Since smith charts are made by mapping the complex plane (grid) to another complex plane via a Mobius transformation Z->(Z-1)/(Z+1), maybe that’s what’s going on here too. The inverse certainly produces a grid again.
I feel like I see antinatalism and childfree movements in the news more frequently now. I suppose if they're any good at their job, the movement won’t exist in seventy years or so.
Baseline testosterone levels are actually even lower in most hunter gatherer populations. This suggests that your explanation is not necessarily correct.
Latin is actually very well attested, both in the classical and ecclesiastical pronunciation. There’s lots of languages, like Egyptian, where the phonology is pretty speculative, but Latin isn’t one of them.
In early August 2023, Professor Gino filed a lawsuit for defamation against Harvard University, and against Leif, Joe, and Uri personally, claiming 25 million dollars in damages. Defending oneself in court is time-consuming and expensive regardless of the merits of the lawsuit – as First Amendment lawyer Ken White put it to Vox , “The process is the punishment.” Targets of scientific criticism can thus use the legal system to silence their critics.
At present, Leif, Joe, and Uri do not have pro bono representation. The lawyers they’ve spoken to currently estimate that their defense could cost anywhere between $50,000 and $600,000 (depending on how far the lawsuit progresses). Their employers have so far only agreed to pay part of the legal fees. Defending science requires defending legitimate scientific criticism against legal bullying.
Edit: I initially wrote that they met their GoFundMe goal of $350,000, which is true. However, I’m not sure why they set their goal to only $350k when they mention that legal costs could skyrocket to $600,000 which they have not met
Great article. nice job. In the response letter Arielly says that he got the data from the insurance company (with which he collaborated on this experiment) and didn't suspect a thing. What is the level of responsibility which is expected from a researcher? What should be the consequences for the researcher on such cases?
Great article. The "Author Feedback" section at the bottom is interesting. All 4 that are there read exactly like you would hope: dedicated researches agreeing with the Datacolada analysis and expressing disappointment that they did not catch this error in time. One wonders where the truth is.
My favorite thing is that Gino is now suing DataColada [1], and basically is claiming that 'they were right in every other case and I supported them, but with me they are lying'.
This data was so shoddily faked that I have a hard time believing someone did this with an intention to deceive. Uniform distribution with a hard cutoff at 50K??
Pruitt had several influential spider biology papers out and when others failed to replicate and dug into the Supplementary Data, they also found lazy patterns.
>When Laskowski dug into data sets that Pruitt had provided for the study, she was shocked to find stretches of data that seemed to have been duplicated, to represent findings for multiple spiders. This questionable data helped to bolster a long-unproven theory that repeated social interactions in a group of spiders cause individuals to behave predictably.
So yeah, who knows how much scientific fraud there actually is; I haven't seen a case of fraud where the data was convincingly faked, which means that these cases are hard to detect or hard to prove.
If you fake and get away with it you’re already admitting to a type of laziness, so it expands y til finally you are faking it so lazily that you get caught.
Faking data realistically is almost as hard as getting it honestly. I know, I “expanded the data pool” for my eight grade science project.
Except the "it" in "getting it" is a significant or even bombastic and sexy finding. There's no reliable way to generate those, it's not just about hardness. The more correct and meticulous you are with your data, the more it will generally tell you that the bombastic claim is false. The more meticulous and effortful you are about faking, the likelier it will slip by.
Your suggestion only works in the simulated science, like school projects where you are retracing the footsteps of past successful scientists, to verify an already known result. There putting in more work will reveal that effect more and cleaner, because your teacher already knew how the thing works in the first place. This is totally unlike real science where we confront the frontier of the unknown.
That somehow loops around to becoming an interesting 8’th grade science project.
Do an easy experiment once correctly, then again with falsified data. Present the results side-by-side. Ask people if they can tell you which is which. Present have a bit on what sort of statistics could catch your faked data set.
Yeah, I did the simplistic thing of decide a question and an answer that sounded good; ran five or so tests, and then extrapolated additional sets based on that.
In my defense I would have run more tests had I started when I should have :)
Yeah that is fair, but it's mind bogglingly lazy/brazen. How much more effort is it have taken to just take an average of a few RAND calls to get a normal distribution instead of a uniform one? Did they not know the central limit theorem??
“Some things that aren’t worth doing are worth overdoing.”
I write about physics, language, and history, or whatever interests me at the moment, with an overarching theme of spending way too much effort analyzing useless topics. Here’s some of my favorites:
I love the book on so many levels. My copy is swollen and waterlogged, and held together with packing tape. I love it for all the Latin I relearned, but I love it even more for everything it indirectly teaches about teaching.
I’ve always treasured polished and well edited textbooks, but this thing makes the best textbooks feel like the work of amateurs. I always think of Neal Stephenson’s Young Lady’s Illustrated Primer when I’m reading it. It’s like parts of your brain being unzippered to discover understanding your didn’t know you already had.
I think of Lingua Latina in a surprising number of conversations… it reminds me to be considerate of how much new information can be absorbed, but also to fully trust my audience with that new information. I don’t need to belabor the presentation of ideas. I simply need to share my ideas in the context they matter, as if my audience already understood completely.
