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Culture War Roundup for the week of August 4, 2025

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"Trump fires Bureau of Labor Statistics chief without evidence for political reasons" says the news radio I wake up to, then continues to say he removed the Democrat appointee "without concrete evidence." Since COVID-19 caused lockdowns, the BLS numbers have been revised downward from initial reports regularly, sometimes ridiculously so, which Axios says has justifiable reasons.

So why are the initial numbers even reported if we know the algorithm they use will be wildly inaccurate?

The whole "without evidence" tic is pretty played out at this point. Of course, Trump does have evidence -- the revisions are higher than usual. It's pretty bad evidence (so "without concrete evidence" is true), but it's enough to make "without evidence" naked editorializing.

BLS has been putting out these numbers monthly for many years; I am sure if they proposed delaying the releases two months there would be all sorts of complaints about that too.

Trumps own former BLS chief himself doesn’t like it. And it includes this very damning quote:

“There’s no way for that to happen,” Beach told CNN’s Kasie Hunt on “State of the Union.” “The commissioner doesn’t do anything to collect the numbers. The commissioner doesn’t see the numbers for until Wednesday before they’re published. By the time the commissioner sees the numbers, they’re all prepared.”

Other articles note that usually, initial estimates are based on larger employers, and smaller ones take longer to report. Savvy consumers of the stats know this. Also, what size company has been hit hardest by recent market uncertainties including tariffs? Small employers. The variance is higher.

If a number feels off is your evidence, and it’s plausible or even likely that the explanation could be explained by either malice OR the underlying stats actually being off, it’s still “no evidence” in a statistical sense. We need DETAILS to be able to assess the claim, and Trump provided none, and furthermore if his own former guy says that the chief doesn’t even see the numbers until they are nearly fully assembled, we have strong reason to be skeptical and zero actual reason to trust him (beyond a baseline level of trust in Trump himself).

Trumps own former BLS chief himself doesn’t like it

So? That doesn't mean it's "without evidence".

And that quote isn't damning at all. The fact that the commissioner doesn't collect the numbers herself does not mean she is not responsible for doing so.

I'm 99% sure Trump's wrong and she wasn't cooking the numbers, and it's likely she wasn't doing a bad job.

BLS commissioner 2013-2017, an Obama-era one but still obviously a person in the know:

FADEL: As a former commissioner, is it possible to just make the numbers up?

GROSHEN: No. The commissioner does not see any numbers before they're final. So they are already baked in the cake. The commissioner sees them before they're released and mostly approves the narrative that accompanies the table with the numbers. But the commissioner has no role in estimating the numbers in those tables. The commissioner doesn't have access to any of the systems and the data that go into the numbers. So a lot of people would know if the commissioner were fussing with the data, and the culture of the BLS is such that you'd immediately get pushback, resignations, whistleblowers, something like that.

FADEL: So it sounds like it would be nearly impossible without, as you pointed out, many people knowing to just phony up the data.

GROSHEN: Absolutely. That's intentional. That's not an accident. And when the BLS changes its methodology in any way, it publishes papers about it, it explains why it did it. All of that is very transparent.

I think that elucidates the point a little bit more, especially the bit about how methodology changes are obvious and up-front. The operation in professional statistics orgs like this is pretty plug-and-play on the collection side and there's a lot of cross-checking that happens. Plus, anecdotally, the BLS has one of the better reputations in the stats community and worldwide.

What I mean by evidence is like, if not actual whisteblowers or a smoking gun email or edited Excel file, at least some kind of specific alleged mechanism: did she pressure data collectors to poll only certain forms? Was the sample size abnormally low? Did they go on some kind of fishing expedition? Were internal policies not followed? Something like that.