Crémieux Profile picture
Feb 20 • 17 tweets • 6 min read • Read on X
The biggest news today should probably be about one of the Executive Orders from yesterday evening.

Trust me, it's big.

The President just authorized DOGE to start cutting regulationsđź§µ Image
This order starts off huge.

Remember those recently-created DOGE Team Leads going into every agency? They're going to work with agency heads and the OMB to review all of the regulations across a number of huge categories.

Which categories? Let's see.

Image
The first category is those rules and regulations which violate the law of the land: unlawful and unconstitutional regulations, things that agencies enacted but which they shouldn't have been able to. Image
Now you might ask: Who decides what's lawful or unlawful, constitutional or unconstitutional, a good or a bad interpretation of statutes, prohibitions, and the law writ large?

Try to keep up, because the administration outlined this a few days ago:
The next category of regulations that DOGE will be purging is sizable.

DOGE was tasked with purging the federal government of socially significant regulations that Congress didn't roll out, and regulations that are costly for private entities without benefitting the public more. Image
This next category of regulations is where things get huge.

DOGE will be purging all regulations that impede innovation and infrastructure, make it harder to response to natural and manmade disasters, and just generally anything unnecessarily standing in the way of business. Image
Now obviously this is a major task, but don't worry: the next section says which regulations to focus on first.

It says to focus on regulations that are particularly important. This is totally logical: get rid of the big barriers to growth first, and then move down the list. Image
The next section might be my favorite part of this whole Order.

This section calls for an end to bureaucratic overreach.

It says that if a bureaucrat is doing more than they're required to, they need to stop it. This means fewer bureaucrats abusing their 'authority'. Image
Additionally, if agencies are currently engaged in overreach in the enforcement of rules and regulations, they're going to stop.

This can also apply to rules and regulations that the President does not want enforced in a given way based on his valid interpretation of said rule. Image
And finally, the Order says what to do with new regulations:

Run them by DOGE, and if they're a barrier to business or a burden on the public, they won't go into effect.Image
Every new regulation will be reviewed and every existing regulation will be reviewed too, and all barriers to growth that can be extirpated from the Federal Register will be extirpated from it.

This authority is expansive and unprecedented, and the admin was building to this.
And just to be sure, there's still more to come.

DOGE is enabling the digitization of records, the installation of modern systems and tools that will enable the U.S. to be governed in a modern, rapid, and flexible way.

That's its purpose, is making a 21st-century government.
And why?

Well obviously because regulations are burdensome, the spending has been too high, and so on, but this Order contains another clue. Image
One of Trump's goals is ending the secret fourth branch of government that persists between Presidencies and ensures Democrats are always in power.

It is an explicit goal of this Administration to end the "Administrative State."
In their Fact Sheet on this Executive Order, the Presidency stated that it is their goal to end the extreme burdens on the American people from this unconstitutional fourth branch of government, and to stop them from prying into American lives forevermore. Image
It is hard to overstate how huge this Order is.

There are hundreds of thousands of federal regulations, and a very large portion of them can be stripped back with executive authority alone.

And now, DOGE has been enabled to start that process, with all that entails.
That entails a lot, but I'll cut myself off here. And keep in mind, this is just the first month of this administration.

Here's the Executive Order: whitehouse.gov/presidential-a…

Here's the Fact Sheet: whitehouse.gov/fact-sheets/20…

• • •

Missing some Tweet in this thread? You can try to force a refresh
 

Keep Current with Crémieux

Crémieux Profile picture

Stay in touch and get notified when new unrolls are available from this author!

Read all threads

This Thread may be Removed Anytime!

PDF

Twitter may remove this content at anytime! Save it as PDF for later use!

Try unrolling a thread yourself!

how to unroll video
  1. Follow @ThreadReaderApp to mention us!

  2. From a Twitter thread mention us with a keyword "unroll"
@threadreaderapp unroll

Practice here first or read more on our help page!

More from @cremieuxrecueil

Sep 15
I am extremely grateful for the publication of this result.

Why? Because it means this method has gone mainstream and replications can flourish by using it.

So, here's the first replication, all using the U.K. Biobank. This is for Black-White differences in IQ: Image
Notes!

0. The sample for the population result is *everyone* with ≥1/16 and ≤15/16 African admixture, the within-family result is for the siblings among them. I didn't plot between-families results, but they're pulled from the same distribution as the population result, so when I have those computed I'll replot, but they shouldn't be any different (will take a few hours, maybe be tomorrow, w/e).

1. Yes, datasets will be merged and sharper results will be obtained for the article on this that's coming out ~shortly. Can't be done for all phenotypes in the UKBB, but can be done for IQ at least. For example, we don't have lipoprotein(a) (lp(a)) measurements in some of the samples of young American kids, some of them don't have objective skin color measurements, etc. As a side note, this result holds up with brain size (not shown) in the UKBB, but I'm unsure if it holds up in the young samples that'll be merged with it, as they're still developing in most cases.

Anyway, the IQ p-value is p = 0.008 (two-tailed) within families and extremely low between them. The within-family result is robust, will get sharper with more data, and is also sharpened by using a latent variable instead of a score, and by correcting for measurement error (not needed with the LVM). Score shown for simplicity and ease of others with UKBB access replicating this. Also, accounting for error in the admixture computation, the p-value would drop a bit further, but not by very much since error is very small.

2. The "IQ per unit of admixture" is statistically indistinguishable between the population and within-family results, and yes, it explains most of the Black-White difference in IQ. I just wanted comparably-scaled results for all the traits here, so you're seeing r's. It's pleasant that the within-family variance reductions aren't enormous for siblings, which is what we expect even with quite high heritabilities given their genetic relatedness. It's the same result we've seen with American data, and it's also nice to see that in the case of this trait, the global admixture result *can* be interpreted like the within-family one. Presumably this only holds with measurement invariance, as we see in the U.K. when comparing Whites and Blacks there. Since we see this in the U.S. too, it's likely that the previous, already-published within-family null—which had a sizable effect in the correct direction which also could not be distinguished from the global r—was just a false-negative.

3. This result replicates with other degrees of relatedness, but we might lose the causal interpretation with those ones because the estimand for, say, a cousin test is different given the identity of the "C" variance component shifts for that comparison.

4. What is architectural sparsity and why is it relevant? Consider this table from nature.com/articles/s4159… (cc: @hsu_steve):

Basically, sparsity refers to the number of variants involved in a trait. It also refers to their effect size distribution. So, for Alzheimer's, for example, the trait is highly polygenic, but APOE explains more variance than the entire rest of the PGS, so while being under highly polygenic control, it remains moderately sparse.

If you're still not grokking what I mean here, consider some distributions of cumulative effects across the chromosomes. Here's the result for lp(a), which is already known to be influenced by essentially one gene. Guess which chromosome it's located on:

Consider, as a comparison, creatinine, which is considerably less sparse, and thus has effects distributed across all chromosomes:

Now, consider what this does to within-family admixture assessments. Skin color, for example, is controlled by only a handful of genes. This means that global admixture shouldn't tag it very much between siblings. The same is even more true for lp(a). And in fact, now we have confirmation of this!

But, we know from other methods that lp(a) is effectively entirely genetically-caused between populations. This is just accepted within the medical community because it is an obvious fact that follows from its strong control by a single gene. You can also figure this out using local ancestry estimates. Basically, the correlation between genome-wide ancestry and ancestry at a causal loci is what we want to get at, and if you know the causal loci, you gain power by restricting your analysis to that area. This is what we find with lp(a) (not shown, but use your brain. The obviousness of this fact is why the author used lp(a) as an example).

Also, in some sense, the frequency of that locus between ancestries gives you what you need without doing all this within-family stuff, if you're confident it's causal. The effect estimate might still be biased by population structure though, so that's worth keeping in mind.

There will be a post soon with more details and the expanded set of results with the additional datasets, robustness tests, and plenty of other fun things to look at.

TL;DR: this is a spoiler, and it shows that, yes, you can explain the Black-White IQ difference in Britain mostly genetically, and the global admixture result that I've posted here before is equivalent to the within-family one. Woohoo for things that should hold up, in fact, holding up!

As a sort of replication of the Young paper, you cannot explain the difference in educational attainment (as years of education) in this way. Why? Well, hard to say. Compensatory factors like I found with the GCSEs? (Haven't read that post yet? Go check it out here: cremieux.xyz/p/explaining-a…). Poor phenotype quality? Very plausible, because education really is a huge garbage heap, but why would that be in the general population and not within families? Maybe it has to do with what other traits admixture tags? Maybe it does replicate, but we just can't see it, because the precision is too poor (possibly the lp(a) story too). Who knows!

Q: Will the combination with more datasets allow us to fix this educational attainment result?

A: No, because most of the other datasets involve young people, not people who have almost all completed their educations, as in the UKBB. That plus the generational change and international incomparability in the definition of educational attainment makes it too poor as a phenotype. Sorry!

Any questions?

Link to a fun previous post from the same dataset, showing a result that *does* hold up within families: x.com/cremieuxrecuei…

Link to another post mentioning the forthcoming article earlier: x.com/cremieuxrecuei…Image
Image
Image
I want to ping an old post that I've also posted some replications for.

Basically, parents are inequality averse, and they try to compensate for when one sibling is less gifted than another, reducing the ancestry/PGS effect on education within families.

Read 13 tweets
Sep 14
Ever wondered why advertisements heavily feature Black actors when they're just 12-14% of the population?

I might have an explanation:

Black viewers have a strong preference for seeing other Blacks in media, whereas Whites have no racial preferences. Image
These results are derived from a meta-analysis of 57 pre-2000 and 112 post-2000 effect sizes for Blacks alongside 76 and 87 such effect sizes for Whites.

If you look at them, you'll notice that Whites' initial, slight preference declined and maybe reversed. Image
It's worth asking if this is explained by publication bias.

It's not!

Neither aggregately (as pictured), nor with results separated by race. Image
Read 8 tweets
Sep 14
You're on trial, and the jury can't make up their minds. The decision is a coin flip: 50/50, you either get it or you don't.

Your odds of a given verdict depend on the "peers" making up your jury.

If you're Black and they're Black, your odds are good; if you're White, pray. Image
Though White jurors have, on average, no racial bias, the same can't be said for Black jurors.

Where the White jury gives you approximately the coin flip you deserve, the Black jury's odds for a verdict are like a coin rigged to come up heads 62% of the time.
Once you get to sentencing, things get even worse.

The White jury is still giving you a coin flip on a lighter or a harsher sentence, but the Black jury is giving lenient sentences to Blacks about 70% of the time.

In short, Black jurors don't rule fairly.
Read 10 tweets
Sep 14
Posts saying Charlie said things he didn't, oftentimes even including videos where he doesn't say what the post says he does, have convinced me.

There will be no organic temperature-lowering coming from the left, because they don't want it.

They believe the things they claim.
They actually believe the people they dislike *are* racists, fascists, homophobes, transphobes, all of it.

They are not reasonable, and they cannot form anything like a reasoned argument for these perceptions.

Even still, it's really what they think.
Accordingly, they will not lower the temperature.

You can't expect people to stop using slurs like "fascist" or "racist" or "sexist"—even if they are completely untrue and it's impossible to provide valid evidence for them!—if they believe they're true.

They just won't.
Read 4 tweets
Sep 13
Your child's teacher says that people like you deserve to be killed for your beliefs.

They also laughed at the fact that when people like you are killed, their kids lose a parent, because again, 'people like you deserve it'.

You believe the teacher should be:
An airline pilot said that people like you should be killed for your beliefs.

You believe the pilot should be:
A surgeon said that people like you should be killed for your beliefs.

You believe the surgeon should be:
Read 12 tweets
Sep 13
A few days ago, I posted this image.

It shows that the gender wage gap is mostly about married men and their exceptional earnings.

In this thread, I'm going to explain why married men earn so much more than everyone elseđź§µImage
The question is:

Does marriage maketh man?

Or

Are all the good men married?

That is, does marriage lead men to earn more, or do men who earn more get married more often? Image
To answer this question, we have to work through the predictions of different theories.

For example, one of my favorite papers on the subject looked into three different hypotheses to explain the "marriage premium" to wages, and they laid out a few testable predictions:Image
Read 12 tweets

Did Thread Reader help you today?

Support us! We are indie developers!


This site is made by just two indie developers on a laptop doing marketing, support and development! Read more about the story.

Become a Premium Member ($3/month or $30/year) and get exclusive features!

Become Premium

Don't want to be a Premium member but still want to support us?

Make a small donation by buying us coffee ($5) or help with server cost ($10)

Donate via Paypal

Or Donate anonymously using crypto!

Ethereum

0xfe58350B80634f60Fa6Dc149a72b4DFbc17D341E copy

Bitcoin

3ATGMxNzCUFzxpMCHL5sWSt4DVtS8UqXpi copy

Thank you for your support!

Follow Us!

:(