I deleted my account years ago after the 2012 hack, their security was and (probably still is) shit; couldn't even salt their passwords. https://en.wikipedia.org/wiki/...

I look at it from time to time, as much as I can see as a guest, and holy shit it's become just a big circle jerk, people posting self-congratulatory tripe and 'deep thoughts' [sic], thinking they are original and insightful, and so much of it looks like AI or people just stealing and pasting shit from elsewhere.

I'm sure some people still use it for finding jobs, I've only ever found mine from direct references/referrals from people I know and places I've worked. Even when I still had an account, it was annoying how many recruiters would contact me with listings that often had no relation at all to my experience and skills.

This kind of automation ultimately causes problems for 'regular' every day consumers and gets hijacked by a smaller group of assholes; plus the technology isn't mature enough to be trusted. So what happens when an agent runs amok, buys a too many of x, and the user says 'wait! I didn't want 100, I want to you to eat the cost of me returning it, and company y says, too fucking bad you bought it' -- who's liable? (my answer is the dumbass with the agent, but who knows how it will pan out)

Only a few years ago some of the kind of stuffs agents do (or at least have access to) we'd call a virus or malware, how things change.

Statistical contortions might provide copium, but don't prove anything. I gave you a straightforward parameter median household income. Something economists have been using for generations. You had to cherry-pick — and your cherry is rotten, because you complained about the period of COVID lock-downs, much of it presided over by your champion.

And you provided no citations. No wonder, your moderation is so high :)

Also Trump is wrecking the economy and nobody wants to acknowledge that

Because it just is not true. Median household incomes in the US are just steadily rising (inflation-adjusted) since he took office in 2024.

that presented themselves as "male" were paid more per task and perceived as more "human-like" than their "female" counterparts

Those complaining loudest are the ones, who can't define the term "woman".

Nova Learning surveyed 463 students in 2025 and 677 students in 2026.

So at a standard 95% confidence level, a sample size of n = 463 carries a margin of error of roughly of + or - 4.55%. A sample size of n = 677 narrows that margin to about + or - 3.77%. While some of the changes are outside of this range, many are not.

I also wonder who they asked " sample consists primarily of middle and high school students from the U.S. West Coast " So Bay Area, LA, Seattle? wealthy kids, middle class? private school, public?

I dunno, the numbers are interesting but I think a larger study with more distribution might be more helpful.

One model going down is happenstance, two — a coincidence, the third one — it's enemy action.

— James Bond

Apples and oranges, generated drama and clickbait. Move along..

A related phenomenon is, Holocaust survivors live(d) longer. There is no good explanation and repeating the experiment is, thankfully, quite impossible...

Simply the Forbes link was enough to confirm this point

Nope. One link is not enough — from the very beginning I asked, that each citation consist of two links: one to the prediction being made, the other — to confirmation/discussion of it coming true. Another rule was, the two links must be at least 5 years apart.

The purpose is easy to understand. A person can privately record 20 predictions of, say, an average temperature somewhere changing from -10 to +9 degrees. Five years later one of them will have made a precise match, and Forbes will write about him. If you didn't know about his 19 other predictions, you'll be impressed... This is why I insist on the prediction to have been published — prominently — ahead of time.

you purposely ignore the arguments

Because I was not asking for arguments — I was asking for citations...

The case against Big Tobacco was based on the fact, that their product was actually addictive. Nicotine is not just psychologically, but chemically addictive for humans.

There is no such case against software. Against marijuana-growers — maybe, but the same actors are surprisingly quiet about that.

Facebook has been pressured earlier into spreading government propaganda and then publicly testified about this pressure. Its current troubles are much more likely to be rooted in that, than in any actual "harm to children".

You're not paying me to be your research assistant.

Voila, asking your kind of science-deniers for scientific evidence usually ends this way.

So you have not read those IPCC documents yourself — while smugly accusing me of doing "anything at all to avoid looking at" same. Take your "L" at the exit, by your left, and don't let your tail get caught in the door.

I've noticed that climate deniers are highly allergic to reading actual science

But you are not, are you? So it should be quite easy for you to provide the citations of nature and in the shape I've asked for: a prediction, and it materializing. Two separate links at least 5 years apart... With the evidence being, supposedly, so abundant, why is it so hard for you to satisfy my request?

1967, the first greenhouse effect model using detailed CO2 infrared spectra and incorporating convection and radiation

Great, what did it predict, that was not trivial and actually impactful, but precise?

here's an article from Forbes that does the same comparison

You're now offering a different link — instead of answering the follow-up question about the earlier ones — does this mean, you concede, that the links you posted earlier are not satisfying the simple rules I started with, and wish to withdraw them? I don't want to be accused of "moving the goal posts"...

P.S. Calling me "an idiot" or "denier" is not going to work :-)

And I'll even help!

Please, sift through your massive documents yourself to cite a couple of "precise, non-trivial and impactful" predictions. I assume, you've read the documents you're offering as evidence yourself, so it wouldn't be much of a burden for you. Thank you!

They not only improved the model's forecasts; they also discovered why some of the model's predictions had been off

Wow, some had been off? Ok, nice to see an acknowledgement of that.

Now, how about a successful prediction? Something reasonably precise, non-trivial and impactful, please — falsifiable, yet not falsified in due time...

If you choose to play, be sure, each citation includes two links: one to the prediction being made, and another — to it coming true within at least 20% of the predicted value (for the quantifiable ones). Crucially, the two links must be at least 5 years apart...