5.24 for 2023.

Methodology matters and we get to see inconsistency in this year's data, not even data that's been updated or anything. It's a mess, so take everything with a grain of salt and, in the interest of caution, only interpret trends. Trends are mostly common between all data sources even if the absolute magnitudes are off, constantly updated, etc.

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More from @cremieuxrecueil

Dec 22
The Australian pension system is funded through mandatory contributions into private retirement accounts

During the COVID pandemic, the government allowed people to pull up to $20,000 from those accounts decades early

What happened?

Firstly, uneducated people pulled the most: Image
Australia did this because they needed fiscal stimulus.

If they didn't allow people to make early withdrawals from their accounts—which normally remain inaccessible until retirement age—, they would have ended up in a very bad position.

But people did withdraw. Image
About a quarter of those aged >34 withdrew.

The most common amount to take out was $10,000 each time the possibility became available.

All said and done, that typically meant pulling down 51% of the total balance. That also meant foregoing $120,000 on average by retirement! Image
Read 10 tweets
Dec 21
The biggest argument against using GLP-1s for weight loss is that they cause excess muscle loss.

But as it turns out... GLP-1s do not cause any more muscle loss than traditional weight loss methods!

Let's discuss🧵Image
The differences in weight loss in that chart showing data from different trials are not

1. Clinically significant—they're not large enough to matter physiologically

2. Statistically significant—each weight loss method is not distinguishable in current data

But that's lean mass
Lean mass includes water.

Unfortunately, if we use DXA scans to understand body composition, we include that with muscle.

But if we use MRIs, we can separate water and muscle! As it turns out, the UK Biobank has just the required data. Image
Read 13 tweets
Dec 7
Why do identical twins have such similar personalities?

Is it because they're reared together? Is it because people treat them alike due to their visual similarity?

Nope! Neither theory holds water. Image
Despite looking as similar as identical twins and being reared apart, look-alikes are not similar like identical twins are. In fact, they're no more similar than unrelated people.

This makes sense: they're only minimally more genetically similar than regular unrelated people.
The other thing is that twins reared apart and together have similarly similar personalities.

In fact, there might be a negative environmental effect going on, where twins reared together try to distinguish their personalities more!
Read 7 tweets
Dec 2
Society is cognitively stratified:

Smart people tend to earn higher educations and higher incomes, and to work in more prestigious occupations.

This holds for people from excellent family backgrounds (Utopian Sample) and comparing siblings from the same families! Image
This is true, meaningful, and the causal relationship runs strongly from IQ to SES, with little independent influence of SES. Just look at how similar the overall result and the within-family results are!

But also look at fertility in this table: quite the reverse! Image
Source: sciencedirect.com/science/articl…

And to learn more about this general phenomenon, see: cremieux.xyz/p/intelligence… (I've added this citation to this article!)
Read 5 tweets
Nov 25
After this article came out, several people responded, alleging that a cultural model made more sense.

Clark has a point-by-point response🧵

Let's start with the first thing: parent-child and sibling correlations in status measures are identical—hard to explain culturally! Image
The reason this is hard to explain has to do with the fact that kids objectively have more similar environments to one another than to their parents.

In fact, for a cultural theory to recapitulate regression to the mean across generations, these things would need to differ! Image
Another fact that speaks against a cultural explanation is that the length of contact between fathers and sons doesn't matter for how correlated they are in status.

We can see this by leveraging the ages parents die at relative to said sons. Image
Read 10 tweets
Nov 24
The idea:

The internet gives everyone access to unlimited information, learning tools, and the new digital economy, so One Laptop Per Child should have major benefits.

The reality:

Another study just failed to find effects on academic performance. Image
This is one of those findings that's so much more damning than it at first appears.

The reason being, laptop access genuinely provides people with more information than was available to any kid at any previous generation in history.

If access was the issue, this resolves it. Image
And yet, nothing happens

This implementation of the program was more limited than other ones that we've already seen evaluations for though. The laptops were not Windows-based and didn't have internet, so no games, but non-infinite info too

Still huge access improvement though
Read 4 tweets

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