There are roughly a million violent crimes a year. It is not credible there are 3x as many defensive uses of firearms that are somehow being missed.
The page you reference indexes a few thousand over several years. Seems likely an undercount as the page claims but not by that much by probably a couple orders of magnitude.
A good example of this is comments on this post. They're basically awful and reduce worthwhile traffic on this site by driving away more people than they attract.
The reality of every forum, as the original author says, is that unless you censor topics that attract cranks, you'll eventually become a qanon platform (or the equivalent) and drive out all worthwhile participants.
I'm not sure what the global rule is called, but something like volume nonlinearity or kookiness asymmetry it something. If you have a bunch of looks everyone else leaves. You're options are to get rid of them or fail. It sucks but there it is.
Ultimately wouldn't these rates be set politically? As in, there'd be one politician who says "raise the tax and do this" and another who says "lower the tax and stop doing that" and voters just pick what they want to happen.
Another key factor is enforcement cost. Enforcing a land tax is really easy for a government. You just... Go there and get it. There's no moving the land offshore or having complex relationships or offsets. If someone won't pay the government just assigns the ownership to someone who will and goes on.
Compliance costs with many other taxes are quite high.
That's kind of the thing that makes APIs possible, right? It sounds to me like "what if programming were done in a completely flat global namespace in which abstractions, encapsulation, and structure were impossible."
Some friends and I were hooked on this game in college. We eventually wrote a program to solve particularly tough hands. It turns out there are a few potential hands that are actually impossible to solve, but not very many! It's a fun programming problem. :-)
From the discussion on this I've read, I think a good direction would be to consider statistical tests like this as simply not "publishable" at all the way we currently think of it.
That is, if you have a theory about how a Gene relates to height on tomatoes, and you do a test, that test would show you you're likely on the wrong track if it falls below some p value, but the only thing it tells you by being above is that "there may be something here."
I think this is true for many fields with a replication crisis. The problem isn't statistical, the problem is no theory. If you have a functional theory there's all kinds of things you do to gain confidence in it, and mostly those will contribute to the ability to predict statistical results, but that is completely different on kind than sending out a survey and noting that question 2 and 6 are statistically correlated.
When a field thinks that the kind of early suggestive work like this is worth talking about, they should probably just talk about it in conferences and similar venues, rather than "publish" it where journalists will pick it up in a "science shows" story that 95% (lol) of the time turns out to be wrong.
In other words, I think it is fine that fields talk about early non-theory results -- that can be interesting for specialists to advance faster. "Publishing" this mostly-going-to-be-wrong stuff is leading to confusion among the public about what the scientific process demands and how trustworthy it is. That is not a good outcome in my opinion.
Are you suggesting the Chinese market is more competitive due to the government being big enough that companies in the market have to exist in an impartial regime? This isn't the impression I get from many other sources.
A local coin/stamp person was completely uninterested in my old stamps from like 35 years ago. I think the shrinking number of collectors is outstripping the number of collections getting thrown out, and the whole idea of collecting stamps is just fading away.
By "open standards people" I mean "people who prefer open standards". Nothing more sinister than that. :-) (I am one, BTW)
This is already a very small subset of the population -- they've bothered to take a stand on something virtually no-one seems to care about. (At least not directly.)
This last part seems crucial to me. You're right that people care that they can chat with friends. It's the clause I think they glaze over at. Something about applications? I just want to chat!! Of course standards folks, being experts in this, care a lot, but messaging is a canonical example of this. I've personally witnessed years of strategy aimed at open standards go nowhere while proprietary standards win out. It's not because billions of people have strong preferences for open standards!
I do think that there are enough open standards fans, and enough open standards-adjacent folks, to make a strong play for something like messaging. But it's not "abstract XMPP" that's the problem -- it's "real XMPP" with fractures, federation headaches, delays in having it be caught up with capabilities of closed platforms, etc. That's the actual competitor. :-(
I have some direct experience with this. It is summed up as "open standards people are extraordinarily hard to work with, uncompromising, and subject to infinite fine splitting of the space. Meanwhile, 5 billion users do not care and want things to be easy, fast, work well, and be well integrated."
The result of these two forces is that it ends up being extremely difficult to work on open standards for any kind of data that people care about. (Users can't see HTTP, so it is fine to standardize. They can see blog titles, so... no dice.)
The authors' point seems to be "if you ask people questions whose real answers correspond to informal statistical judgments, then they will give the right answers."
This isn't really that informative, but the strongest form of this argument is "informal statistics is better in a lot of real-world cases." This sounds to me quite a bit like the case the behavioral economists make -- that these intuitions aren't crazy, or stupid, but they do exist. They were constructing tests specifically to isolate them, and succeeded.
A further point is that these kinds of situations when intuitions are challenged happen regularly. I don't know what behavioral economics says specifically about causes, but it seems to me they take a fairly neutral view: such situations can occur by chance, due to hostile intent, or by mistake. Whether the outcome is positive or negative depends as well. The point of "nudge policy" (opposition to which seems to be the main point of the article) is to see about making these situations positive -- that is, arranging the world through policy such that making intuitive considerations actually yields positive outcomes. I don't think the authors' argue successfully for the point that since everyone is rationale and no-one ever gambles when presented with the opportunity, that therefore arranging policy such that intuitive choices yield positive outcomes is unwarranted interference.
The point of the article is that your intuition is incorrect. By inhibiting zipper merging you are forcing congestion backward, and leaving carrying capacity of the road unutilized during congestion when it is most at a premium.
Pushing congestion backwards is exactly the cause of a lit of traffic jams. I've observed this myself every single GD day on the 210W freeway between Hill exit and the 134 exchange. People get over way early, causing huge congestion to the merge entrances. If they'd stay left and zipper, everyone in the jam would save about 5-10 minutes. This is thousands and thousands of dollars a day of cost in completely avoidable congestion in just one two mile stretch of highway ( albeit it a particularly egregious one)
Did anyone else find the variance illustration completely baffling? It's got little to do with an intuitive feel for the variation in outcome for a random variable
The history is that 'fake news" was used to refer to fabricated stories. Following it's surge in.popularity following the 2016 election, Trump realized the term was catchy and claimed falsely to have invented it, but used it instead to refer to "news Trump doesn't like" of various sorts, thus making it a contentious term.
google.com/search?q=human+echolocation brings up a ton of related stuff.
The thing is "what do you type into the search engine." I, for one, would never think to type in any of probably tens of thousands of topics that, having seen, I think are awesome.
I read over a couple of the papers. The descriptions of them by the authors did not match the content of the papers.
For instance, the one they call "Hooters" is described as "A gender scholar goes to Hooters to try to figure out why it exists." The actual paper is written as a record of transcripts of visits to a restaurant and an extraction of particular conversation themes. At no point did I see the paper questioning why Hooters exists -- the (apparently totally faked) data seems pretty stereotypically motivated, which I think may be their point, but I'm not sure short of a fraud investigation how reviewers are supposed to know that the particular group this author claims to have visited Hooters with didn't say the things supposedly directly recorded. That's a really dramatic claim for a reviewer to make: "This conversation which the author claims is a direct transcription from a recording couldn't possibly have happened because it seems too stereotypical."
Yes, the methodology isn't that great, and the paper was rejected.
More generally, the "study" isn't selecting random journals to see if they could defraud -- it is instead aimed at specific academic targets and a "test to failure" scattershot mechanism is used. Thus we have no idea whether these journals are any more discriminating than, say, PLOS or Nature.
Ultimately, I had some sympathy for the Sokal experiment in that it seemed to say something about the interaction of literary theory and physics. I don't get the same sense that there's much here other than "confirmation bias exists, even among gender studies folks!!!" which seems like it wouldn't take 3 people 10 months to figure out, and could be done in a much more direct way, and honestly isn't that shocking or rattling a conclusion.
The page you reference indexes a few thousand over several years. Seems likely an undercount as the page claims but not by that much by probably a couple orders of magnitude.