I think GP is pointing out a legitimate asymmetry between the "two sides": there's one* way for a conservative to do things the way they've always been done, and there's an infinite* number of ways for a progressive to change things to do something different, for better or for worse. The Paradox of Choice affects one side much, much more than the other.
> he's saying that discussing it is taboo, and increasingly so.
It's not though. There's no evidence of that.
In fact, the very claim "no one wants to impinge involuntarily single-parenthood households" is itself an ironic admission that the difficulties of single-parent households are obvious to everyone.
It's not "8-wide", it's "512-bits wide". The basic "foundation" profile supports splitting up those bits into 8 qword, 16 dword, etc. while other profiles support finer granularity up to 64 bytes. Plus you get more registers, new instructions, and so on.
Not OP but for me it's not about what sources to trust (blindly? literally none of them), but what type of information you can trust. Naked facts seem to be safe for the time being, context should be assumed to be heavily biased in a particular direction, and opinions are worse than worthless.
Unfortunately I've found journalists and/or their sources often lie about basic facts too, even when those facts are easily checked.
You'd think they wouldn't do this. Probably they do it because they know most people will take factual claims at face value, or the journalists are so sloppy/confused that they themselves don't realize the claims are wrong.
Slight tangent: does anybody know how these models are tuned to censor certain topics so precisely? I thought it was a bit of a black box how things worked internally?
I was thinking about this last week[1] and I think that both the "math" people and "common sense" people are correct in a sense, and talking past each other. The math people are of course mathematically correct within the limits of the constructed model, given all the assumptions of perfectly random sampling, no systemic error, etc. Meanwhile common sense people are correct in a practical sense: small samples are vulnerable to sampling error, p-hacking, outright fraud, etc. Even before you're aware of the exact mechanisms by which things can go wrong you intuitively know that small/cheap studies are more vulnerable to some kind of honest human error or dishonest... shenanigans.
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[1] I was listening to a podcast where trolley problems were brought up and the speaker was lamenting how clearly "unethical" and "irrational" your evolved intuition is given that most people will let the train hit 10 men working on the tracks than to divert it and kill 1 innocent. Trolley problems are intellectually interesting for various reasons but jumping to that conclusion is clearly absurd. Your intuitions are shaped by millions of years of genetic and social evolution to precisely be most rational for actual real-life problems. If you were actually standing at that switch you'd be thinking...
* do I actually trust my eyes in this situation? Are the workers on a parallel track and there's no actual problem here?
* if I pull the switch, will it derail the train and kill N+1 people instead of the 10.
* will the workers just notice the train in time and scurry off the track? Or will the train just stop? How good are brakes on a train anyway?
* how much time do judges and juries spend solving trolley problems?
... and while you were paralyzed thinking about these and a million other things, whatever was about to happen would happen and there would be no trolley problem.
I think the points he makes in the article actually perfectly match the "broscience" in powerlifting and olympic weightlifting. There it's all about long rest between sets, low reps, tracking weekly pounds lifted, hitting the same muscles many times per week, etc. I was nodding along at everything thinking "this is obvious isn't it" and had to remind myself he's writing about a different field.
