I’m looking for good resources to learn math that use visuals and give the intuitions behind the math. 3B1B is exactly the kind of thing I’m looking for. I’m interested in learning a bunch of areas but I’m currently most interested in cryptography.
Why do business leaders consistently refer to their highly educated workforce as "talent"?
This talk of "attracting talent" and "retaining talent" is everywhere I look. (I first thought it was an artefact of tech/Silicon Valley culture, but I hear it in interviews with CEOs in other areas of business too.)
My impression is that they are often very happy to hire someone who learned their skills through extensive experience, rather than being born with them.
I think it's a convenient shorthand for "people with the skills we need", and I admit I don't know a great alternative shorthand. But I don't think this one is great either, as I believe it sends a very exclusionary message.
Is my impression right? If so why did we pick "talent"? And what could we say instead?
I am reaching out for help as I am struggling with anxiety and mental illness relating to an Information Hazard / AI thought experiment. I am currently being treated by a psychiatrist but I feel like I need to talk to someone who understands simulation hypothesis arguments and related issues.
Can anyone recommend a good offline variant of github? That is, my company has a git repository that lives on an offline network, and primarily I want the better UI experience that github provides relative to the CLI. I think this + lots of other bells and whistles can be had via Enterprise Github for $21/person/month; I'm wondering if there are cheaper alternatives (with fewer bells and whistles) out there.
GitLab is the big one, however if you are just looking for a code browser and not issues, pull requests, CI, etc. then something like cgit: https://git.zx2c4.com/cgit/about/
Thanks! I didn't know about GitLab, it might be the right answer for us. The main thing I really want is a good UI for pull requests. I don't need integrated issue tracking (I can't get it anyway, since the repository is offline, whereas our issue tracking is online so that other people can access it), I could see us getting some use out of CI but living without it doesn't bother me too much, but having review comments consist of plaintext emails saying "on line 137 of file foobar.cs you do this thing, why do you do it" (instead of having that comment hang out next to line 137 of foobar.cs) is really annoying. For some reason, this doesn't seem to be a common feature set, and I'm puzzled by why that is.
I've recently saw this TED Talk (uh oh, red flag!) https://www.youtube.com/watch?v=PrJAX-iQ-O4 ("Emily Nagoski and Amelia Nagoski: The cure for burnout (hint: it isn't self-care) | TED")
And I'm curious what do people think about this "stress is a tunnel, it's only a problem if you get stuck in it"?
A criticism of space shows like Star Trek is that, even if an alien planet's atmosphere were chemically identical to Earth's, it still wouldn't be safe to breathe since it would contain microorganisms and toxic particles. Humans who visited would need to wear space suits, which they never do in most space shows.
If you used a time machine to visit the Mesozoic era, would there also be a risk of you breathing in microorganisms or biotoxins that would kill you? Do we have evidence for or against this?
You'd probably want to wear an environment suit (but not a full pressure suit) the first time you visited a completely alien world with a biosphere. Or at least a good filter mask. But the audience wants to see the actors' faces, so we make that concession to reality.
Reality is, the human immune system is really, really good, and even microorganisms that have specifically adapted to our fellow mammals usually can't make a foothold in a human body until they've spent many years evolving in close proximity to humans. An alien microorganism that has the wrong chirality or needs an amino acid humans don't have or whatever, is going to just starve in a human body and probably face an insurmountable evolutionary hump trying to do otherwise.
So the protective gear the first explorers wear is *probably* unnecessary, but nobody who is serious about space travel takes even 1% risks if they don't have to.
Very few bacteria even on the Earth are well-adapted to infecting a given species, such as humans. As a rule, nonspecific immunity and the lack of the organism's usual environmental niche mean most random micro-organisms that end up inside us die or are killed almost immediately. It's only a relative handful of species, which have evolved in close parallel to us, which have developed the necessary mechanisms to survive for any length of time*. So a priori alien micro-organisms are very unlikely to be infectious, let alone dangerous.
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* The most successful of them, e.g. E. coli, can live and even thrive inside us indefinitely, because they have worked out a modus vivendi whereby they do us no harm (and perhaps some good) and our immune system in turn tolerates their presence.
Why would space microbes be adapted to live inside a human? Why would they even eat the same kind of biomolecules as we do?
It's honestly a tossup between the microbes having no idea what to do in a human body and the human body having no idea what to do with them, assuming they lack PAMPs (pathogen associated molecular patterns) the immune system evolved to recognize.
It's interesting that you could still get adaptive immunity to them, at least antibody-mediated - T cells would just get confused.
Mesozoic era would be about as safe as anthropocene.
Since using space suits was clumsy and restrictive for the actors (they did it in the episode "The Tholian Web" https://www.youtube.com/watch?v=pWdtds3v1j8) and expensive for shows, Star Trek at least fudged the whole thing with the transporter filters (i.e. supposedly when beaming you back up from a planet, they checked for any nasty buggies you might have picked up below): https://memory-alpha.fandom.com/wiki/Biofilter
TL;DR: I don't think this is political, though I suppose the ramifications might be, but I'm concerned about how poverty is calculated in the US and recent articles that point at statistics generated using a newish monthly methodology based on the also newish Supplemental Poverty Measure. I'm wondering if anyone knows about this and can clarify whether these measures are an improvement, better capturing poverty rates or just political hay making numbers.
"At the center of the American Rescue Plan is a monthly payment structured as a tax credit for the vast majority of families — of $300 per child under 6 years old or $250 per child between ages 6 and 17. The benefit has been well received in polls, and studies say it quickly lifted millions of U.S. kids out of poverty."
Something about it seems wrong to me but I can't put my finger on it. With the rise of inflation across a variety of consumer indices (CPI up 5.3%) as well as a quantitative easing (size of Fed balance sheet doubled since last year to over $8 trillion), it's hard for me to imagine anyone was 'lifted' out of poverty.
The big change here is that they calculate poverty on a monthly basis instead of an annual basis, stating numerous times this method is supplemental to annual measurements. The reason they think this is important is that "the average family with children receiving income support in 2018 received more than a third of those transfers in a single month through a one-time tax credit payment." They believe it's important to understand this because month-to-month income volatility is a better representation of how families actually experience poverty. this seems like a reasonable claim.
Still something seems off to me and I'd be glad to hear if anyone else sees flaws in their methodology. The more I read into it, the more it seems like they are making a lot of guesses about what monthly income actually is from data that doesn't provide that level of detail. Furthermore, there seem to be noted issues with the Supplemental Poverty Measure (SPM) that might over-report poverty and fail to account for a number of inputs like home-ownership and health insurance. Do these issues compound if calculated monthly?
I don't actually expect anyone to look at this stuff, but it was definitely an interesting and eye-opening look into official poverty statistics and it seems like the kind of thing that was developed specifically for political football. My bias has me feeling strongly suspicious, but I might be very wrong and would love to hear some other opinions.
It's often been controversial since it was introduced, since anyone is eligible to apply for it regardless of income (back in the 70s, this was defended as allowing women a separate income for the home in the case of abusive/controlling spouses who did not provide enough money to pay bills) and accusations of abuse (our equivalent of 'welfare queens').
Who are some people who look strongly "English"? I visited England several years ago and thought that most of them looked the same as white Americans. However, a minority of them had a strongly "English" appearance that set them apart from white people from other European countries. It was hard to put my finger on what was different, but it was definitely there.
People I'd nominate as strongly "English-looking":
Charles Dance
George Washington
Ken Miles
Bernard Montgomery
I guess they all have big, bony noses and big chins.
From this side of the pond, to me there is a particular 'American look' about the jaw- I think it's because of all that dentistry and orthodontics you lot engage in from a young age; it gives even women prominent, strong jawlines and full cheeks 😀
I would say American whites look like Germans. There’s an English rose type that you don’t really get in the US. And the floppy headed artistic type. Those traits are dying out everywhere maybe.
Growing up in the southeastern U.S., I noticed that a number of rural whites (though not a majority) have eyes that look a little East Asian. I think it's an Irish feature.
"With the right investment grade trained arabian hunting falcon or falcon derivative financial product, things don't have to fall apart. The center *can* hold. Falcons always hear the cry of the falconer, keeping a tight, stable gyre.
This is brilliant. Just keep reading. It gets better and better.
Wouldn't a greenhouse be most efficient if its ceiling were only a little higher than the plants it was intended to have inside of it? A lower ceiling means a lower internal volume, which I presume would maximize the humidity inside the greenhouse since the water vapor wouldn't be dispersed throughout a larger interior volume. Also, a low ceiling keeps heated air around the plants. A lower ceiling height also means the greenhouse's construction requires less material, making it cheaper to create.
A typical eggplant is only 24 inches tall, so wouldn't the ideal eggplant greenhouse be 25 inches tall? Assume robot farmers of arbitrarily small size can enter the structure to do work that human gardeners would normally do.
There are varous implementations of this sort of thing, from sticking half of a 2l soda bottle over your seedlings to dutch lights.
I personally like low tunnels because you can replace the plastic with mesh later in the year and it keeps birds/insects out without overheating the plants. My cat likes them because he reckons it's a tent for him to sleep in.
Apart from the fact that we don't have 25" tall farmers, one of the big advantages of a taller greenhouse is that it has more thermal mass and thus the temperature and humidity remain more consistent. You don't want the air around your plants to be too heated on a hot summer's day.
Commercial greenhouses are mostly roof, so the wall height only contributes a small fraction to the amount of glass needed.
Seems like a complex question. I would not be surprised to learn that the specific air circulation patterns matter, as well as the temperature gradient, and both those things would be affected by the headspace.
I build little movable greenhouses out of reclaimed window panes/ box windows around plants during the winter, and I find that they seem to perform best with only a couple inches if clearance around the plant, but about .3 of the plants total height of clearance above.
The effect is more observable in herbaceous plants than fruit trees.
NO real ideas why, except for: SoCal, so it could be that even winter sun is hot enough to cook them if there is not enough air in the enclosure.
Sprayers need to be a certain height above the beds to distribute the water evenly. I bet they could be engineered differently, though—but there might not be a cost benefit (just speculation).
Let me rephrase this question: Should birds be considered dinosaurs in the same way that, for example, primates are mammals?
I'm not asking whether birds descended from dinosaurs – the evidence is pretty clear on that. It's rather the claim that "dinosaurs didn't go extinct, because birds are dinosaurs" which seems wrong to me. After all, mammals descended from amphibians, and yet nobody claims that "mammals are amphibians".
I'm neither a biologist nor an archeologist (or whoever is responsible for such matters), and my terminology is probably wrong. Maybe the question doesn't even make sense from a scientific perspective, but I don't know how to formulate it properly.
As far as we can tell, a lot/most of the dinosaurs were feathered, so a Deinonychus would have looked like an ostrich/emu/etc. with more complete front claws and teeth and a Tyrannosaurus rex would have looked like an oversized ostrich/emu with, again, more complete teeth. Dinosaurs were transitional forms between what we would now classify as reptiles vs. what we'd now classify as birds (in an anatomical sense) - the four-chambered heart was definitely there (as it's also present in crocodiles, which are the closest living relatives of the dinosaur clade), and a lot of them had become warm-blooded and/or bipedal (theropods in particular, the subset of dinosaurs including the aforementioned Deinonychus and Tyrannosaurus as well as, y'know, birds).
You can absolutely say that large groups of dinosaurs went extinct (e.g. sauropods), as well as the plesiosaurs and pterosaurs (technically not considered dinosaurs). But there's obviously one lineage that survived, and the closer to that lineage you look the more bird-like the dinosaurs look (even back in the Mesozoic) - if, say, Tyrannosaurus had lived to the modern day, it would probably have been considered a bird. Not sure if this answers the question, but it might give some context.
I'd summarize the answer as basically: think about what you really want to know; ask that instead and the answer will usually be obvious - e.g. "Are birds terrifying megafauna that can stomp me to death? No. Are birds some of the closest living relatives of ancient dinosaurs? Yes." And then while it may *feel* like there's still a question "are birds dinosaurs" to be resolved; that question no longer points to anything in the real world that hasn't been answered already, so there's no reason to ask it.
"The machine-gunners' dreams of point blank fire into serried masses of Emus were soon dissipated. The Emu command had evidently ordered guerrilla tactics, and its unwieldy army soon split up into innumerable small units that made use of the military equipment uneconomic. A crestfallen field force therefore withdrew from the combat area after about a month."
I'd say it comes down to a question of whether birds are significantly more distinct physiologically from other branches of the Dinosaur clade than those other branches were from one another, since that seems like the strongest principle on which to split a clade into a paraphylectic group and a crown group.
I don't have a confident answer to that question. Going through differences between birds and their closest living non-dinosaur relatives (crocodiles and alligators), several are know or suspected to be widely shared among many stem dinosaurs (endothermy, erect hind limbs, "bird" hips, bipedalism, body feathers, taloned feet, hollow long bones, "avian" lungs, four-chambered hearts), while others are either unique to true birds or are shared only with closely-related protobirds (hard toothless beaks, avian-style wings, deeply keeled breastbones). And some, like the ZW chromosome mechanism for sex determination, seem to be open research questions.
So is the former list more significant than the latter, and are the latter more significant than similar lists of unique traits among other dinosaur subclades?
So is the former list more significant than the latter, and are the latter more significant than similar lists of unique traits among other dinosaur subclades? My gut feel is yes and no respectively, both of which argue in favor of birds being dinosaurs, but neither list is comprehensive and both were based on top-of head recollections supplemented by light googling. I'm prepared to have other commenters who are better versed in the subject jump in and explain why I'm wrong.
Birds are dinosaurs in the same sense that humans are apes and apes are monkeys and tetrapods are bony fish and land plants are green algae and ants are wasps. I'd say that insisting that all terminology be monophyletic is not likely to be conducive to effective communication. But if you want to be precise, you can say "non-avian dinosaurs".
I knew that the first reply would bring up "non-avian dinosaurs"! ;-)
To me that sounds like "non-terrestrial fish" (to exclude reptiles, mammals, etc.) or "non-aquatic ungulates" (to exclude whales): biologically correct, but misleading outside of scientific contexts, because although reptiles descended from fish and whales descended from ungulates, they are sufficiently different that mammals aren't considered to be fish and whales aren't considered to be hooved mammals.
SSC/ACX got a shoutout on today's Ben Shapiro show, episode 3150, 26 minutes in. Shapiro likes the _Revolt of the Public_ book review and spends several minutes quoting a big chunk of it. He especially likes the notion of the public wanting experts to press - or criticizing for failing to press - a secret "cause miracle" button.
It is amusing how despite being a liberal, Scott is loved by conservatives. "Small Men on the Wrong Side of History", an average-size political book, cites him *seven times*.
My pet theory is that in an era of leftist political hegemony, the 'autistic', society-ignoring curiosity of rationalists gets you to right-wing conclusions because it's all the things the (left) powers that be sweep under the rug. 70 years ago they would have been liberals.
Scott is by no means a liberal on the American political spectrum. On the culture war, which is by far the most significant fault line in American politics today, Scott is clearly a conservative.
I don't think that's true. Scott has publicly defended eg the use of preferred pronouns for trans people, believes in climate change, supports COVID vaccines and lockdowns, etc. He differs from both mainline conservative and mainline progressive stances in significant ways, but he's much closer to mainline progressive.
The idea that being liked by people with different political opinions is somehow controversial, is itself an evidence of strong polarization of (American) society. What is the "normal"? People only able to appreciate good texts written by people with the same political opinion, regardless of the quality of text? (Should I feel weird for liking some Chesterton quotes? Or perhaps, should Chesterton feel weird for being liked by me?)
"I have a dream that one day right here on the internet little conservative boys and little conservative girls will be able to join hands with little progressive boys and progressive girls as sisters and brothers. I have a dream that my four little children will one day live in a nation where they will not be judged by the color of their tribe but by the content of their character."
Have no fear, your dream will come true. Of course, the reason it'll come true is that we'll find another reason to hate each other. It might be one of the good oldies like race, nationality, or wealth, or it might be an entirely new dividing line, like whether you were genetically modified or not.
In a further bit of humor, a user on said hellsite pointed out that the data repeats every 22 rows, and 22 rows is the amount viewable on screen in a default install of excel at 100% zoom.
It's a good article and pretty shocking. You'd think if someone wanted to make fraudulent data, they'd at least put a little bit of effort into making it look believable. Publishing a Cohen's d effect size of 3.2 in addition to the repeating data...
I was tempted to answer "pride in craftsmanship", but then it occurred to me that in a way the incentives actually cut the other direction: if you fake something too well, then you risk nobody ever appreciating your efforts.
Kinda like the line in Christopher Clark's "Sleepwalkers' about the laughably bad secrecy of the Black Hand organization, e.g. holding "secret" meetings in public coffee houses, which Clark attributed to a sentiment of "What was the point of belonging to a secret society if nobody knew you did?"
Reading Kyle Harper's "The Fate of Rome," I was struck by a reference in a table entitled "All Known Epidemics, 50 BC - AD 165" (on page 89, for those of you who may have the book). The description of an epidemic in 90 AD -- the source being Cassius Dio -- reads:
"People died from being smeared with needles, not only in Rome, but virtually the whole world (This obscure notice has defied understanding, and Dio does not actually claim there was an epidemic.)"
Naturally, this raised the question, "What? What the - what? What?" At least, those were my thoughts.
So I looked up the mention in Dio LXXIII:14:3, describing events during the reign of Commodus. (Heh.)
"Moreover, a pestilence occurred, the greatest of any of which I have knowledge; for two thousand persons often died in Rome in a single day. 4 Then, too, many others, not alone in the City, but throughout almost the entire empire, perished at the hands of criminals who smeared some deadly drugs on tiny needles and for pay infected people with the poison by means of these instruments."
(Note that 3 is referencing a disease of some sort; the needle thing comes in at 4.)
That's when I discovered that there had been another such run years before in the reign of Domitian!
"During this period some persons made a business of smearing needles with poison and then pricking with them whomsoever they would. Many persons who were thus attacked died without even knowing the cause, but many of the murderers were informed against and punished. And this sort of thing happened not only in Rome but over practically the whole world."
So....what in the world was going on here? Some sort of mass hysteria? Ninja porcupines? Strangely aggressive pine trees? Johan Larson's aliens with blowguns?
If I take it as a straight account, it's very strange. Who would be paying for those killings?
Alternatively, there was no payment, just mass killings as sometimes happens in the modern world. Or maybe it was assassination for inheritances.
And there might be some hyperbole about how common it was.
My tentative theory is that it's the result of erroneous copying of a text which said something else, but I have no idea what, and I realize this is a not a good approach for handling weird things in ancient texts.
The modern world will swamp future historians with such a huge amount of material (much of it lies or fiction) that it will be just as hard to figure out what's going on.
The specific words of interest are βελόνα and φαρμάκοις. βελόνα does mean needle. But it's also the word for syringe. φαρμάκοις means drug, potion, medicine, poison, etc. You'd probably recognize the word phonetically: pharmakon. I'd take this as saying that assassins were injecting people with the disease for pay. Though it could also be an unrelated poison.
Was there a known poison in ancient times that could kill with only a needle-prick? I'm a bit rusty on my poisons, but if you don't have a poison dart frog handy I was under the impression that most natural poisons are kind of hit and miss in the effectiveness department. What did the Romans have at their disposal poison wise? Arsenic wouldn't work, or deadly nightshade: you need more of a dose than a needle prick for those to be deadly, or even sicken.
Are the symptoms recorded? Faeces would probably suffice to make people dangerously ill if you get it into the blood, though I don't know how reliably a needle prick gets a coating into the bloodstream.
Yeah, I doubt it was actually a poison. Maybe there were one or a few such cases, but I'd be surprised if most of the accusations weren't due to mass hysteria.
Ricin was known. 100% ricin would definitely be dangerous via unnoticed needle-stick (notoriously, it was used by the KGB to murder Georgi Markov with an umbrella gun), but I'm not sure they'd have been able to purify it. 5% ricin would need on the order of 25 milligrams to reach LD50, which is quite a bit for a needle without a syringe behind it.
Lethal dose for cyanide appears to be ~100 mg, which is a bit much for a needle stick. Unless "needle" means "syringe", but I don't think that's likely.
That -- and/or the already-mentioned mass hysteria -- was my working theory. I do wonder, though, if there was something going on to give the people of the time any good reason for thinking of it in the first place, though. Such as maybe an asbestos mine emitting fibers or some such.
It reminds of another story about Roman "poisoning". Some rich people had a fancy party at someone's house, and the weather was nice so they stayed out in the garden after dark. Then lots of people who had been at the party got sick, and they thought someone had poisoned the food. Their doctors pointed out that their symptoms were just like malaria, and being outdoors after dark is a risk factor for malaria, and the city was in the middle of a malaria epidemic.
The first paper I had to write in college had a sentence like "Some people argue [POSITION I NEED TO ATTACK]". The paper came back with that underlined, and a comment: "who says this?" Of course, no one said this. And if they did say it, it would probably have enough nuance that their position would require a more complex counterargument. I knew about strawmanning before before I wrote that, but like now I had a very nice concrete way to check if I was doing it — if I said something like "people think X", an alarm would go off and I'd go do research on what people actually think, and make sure I had an actual representation of their argument.
But like, now, if I was writing that I FOR SURE can find a tweet that says whatever I was strawmanning. I can link the tweet, say look at this, here's why it's wrong. And it will be so shortly phrased that it won't contain any of the couching or caveats that good arguments always have. And it will be phrased in the most controversial (incorrectest) form, because that's what twitter likes?
Maybe there are two notions of strawman:
1. An argument you construct that no one actually holds
2. An argument you construct that no INFORMED person actually holds
I guess maybe it's ok to counter 2? Because if people are tweeting 2, and people are reading 2, I guess it's worth explaining why it's wrong. But like, no one reading your blog will think 2, because they are INFORMED, right?
Anyways, I wonder if banning twitter arguments is an epistemic best practice.
#2 seems to be a defense of nutpicking, and nutpicking is bad. Yes, someone on twitter somewhere said something really stupid and extreme and wholly devoid of nuance. Probably two someones said approximately the same thing. Therefore it is technically true that "some people argue..."
But technically correct is not in fact the best kind of correct, and if "some people" are a tiny irrelevant handful of nuts, then you should say "a tiny irrelevant handful of nuts argue...", and then ask yourself why you are getting involved.
If you can't find anything but tweets, it's probably a handful of nuts.
I've been trying to promote "tinman" as an improved term for "weakman", as the latter term sounds like it could be referring to physical or moral weakness rather than being cherry-picked for making a weakly persuasive argument for a disfavored position.
"Tin" on the other hand connotes something stronger than straw, and superficially appearing more solid still, but nevertheless still weak and artificial (c.f. "tin-plated dictator" or "little tin god"). It's also a natural companion to "strawman", per the Scarecrow and the Tin Woodman from The Wizard of Oz. Which has additional apropos implications, as the Scarecrow was an artificial construct from the beginning, while the Tin Man had started out as a flesh-and-blood human.
That's one of my least favorite trends in "journalism" today, where instead of doing any kind of actual research or interviews, a reporter will just browse Twitter until they find some opinion they can write negatively about.
Yeah, sometimes some "reporter" finds two tweets by people I've never heard of, that might even be troll accounts - and then proceeds to write an article that essentially treats the absurd position stated in the tweets as if it was the rock-solid consensus of the entirety of [the reporter's political outgroup]. But here's the real important question here: When I deplore the fact that people in my own political outgroup tend to go around approvingly citing such articles, am I myself committing a similar kind of quasi-strawman argument?
I came across this paper from Roger Pielke Sr. Thought I'd share. Over the years I've come to respect Pielke's fortitude in being a gadfly to climate modelers. He's been called a denialist, but he's not denying AGW, but rather he's pointing out that models aren't doing a very good job of prediction when compared to the observed.
Please note, I'm not just ranting about climate models here. I'm ranting about models in general! ;-)
I've often heard the platitude about models that they don’t necessarily try to predict what will happen, but they can help us understand possible futures. But it seems to me that a model should logically be seen as a hypothesis. If it can't make an accurate prediction, something is wrong with assumptions being made in the model. Saying a model will "help us understand our possible futures" is a cop out in my view. Assuming that the laws of probability rule the workings of many events, what good does it do us if a model or the models keep predicting the improbable?
Over the past pandemic year-and-a-half I've been tracking the COVID-19 epidemiological models posted up on the CDC website. None of the epidemiological models for COVID-19 have been able to predict case-loads beyond two weeks out—and only a minority of the models can do it moderately within that two-week time horizon! So, the best epidemiological models are working at about the level of weather forecasting, and those can give us an OK picture of where what the case-loads will be in a week to ten days. But the rest might as well be based on astrology. Worse yet, these models don't seem to be improving as we learn more about SARS-CoV-2. And no one seems to be discussing the elephant in the room. What good is knowing the range of all possible future worlds when most are absurdly unlikely?
On the other hand, weather forecasting models have become much more accurate over the past couple of decades. I suspect it’s because their results get a lot more attention from a wider audience, and the predictions are such a short time horizon, that the modelers can see whether they’re off track within a few days.
On the longer term, from the data I’ve seen *most* of the long-term climate models have been overpredicting the actual warming we’ve observed. I’ve been tracking the global warming narrative/arguments/predictions* since 1985. I was taking a course in Glacial Quarternary Geology to familiarize myself with the climate history surrounding the emergence of genus Homo. The geologist teaching our course introduced us to the theory of climate modeling—and he did so when the tide of climate modeling opinion had flipped from the prediction that we’d soon be entering an ice age to one where we’d soon be entering a hothouse. Personally, I was alarmed by the some of the predictions (>3°C by 2025) that I continued to follow the research in Science and Nature — and the advent of the World Wide Web, gave me access to wider range of papers. It became clear to me around 2005 that initial model predictions were wrong. By that time newer models had churned out somewhat more conservative predictions, but I had become less enamored of the usefulness of these models — and any sort of predictive modeling in general.
I see a model as being a hypothesis that is trying to describe a system in way that’s accurate enough to predict the outputs. If the model outputs (predictions) don’t match the observed results, then there’s something wrong with the system described in the model. I complained to a Physicist friend that if you run any of the climate models backwards they can’t predict the past states of climate history. He pointed out that all scientific models fail on that count! It took a while for the implications of that idea to sink in!
* it’s difficult to find an agnostic term to describe the debate that isn’t pro or con to the theory
Its totally unsurprising that we can't model Covid-19 more than 2 weeks in advance. Covid 19 cases are part of a dynamical system subject to a not-particularly-good controls system whose goal is to keep the entire system at a point of instability.
Consider an inverted pendulum on a sliding table. There's a controls system that constantly measures the position of the bob of the pendulum and slides the table so that the hinge will be directly underneath when the pendulum loses all its velocity to gravitational potential energy. But sometimes the control systems sensor are wrong about where the pendulum bob is and these inaccuracies manifest as the pendulum swinging wildly before the controls system saves it (or not). Watching this in action https://www.youtube.com/watch?v=hQK_3C6S4Ak is much better than me describing it.
The mechanics of this system are known perfectly. Without the control system, any deviation away from the unstable fixed point increases (at least initially,) exponentially. However, if you're modeling both, you have to model the real system, but also model the control system's model of the real system. And anything you get wrong about either will grow exponentially until it overwhelms whatever you got right. Covid-19 is like that. It's insufficient to model the covid, you also have to model the fear: all 7,000,000,000 instances of it.
The caution I would have for considering climate models is that if the variable you care about is subject to a controls system, then models might not be able to predict it at all. For a concrete example of this look at the collapse of the Grand Banks fish stocks: https://en.wikipedia.org/wiki/Collapse_of_the_Atlantic_northwest_cod_fishery . The ecosystem looked fine until it totally collapsed. It's not likely that the whole climate is like this, but we should at least consider the possibility that some parts of it that we like are.
I understand most of this except for the part where you say "Covid 19 cases are part of a dynamical system subject to a not-particularly-good controls system whose goal is to keep the entire system at a point of instability." What is this point of instability, & why do we want it?
(I'm also wondering whether you meant to say "if the variable you care about is /not/ subject to a controls system.)
Re. "It's not likely that the whole climate is like this, but we should at least consider the possibility that some parts of it that we like are", that's supported by the IPCC 2015 report, which concluded, "There is little evidence in global climate models of a tipping point or critical threshold in the transition from a perennially ice-covered to a seasonally ice-free Arctic Ocean, beyond which further sea-ice loss is unstoppable and irreversible" (p. 74). It mentions "medium confidence" that there is a Boreal [Arctic tundra (frozen deserts) and boreal forests (shrub pines)] tipping point, but says there are "few adaptation options in the Arctic" (no obvious actions to take); and "low confidence" that there is an Amazon tipping point where "Moist Amazon forests could change abruptly to less-carbon-dense, drought-and-fire-adapted ecosystems". (p. 70)
Marine ecosystems don't get much consideration in the report; the oceans are mostly considered only in terms of how they redistribute heat and CO2. Some mention of coral reefs, acidification, & shellfish; but no mention of tipping points. The oceans haven't been divided up into discrete types of ecosystems to the extent that the land has, and so I suppose aren't as easily analyzed.
Re: Covid-19. Consider the simplest possible model there are only Susceptible and Infected individuals. This model is quite close to reality for a novel disease at the very beginning when the ratio of Susceptible to Recovered is very low. In this model, the only variable is the number (or ratio) of Infected. This differs from the pendulum model in that there's no velocity; it has 2 variables (position and velocity) where this just has 1. This model has 2 stable points: if R_0 is less than 1, the disease dies out if it's greater than 1, it exponentially increases until everyone is infected. What cannot happen is that the number of infected just kinda stays the same. This is what we saw generally during covid: R_0 would be greater than 1, cases would go up, people would get scared and R_0 would go down, cases would go down and then people would relax. The aggregate effect of all this stressing and relaxation has the appearance of "wanting" to balance new cases with recoveries. My point in all this is that there is good reason to believe that modeling the dynamics of covid is more akin to modeling the dynamics of the stock market than it is to modeling hurricanes. Because the dynamics of covid are dependent on the covid models of the people who might be infected.
For the climate stuff. I can't point to anything which might be a tipping point. I'm just generally worried that they might be in there somewhere and we won't know about them until after we fall of the ledge---despite our best efforts to identify them in advance. Although, if pressed, I would point to a potential shutdown of the gulf stream. Would it be a disaster for the whole world? No. Would it significantly harm Britain in particular and Western Europe in general? Maybe. I don't think that there has to be a tipping point for the whole climate for us to get blindsided by one. The thing that keeps me up at night is that we're really interested in a measure of total ecosystem health, but if a few of the numbers that we consider important are, like the abundance of fish in the North Atlantic, subject to a controls system, the ecosystem might look healthy right up to the point it totally collapses.
Ah, so when you mentioned a "controls system whose goal is to keep the entire system at a point of instability", you meant a sort of unconscious collective goal, not the goal of the government. And when you say "subject to a controls system", you don't mean a control system deliberately imposed by humans, but an emergent one.
The sudden abundance of wildfires on the west coast could be just such a "collapse"--an accumulation of dry wood, say, over a period of decades, which passed a critical point just now. But that one is self-correcting. Most tipping points in ecosystems are self-correcting, I suppose because they evolved, and ecosystems that weren't self-correcting crashed and died.
Global temperature is not really an ecosystem nor a living thing, so might not be self-correcting. Yet the climate record shows that it is; global temperature oscillates. Insert anthropomorphic argument here if you like.
The great disasters for life aren't the global heating periods, but the global ice ages, which are an existential risk or close to it, which global warming is not. We don't yet know very well what causes ice ages, and I'd like to see more money put into studying that right now.
Whenever you see someone making a prediction based on a model, ask how the model was validated. If it was, see if you're still in the approximate domain where it was validated. If it wasn't, or if that information is hidden where you can't find it, ignore the prediction, the model, and whoever put forth the model as something you should take seriously.
Every model is a gross oversimplification of reality, based on educated guesses as to what parts of the problem can be ignored or modeled at extremely coarse resolution. For any remotely complex problem, and both climate and COVID are quite complex, nobody will get all those guesses right the first time, just by thinking real hard with their might science brains. You've got to test your guesses against experimental or observational data.
And not in hindsight; that usually just means overfitting to produce a "model" that accurately predicts the past because all it is is an obfuscated curve fit to the past. It is sometimes possible to use blinded historical data to validate a model, but that's rarely done well.
And, yeah, most climate modeling and almost all epidemiological modeling is unvalidated crap.
> On the other hand, weather forecasting models have become much more accurate over the past couple of decades. I suspect it’s because their results get a lot more attention from a wider audience, and the predictions are such a short time horizon, that the modelers can see whether they’re off track within a few days.
Note that there is a massive and immediate feedback. For example predicting path of hurricanes, predicting storms and floods will have immediate effects and can save lives (not only) on timescale of hours and days.
So there is massive benefit of good models and there is zero incentive to be biased toward some result, and noone will complain about results for ideological or political reasons[1].
[1] exceptions apply - but compare to climate models where there is bias of various kinds, extreme politics and so on.
I've built and studied complex models in physical sciences for decades, and your skepticism is if anything far more moderate than deserved. Models of physical systems that are any more complicated than an apple falling from a tree should *always* be treated with deep skepticism. (Parenthetically, I think part of the problem is that people confuse their properties with models of *digital* systems, such as models of digital circuits, or computer programs, which don't suffer from some of the crucial limitations of models of what we might call the "analog" systems constitute the real physical world.)
In general, most complex systems are chaotic, which is both a good and a bad thing. By "chaotic" I mean in the sense that the future values of dynamic variables are exquisitively sensitive to their initial values and on the quality of the evaluation of their propagation. So on the *bad* front, it means almost any practical evaluation of the dynamics will cause your specific dynamic variables to diverge exponentially from what they would be in the real world so fast that if you are relying on their particular values you will get garbage almost immediately. On the "good" front it means that if (and this is the big if!) the important result is driven by thermodynamic (or thermodynamic-like) properties of the system, then your model will rapidly evolve to the correct end result even if you pick stupid initial conditios, or your simulation of the dynamics is imperfect (or you're using double precision math in your program instead of infinite precision ha ha).
So if you are modeling something where you have good reason to suspect some kind of thermodynamic or thermodynamic-like governing principle controls the outcome, then models are robust and valuable. They are a way of discovering what the governing principle dictates, in situations that are otherwise far too complex to discover by direct evaluation. Roughly speaking dynamic models are methods of approximately solving horribly large sets of coupled differential equations when the solution is known to be stable and constrained by some global condition (that's your thermodynamic condition).
But if you are *not* -- if you are attempting to solve for the actual dynamics in a complex system where you have no idea whether there is some robust global constraint, or even worse it is clear there is not -- then you are going to go wrong so fast that usually an informed guess is better.
That doesn't mean such modeling is worthless, though, even when its specific predictions are. You can use models to explore how sensitive your results are to your initial conditions, to various parameters, to various approximations you make to the governing dynamics, and from the point of view of understanding complex dynamics these are all exceedingly valuable things. Indeed, much of our understanding of how choatic systems behave has come from modeling studies which we know don't give the correct results -- but how they go wrong, and how fast, is deeply informative.
With respect to climate modeling, there are certainly governing thermodynamic principles up to a point, because the atmosphere is a thermodynamic system of course, but part of the problem is that you're trying to model a rare deviation from equilibrium and the thermodynamic constraints are less helpful because they aren't as strong. It feels to me a lot like trying to model phase transitions in condensed systems (e.g. freezing of liquids), which is well-known to be very, very difficult, in part because the thermodynamic constraints are by definition weaker at this point of instability. But I'm not in this business, so I may have the wrong impression.
With respect to epidemiology, I can't imagine what the thermodynamic constraints are, aside from there are a finite number of people who can get sick. I would expect that any modeling of the course of an epidemic is therefore essentially worthless past the point where you could do pretty much as well by a simple extrapolation from the present. It's an interesting thing to study, and may have some practical use in terms of discovering things like how sensitive are your results to input data like R0 or the distribution of population density, et cetera, but I would never take *the actual predictions* as actionable.
> Roughly speaking dynamic models are methods of approximately solving horribly large sets of coupled differential equations when the solution is known to be stable and constrained by some global condition (that's your thermodynamic condition).
Can you give me an example of models where thermodynamic or thermodynamic-like governing principle controls the outcome? Not that I'm doubting what you say, I just need an example so I can pin it on to my brain as a type of modeling situation that works.
And that trouble-maker <#snarkasm>, Judith Curry, has just posted some observations about the IPCC AR6. It looks like the IPCC is starting to hedge its modeling bets a bit...
Sure. Let's say you're trying to model how a mutant S protein from a SARS-CoV-2 virus binds to a human ACE2 receptor. You do this with some pretty physical model, meaning you're representing at least individual domains of the two proteins, if not individual atoms, and you've got some model of the forces that is derived from the actual physical forces -- ionic attractions, van der Waals attractions, some model for hydrogen-bonding and/or the hydrophobic effect (or else you're expensively including discrete water molecules). Your purpose, let us say, is to find out whether the binding of the mutant is stronger or weaker than the wild type.
The governing constraint is that you know[1] the underlying system is going to minimize the free energy. But thermodynamics only technically applies in the limit of infinite numbers of degrees of freedom, and how much of the detail of the degrees of freedom and their nature matters in the limit that there are an infinite number of them? Some details, without doubt: we know infinity water molecules behave quite differently than infinity carbon atoms in a diamond lattice. But it's a reasonable hope (and borne out repeatedly empirically) that almost all of the fine details of the interaction and dynamics are washed out, don't matter, and you get the same result whether or not your model of the carbon atom is a hard sphere or a somewhat squishy one, whether you model your ionic interactions perfectly or fudge it with a dielectric constant or a cut-off distance, and whether you solve Newton's equations perfectly or only with 32-bit precision. So there's a lot of detail you can screw up and your model will still reach an accurate (at the level of interest) representation of the real end point, because the system (both in reality and in your model) is being driven to a particular small class of end points by the thermodynamic constraint[2].
This is not by the way some kind of obvious conclusion. When people first started doing computer simulation of complex physical systems in the 1950s (piggybacking off the hardware and algorithms nuclear physicists developed for simulationg fusion bombs), this was an unproved hypothesis, and there were plenty of people who were skeptical about it. It took some time before it was generally accepted that when you're looking for something driven by thermodynamics, you can indeed ignore the fact that your simulated dynamics is going to deviate from the real dynamics very quickly. Doesn't matter, because it's all driven to the same thermodynamic endpoint, both reality and your not-too-far-from reality model.
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[1] You actually don't *know* that, you assume that, but the empirically-proved applicability of thermodynamics to even shockingly small systems has been a staple of the biz since Count Rumford. I wouldn't say we really know *why* it's true, but it is.
[2] Experience tells us you *do* need to make sure you handle certain things pretty well, e.g. you had better make sure energy is conserved. It doesn't have to be collision-by-collision, but it better be overall.
The models I've seen have two major things missing: they don't model transportation or population density. I don't know why; it isn't very hard. You can use general models about the relationship between city size, density, and travel destination frequency to construct a model of both, without needing specific data about real cities. This is a crucial consideration for covid, which seems to spread mainly in urban areas.
Covid models have a tough job in any case, because the data collected hasn't been chosen to make models useful. For instance, last I checked, we don't count deaths caused by covid; we count "covid-related deaths", which in practice means people who died and tested positive for covid (in either order). This is like estimating how many people die of smoking from the number of people who die while they're smokers. Also, hospitals and nursing homes are financially incentivized to declare deaths as covid-related.
We count covid cases, and eventually we started counting number of people tested; but AFAIK we've never recorded the reasons these people were tested, and in particular whether or not they were symptomatic. This would be necessary to use the "number tested" data together with the "number of cases detected" data to estimate the frequency of covid in the population, because the availability of covid tests has varied greatly from time to time and place to place, meaning you can't treat the people tested as a random sample of the population.
I don't know if this even matters anymore. I think both covid and climate change have become too politicized for data or models to be trusted. They have the epistemological status of medieval proofs for the existence of God.
And even that doesn't really matter, since nobody reads the reports. That 2014 IPCC report that was widely reported as saying we're all doomed by 2030 actually said that the economic impact of global warming would be 0.2 to 2.0% of worldwide GNP by 2100 AD--an amount which would be completely eclipsed by a single year of even mediocre economic growth. The "irreversibly doomed by 2030" claim, as best as I can tell, comes from an estimate that, under the very worst-case scenario (in which we inexplicably decide to greatly increase our CO2 emissions right now), using data and parameters from the worst-case scenarios of earlier studies, then there will be enough CO2 in the air by 2033 that, even if all CO2 emissions stop then, the Greenland ice sheet will still eventually melt, raising sea levels by up to 7 feet (worst case) by 4000 AD.
For a while there, the scare headlines were that Greenland was losing the equivalent of Lake Eerie volume of water every year from its ice sheet. Just out of curiosity I looked up the volume of Lake Eerie, and the estimated volume of the Greenland ice sheet to figure out how many Lake Eeries it held. Granted the volume of ice and liquid water are not quite equal, and then I have to worry about the volume of compressed ice, but a quick estimate showed that at the current rate of melting it will be around another 5,000 years. The entire Laurentide ice sheet was larger than the Greenland ice sheet, but it took close to 12K years to melt away. Although the melting started when temperatures were somewhat cooler than today, there was a long period between 10Kya and 8Kya when global temps were between 1.5°-2.5°C warmer than today. That was the period when the last of the Laurentide Ice Sheet disappeared. Anyway, I don't think rising sea levels will be a major concern for several generations at least. We have tide gauge data from past 150 years from geologically stable coastlines (where there's no geological subsidence or uplift going on) that shows no increase in the rate of sea level rise in recent decades.
Data from Wismar Germany going back to 1848 that show a very steady sea level rise of 1.41 mm/year (+/- 0.1 mm). There has been no upward incline in this rate in ~170 years. As an ironic aside, the Heartland Institute took the raw NOAA data, and re-graphed it, and they show the Wismar sea-level rising at a slightly higher rate than the NOAA graph (1.43 vs 1.41 mm/year). But both graphs show no upward incline in the trend.
Likewise, San Francisco shows a steady 1.97 mm/year (+/- 0.18mm) with no upward incline in the trend. (OTOH, cities like Miami in Florida, where aquifer depletion has caused land subsidence, show a rapid sea level rise over the past 30 years.)
Even if you ignore the future impacts of climate change entirely, it has already caused immense damage *today*. For example, record setting wildfires are now an annual occurrence.
Also observing that there is uncertainty in modeling is not an excuse for inaction - it actually makes the tail risks **more** dangerous, not less.
I'm not sure you can lay the California wildfires at the feet of climate change. These fires didn't start spontaneously.
1. PG&E was responsible for a large percentage of them for implementing their restarter technology (which was never approved for deployments in fire-prone areas). This was done to save money on sending out technicians to manually reset failures in the lines. Likewise, PG&E decided to save even more money by contracting out tree trimming around the lines—which it turns out often didn't get done by the contractors.
2. The second most common cause of the fires was arson. There's nothing like a forest fire in the news to get an arsonist motivated to set their own.
3. The third cause of fires was lightning strikes.
Moreover, the forests had been unnaturally shielded from fires for over a century by state and federal forest services. So there was a huge biomass that was ready to burn, burn, burn.
In California, the Native Americans set off regular "controlled" burns. Indeed, if we look at old tree ring data, it seems like they were setting off burns quite frequently—so the flammable biomass never accumulated to the levels it has today. Also, there are accounts from the early white settlers in the California interior that tell of forest fires that would burn for months until the rains came.
Yes, the drought no doubt made things extra flammable, but in an area where we've had severer droughts in the past, it's difficult blame all this on climate change. Rather, I blame it on human stupidity.
The idea that a large wilderness area will or can be expected to go many years with zero ignition events is not plausible. The only cause that matters is the accumulation of a high areal density of dry fuel. Trying to figure out exactly where the spark came from and saying "that's what caused it!", might be the basis for a nice lawsuit but is otherwise pointless.
Four of the last five years have burned >1.5 mil acres, something that almost never happened historically. Nearly all of the biggest wildfires in CA history have happened in the last two years.
What do you think changed five years ago? Did nature suddenly invent lightning?
As for forest policies, the policies people like to criticize go back decades. What changed is not policy, but temperature and drought. One of the reasons that people don't do controlled burns any more is because the new climate means there is no such thing. Those innocuous fires of the past would grow out of control and torch the state if they happened today.
It's also hard to square the "forest management" scapegoating with the global nature of the recent wildfires. What do Siberia and Greece have in common with the American West? I'm pretty sure it's not forest management.
When we think about the natural world we often make the mistake of assuming that what we see today in "wild areas" is like it's always been, and that humans have somehow left the uninhabited these landscapes untouched.
For instance, if you were to visit the countryside of southern New England for a fall foliage excursion, you'll see rolling hills covered in deciduous forests of predominantly maple and oak. If you were to go back in time and visit those same places 150 years ago, you would have seen rolling hills used for dairy farming virtually denuded of trees except for small lots set aside for maples ("sugar bushes" for maple syrup) and wood lots for fire wood. But there were very few extant forests left in Connecticut, Massachusetts and Rhode Island during the 19th Century. If you were to visit southern New England 450 years ago, you would see it covered in mostly climax conifer forests, areas denuded by fires set by Native Americans, and other patches of deciduous forest that had grown up in the agricultural spots abandoned by Native Americans. A good book that describes this is Changes in the Land: Indians, Colonists, and the Ecology of New England, by William Cronon...
Archaeological evidence now suggests that the Amazon rainforest, before the Europeans arrived, was once home to civilizations with an agricultural base that could have supported tens of millions of people. The Amazon rain forest may have only existed in patches 1,000 years ago. But it would be ironic, indeed, if the current Amazon rainforest is an artifact of European colonial expansion which killed off 80-90 percent of native inhabitants with measles and to a lesser extent smallpox.
No, but about a decade ago PG&E started deploying their (illegal) restarter units. According this report, PG&E was responsible for about 1500 fires between 2012 and 2019.
And the recent 30,000 acre Dixie fire *was* caused by PG&E. At least 5 of the 10 most destructive fires in the past 5 years were linked to PG&E equipment, and PG&E and equipment and/or policies were implicated in the other two. Arson comes up as the next most common cause of wildfires in California.
I've lived in California for nigh on 25 years, and in almost every year of those I've heard about things that have happened that have never happened historically. More rain than ever recorded! Less rain than ever recorded! Highest temperature ever in X! Lowest temperature ever in Y! Biggest/lowest yield of crop A, worst floods in county Z, and so on.
In part I think that's because there's a whole lot of things that can happen, and in part it's because California's history isn't very long, and the part of it that contains detailed records of everything that can happen is even shorter.
If we were talking about something that hadn't happened in the last 100,000 years, and we had good records to confirm it, I'd be impressed. But fires...? Meh. I would need a lot better argument than "we haven't recorded this in the 60-100 years people have been keeping somewhat decent track." California is famous for having big burn seasons every now and then even in its recorded history, and it's clearly been going on for a very long time -- far longer than humans have been building combustion engines -- for there to be the many noted adaptions of Western pines to forest fires, including cones that don't even open until the forest has been burned.
I don't mean in that paragraph to say that climate change should be ignored, only to express my despair in noting that it doesn't matter what our models say; politicians will say whatever helps them, the newpapers will repeat whatever quotes they like best, and people will repeat and believe them.
Be careful, though: Record-setting wildfires are always an annual occurrence, in that every year there's a record-setting wildfire somewhere. Checking https://www.oregon.gov/odf/Documents/fire/odf-century-fire-history-chart.pdf , https://en.wikipedia.org/wiki/List_of_California_wildfires , and https://en.wikipedia.org/wiki/List_of_California_wildfires , I see that there have been a lot of big fires on the west coast in the 2010s, and also that 2020 was bizarre--it's something like ten standard deviations above the recent average in terms of acres burned, which would be too large and sudden to be accounted for by climate change if we could model acres burned with a normal distribution. Probably it /doesn't/ have a normal distribution, but a power-law distribution.
Your second point doesn't make sense to me. Uncertainty in modeling gives you bigger tails, in which both lower and higher risks are enclosed. It doesn't change the expected value. It sounds to me like you want to base policy on the worst-case scenario (which is, in fact, what's happening) rather than on the expected value.
But in any case I agree we should take action immediately, and build more nuclear power plants.
Going by that Wikipedia link, four of the last five years have burned >1.5 mil acres, while only two of the preceding 17 years did. There really does seem to have been a major change in the last couple years where cataclysmic wildfires are now a routine event.
Obviously, it's not like the global temperature suddenly jumped in 2017 (and dipped back down in 2019), but there's also no way you can argue that the recent wildfires are within historical parameters. It's clear that the long term warning trend has led to conditions under which wildfires are much more destructive than before.
How confident are you that the acreage burned over the next 10 years will be similar to the current rate instead of something closer to the historical average?
So it certainly looks like it's been increasing since around 1995. And it makes intuitive sense that warmer weather would dry things out and cause fires.
Still, if that's the extent of the evidence that global warming *caused* the increase in fires, then the evidence isn't that strong. There looks to be about as much correlation between global temperature and wildfires as there is between obesity rates in the US and wildfires.
Once we've established causation, the next question is how much of the wildfires are due to the increase in temperature. How much land would have burned if we hadn't warmed the Earth? Is all the increase in wildfires due to global warming?
How do you know it has caused immense damage today? You know that bad things have happened and people who are concerned with climate change blame them on climate change. People who are concerned that preventing small wildfires and restricting timber harvesting produce big wildfires blame them on that. I expect there are other people blaming them on other things. With or without climate change, rare bad things sometimes happen.
Has there been any notable change in the timber management policies of Siberia in the last couple years?
A "rare bad thing" happening once could be just bad luck. But when it happens year after year and all around the world, you'd have to be willfully obtuse to ignore it.
Laurie Anderson is a spectacularly good and weird artist. She is dong a big show at the Hirshhorn in DC. She's 72 and they wanted her to do a retrospective, but she's not interested in going over her past work, so it's a new show, running September 24 to July 31.
Note that a visit could be combined with Worldcon.
She might be of interest for the evolution of art discussion. Her work is avant garde, but it isn't hostile. She's trying to introduce people to non-obvious things, but she isn't punishing them for not seeing them already.
I saw Anderson's Forty-Nine Days in the Bardo which was about pet dog that died.
I'd have sworn I wrote something about it, but I can't find it.
Thing to learn: if you want a really great remembrance after you're dead, be loved by an excellent artist.
Anyway, here are some things I remember. A little statue of the dog which had the cremated ashes worked into the clay and a description of bringing back the smell of wet dog.
A little white statue (maybe a madonna) with a film clip projected on it, giving an illusion of 3D movement. I'm surprised people haven't done more what that technology.
BIG black and white paintings. The only one I remember is a portrait of the dog's face. I think there were others about the confusion of being between lives.
No tie in to physics. Just one that tickled my love of word play.
This was a themed puzzle with a series of clues being movie titles. The trick is to think of a - sometimes twisted - alternative meaning for the title. Answers are generally caps locked in the solutions.
Clue: Top Gun
ROT13’d Answer: GFUVEGPNAABA
Without the intersecting letters from the down answers there is no way I could have solved this. If someone can come up with the answer without that support they are either really lucky or perhaps clairvoyant.
If you want to try to get the puzzle experience without the intersecting words, I suppose you could randomly decipher the ROT13'd letters one or two at a time.
Yeah, it's not a pun. I'd just call it word play. There is no physics meaning in the answer. The way the question is set up sends the solver in that - incorrect -direction with its 'special relativity' phrasing.
As Edward Scizorhands mentions below, the puzzle creator usually give warning of this sort of misdirection by ending the clue with a '?'
FWIW appreciation of this sort of word play is not universal. When I show my wife one of these she gets pretty annoyed, complete with some choice obscenities.
My comment regarding math and physics nerds possibly enjoying the little word game was the clue set up. It *looks* like they are talking about physics, until you have the rug pulled out from under you with the 'aha moment'.
Even though I do enjoy these sorts of twists - big endorphin payoff when I get it - the words 'those bastards' or something similar can come out of my mouth.
Another example from earlier in the week. Warning I'm not going to RO13 the answer cause I'm just demonstrating the technique.
Clue: What jelly rolls are filled with? - Note the ? mark
Answer: ELLS - The words 'jelly rolls' have four occurrence of the letter 'L' . They are filled with ELLS.
If that one annoys you as much as it annoys my wife, then the current NYT XWord is probably not your cup of tea.
I’m looking for good resources to learn math that use visuals and give the intuitions behind the math. 3B1B is exactly the kind of thing I’m looking for. I’m interested in learning a bunch of areas but I’m currently most interested in cryptography.
Why do business leaders consistently refer to their highly educated workforce as "talent"?
This talk of "attracting talent" and "retaining talent" is everywhere I look. (I first thought it was an artefact of tech/Silicon Valley culture, but I hear it in interviews with CEOs in other areas of business too.)
My impression is that they are often very happy to hire someone who learned their skills through extensive experience, rather than being born with them.
I think it's a convenient shorthand for "people with the skills we need", and I admit I don't know a great alternative shorthand. But I don't think this one is great either, as I believe it sends a very exclusionary message.
Is my impression right? If so why did we pick "talent"? And what could we say instead?
Hello
I am reaching out for help as I am struggling with anxiety and mental illness relating to an Information Hazard / AI thought experiment. I am currently being treated by a psychiatrist but I feel like I need to talk to someone who understands simulation hypothesis arguments and related issues.
Can anyone recommend a good offline variant of github? That is, my company has a git repository that lives on an offline network, and primarily I want the better UI experience that github provides relative to the CLI. I think this + lots of other bells and whistles can be had via Enterprise Github for $21/person/month; I'm wondering if there are cheaper alternatives (with fewer bells and whistles) out there.
GitLab is the big one, however if you are just looking for a code browser and not issues, pull requests, CI, etc. then something like cgit: https://git.zx2c4.com/cgit/about/
Thanks! I didn't know about GitLab, it might be the right answer for us. The main thing I really want is a good UI for pull requests. I don't need integrated issue tracking (I can't get it anyway, since the repository is offline, whereas our issue tracking is online so that other people can access it), I could see us getting some use out of CI but living without it doesn't bother me too much, but having review comments consist of plaintext emails saying "on line 137 of file foobar.cs you do this thing, why do you do it" (instead of having that comment hang out next to line 137 of foobar.cs) is really annoying. For some reason, this doesn't seem to be a common feature set, and I'm puzzled by why that is.
I just suffered a heart break, realizing that I missed the Berlin meetup. Hope there will be another one soon!
Burnout.
I've recently saw this TED Talk (uh oh, red flag!) https://www.youtube.com/watch?v=PrJAX-iQ-O4 ("Emily Nagoski and Amelia Nagoski: The cure for burnout (hint: it isn't self-care) | TED")
And I'm curious what do people think about this "stress is a tunnel, it's only a problem if you get stuck in it"?
A criticism of space shows like Star Trek is that, even if an alien planet's atmosphere were chemically identical to Earth's, it still wouldn't be safe to breathe since it would contain microorganisms and toxic particles. Humans who visited would need to wear space suits, which they never do in most space shows.
If you used a time machine to visit the Mesozoic era, would there also be a risk of you breathing in microorganisms or biotoxins that would kill you? Do we have evidence for or against this?
You'd probably want to wear an environment suit (but not a full pressure suit) the first time you visited a completely alien world with a biosphere. Or at least a good filter mask. But the audience wants to see the actors' faces, so we make that concession to reality.
Reality is, the human immune system is really, really good, and even microorganisms that have specifically adapted to our fellow mammals usually can't make a foothold in a human body until they've spent many years evolving in close proximity to humans. An alien microorganism that has the wrong chirality or needs an amino acid humans don't have or whatever, is going to just starve in a human body and probably face an insurmountable evolutionary hump trying to do otherwise.
So the protective gear the first explorers wear is *probably* unnecessary, but nobody who is serious about space travel takes even 1% risks if they don't have to.
They didn’t take any chances when the Apollo crews returned from the moon.
https://en.m.wikipedia.org/wiki/Mobile_quarantine_facility
An allergic reaction seems like a larger risk than an infection.
Very few bacteria even on the Earth are well-adapted to infecting a given species, such as humans. As a rule, nonspecific immunity and the lack of the organism's usual environmental niche mean most random micro-organisms that end up inside us die or are killed almost immediately. It's only a relative handful of species, which have evolved in close parallel to us, which have developed the necessary mechanisms to survive for any length of time*. So a priori alien micro-organisms are very unlikely to be infectious, let alone dangerous.
-------------
* The most successful of them, e.g. E. coli, can live and even thrive inside us indefinitely, because they have worked out a modus vivendi whereby they do us no harm (and perhaps some good) and our immune system in turn tolerates their presence.
Why would space microbes be adapted to live inside a human? Why would they even eat the same kind of biomolecules as we do?
It's honestly a tossup between the microbes having no idea what to do in a human body and the human body having no idea what to do with them, assuming they lack PAMPs (pathogen associated molecular patterns) the immune system evolved to recognize.
It's interesting that you could still get adaptive immunity to them, at least antibody-mediated - T cells would just get confused.
Mesozoic era would be about as safe as anthropocene.
Since using space suits was clumsy and restrictive for the actors (they did it in the episode "The Tholian Web" https://www.youtube.com/watch?v=pWdtds3v1j8) and expensive for shows, Star Trek at least fudged the whole thing with the transporter filters (i.e. supposedly when beaming you back up from a planet, they checked for any nasty buggies you might have picked up below): https://memory-alpha.fandom.com/wiki/Biofilter
TL;DR: I don't think this is political, though I suppose the ramifications might be, but I'm concerned about how poverty is calculated in the US and recent articles that point at statistics generated using a newish monthly methodology based on the also newish Supplemental Poverty Measure. I'm wondering if anyone knows about this and can clarify whether these measures are an improvement, better capturing poverty rates or just political hay making numbers.
For fun, I answer Metaculus prediction questions. One I was recently looking at was: https://www.metaculus.com/questions/7963/will-the-large-child-tax-credit-be-extended/
As I was investigating this I read this claim:
"At the center of the American Rescue Plan is a monthly payment structured as a tax credit for the vast majority of families — of $300 per child under 6 years old or $250 per child between ages 6 and 17. The benefit has been well received in polls, and studies say it quickly lifted millions of U.S. kids out of poverty."
Something about it seems wrong to me but I can't put my finger on it. With the rise of inflation across a variety of consumer indices (CPI up 5.3%) as well as a quantitative easing (size of Fed balance sheet doubled since last year to over $8 trillion), it's hard for me to imagine anyone was 'lifted' out of poverty.
I've been looking at this study and the associated methodology to try and get a better view into this claim: https://www.povertycenter.columbia.edu/forecasting-monthly-poverty-data
The big change here is that they calculate poverty on a monthly basis instead of an annual basis, stating numerous times this method is supplemental to annual measurements. The reason they think this is important is that "the average family with children receiving income support in 2018 received more than a third of those transfers in a single month through a one-time tax credit payment." They believe it's important to understand this because month-to-month income volatility is a better representation of how families actually experience poverty. this seems like a reasonable claim.
Still something seems off to me and I'd be glad to hear if anyone else sees flaws in their methodology. The more I read into it, the more it seems like they are making a lot of guesses about what monthly income actually is from data that doesn't provide that level of detail. Furthermore, there seem to be noted issues with the Supplemental Poverty Measure (SPM) that might over-report poverty and fail to account for a number of inputs like home-ownership and health insurance. Do these issues compound if calculated monthly?
Info: https://www.aei.org/research-products/report/addressing-the-shortcomings-of-the-supplemental-poverty-measure/
I don't actually expect anyone to look at this stuff, but it was definitely an interesting and eye-opening look into official poverty statistics and it seems like the kind of thing that was developed specifically for political football. My bias has me feeling strongly suspicious, but I might be very wrong and would love to hear some other opinions.
We don't have tax credits of that kind here, but we do have Child Benefit (formerly Children's Allowance):
https://www.citizensinformation.ie/en/social_welfare/social_welfare_payments/social_welfare_payments_to_families_and_children/child_benefit.html
It's often been controversial since it was introduced, since anyone is eligible to apply for it regardless of income (back in the 70s, this was defended as allowing women a separate income for the home in the case of abusive/controlling spouses who did not provide enough money to pay bills) and accusations of abuse (our equivalent of 'welfare queens').
Some time ago there were news about something good happening in USA healthcare, with some transparency rules being created. And now
> In addition to a number of other changes, the Final Rule repeals the price transparency requirement for hospitals
https://www.natlawreview.com/article/cms-backs-price-transparency-providers-and-plans
(Provided this means what I think it means)I'm honestly shocked that something like this could happen
But i'm not working, the invisible hand of the free market will guide the promised people to the best possible outcome for all involved
Who are some people who look strongly "English"? I visited England several years ago and thought that most of them looked the same as white Americans. However, a minority of them had a strongly "English" appearance that set them apart from white people from other European countries. It was hard to put my finger on what was different, but it was definitely there.
People I'd nominate as strongly "English-looking":
Charles Dance
George Washington
Ken Miles
Bernard Montgomery
I guess they all have big, bony noses and big chins.
From this side of the pond, to me there is a particular 'American look' about the jaw- I think it's because of all that dentistry and orthodontics you lot engage in from a young age; it gives even women prominent, strong jawlines and full cheeks 😀
I would say American whites look like Germans. There’s an English rose type that you don’t really get in the US. And the floppy headed artistic type. Those traits are dying out everywhere maybe.
Growing up in the southeastern U.S., I noticed that a number of rural whites (though not a majority) have eyes that look a little East Asian. I think it's an Irish feature.
If anyone from Paris sees this, please tell the organizer I might be 20+ minutes late.
I'm pretty sure this is satire.
https://twitter.com/FalconryFinance/status/1446873636485287941
"With the right investment grade trained arabian hunting falcon or falcon derivative financial product, things don't have to fall apart. The center *can* hold. Falcons always hear the cry of the falconer, keeping a tight, stable gyre.
This is brilliant. Just keep reading. It gets better and better.
The junk-grade curry-dipped seagull is probably my favorite element.
Iranian data seems to indicate that natural immunity didn't do much to slow subsequent COVID-19 surges...
https://threadreaderapp.com/thread/1446154506216017921.html
Wouldn't a greenhouse be most efficient if its ceiling were only a little higher than the plants it was intended to have inside of it? A lower ceiling means a lower internal volume, which I presume would maximize the humidity inside the greenhouse since the water vapor wouldn't be dispersed throughout a larger interior volume. Also, a low ceiling keeps heated air around the plants. A lower ceiling height also means the greenhouse's construction requires less material, making it cheaper to create.
A typical eggplant is only 24 inches tall, so wouldn't the ideal eggplant greenhouse be 25 inches tall? Assume robot farmers of arbitrarily small size can enter the structure to do work that human gardeners would normally do.
Plants also need CO2, would there be enough in that case?
There are varous implementations of this sort of thing, from sticking half of a 2l soda bottle over your seedlings to dutch lights.
I personally like low tunnels because you can replace the plastic with mesh later in the year and it keeps birds/insects out without overheating the plants. My cat likes them because he reckons it's a tent for him to sleep in.
Apart from the fact that we don't have 25" tall farmers, one of the big advantages of a taller greenhouse is that it has more thermal mass and thus the temperature and humidity remain more consistent. You don't want the air around your plants to be too heated on a hot summer's day.
Commercial greenhouses are mostly roof, so the wall height only contributes a small fraction to the amount of glass needed.
Seems like a complex question. I would not be surprised to learn that the specific air circulation patterns matter, as well as the temperature gradient, and both those things would be affected by the headspace.
I build little movable greenhouses out of reclaimed window panes/ box windows around plants during the winter, and I find that they seem to perform best with only a couple inches if clearance around the plant, but about .3 of the plants total height of clearance above.
The effect is more observable in herbaceous plants than fruit trees.
NO real ideas why, except for: SoCal, so it could be that even winter sun is hot enough to cook them if there is not enough air in the enclosure.
Sprayers need to be a certain height above the beds to distribute the water evenly. I bet they could be engineered differently, though—but there might not be a cost benefit (just speculation).
Today in nominative determinism that somebody should really have seen coming:
> More than 500 cases of Covid-19 have been linked to the TRNSMT music festival
https://www.bbc.co.uk/news/uk-scotland-58847481
I guess this goes with the earlier gag about Scott’s European tour details being kept on a ‘spreadsheet’ was somewhat ominous. :)
Have fun in Berlin and Paris!
Are birds dinosaurs?
Let me rephrase this question: Should birds be considered dinosaurs in the same way that, for example, primates are mammals?
I'm not asking whether birds descended from dinosaurs – the evidence is pretty clear on that. It's rather the claim that "dinosaurs didn't go extinct, because birds are dinosaurs" which seems wrong to me. After all, mammals descended from amphibians, and yet nobody claims that "mammals are amphibians".
I'm neither a biologist nor an archeologist (or whoever is responsible for such matters), and my terminology is probably wrong. Maybe the question doesn't even make sense from a scientific perspective, but I don't know how to formulate it properly.
As far as we can tell, a lot/most of the dinosaurs were feathered, so a Deinonychus would have looked like an ostrich/emu/etc. with more complete front claws and teeth and a Tyrannosaurus rex would have looked like an oversized ostrich/emu with, again, more complete teeth. Dinosaurs were transitional forms between what we would now classify as reptiles vs. what we'd now classify as birds (in an anatomical sense) - the four-chambered heart was definitely there (as it's also present in crocodiles, which are the closest living relatives of the dinosaur clade), and a lot of them had become warm-blooded and/or bipedal (theropods in particular, the subset of dinosaurs including the aforementioned Deinonychus and Tyrannosaurus as well as, y'know, birds).
You can absolutely say that large groups of dinosaurs went extinct (e.g. sauropods), as well as the plesiosaurs and pterosaurs (technically not considered dinosaurs). But there's obviously one lineage that survived, and the closer to that lineage you look the more bird-like the dinosaurs look (even back in the Mesozoic) - if, say, Tyrannosaurus had lived to the modern day, it would probably have been considered a bird. Not sure if this answers the question, but it might give some context.
There are some classic LW/SSC posts about this kind of thing:
https://www.lesswrong.com/posts/4FcxgdvdQP45D6Skg/disguised-queries
https://slatestarcodex.com/2014/11/21/the-categories-were-made-for-man-not-man-for-the-categories/
https://www.lesswrong.com/posts/895quRDaK6gR2rM82/diseased-thinking-dissolving-questions-about-disease
I'd summarize the answer as basically: think about what you really want to know; ask that instead and the answer will usually be obvious - e.g. "Are birds terrifying megafauna that can stomp me to death? No. Are birds some of the closest living relatives of ancient dinosaurs? Yes." And then while it may *feel* like there's still a question "are birds dinosaurs" to be resolved; that question no longer points to anything in the real world that hasn't been answered already, so there's no reason to ask it.
"Are birds terrifying megafauna that can stomp me to death?"
You may be interested in the Emu War:
https://en.wikipedia.org/wiki/Emu_War
"The machine-gunners' dreams of point blank fire into serried masses of Emus were soon dissipated. The Emu command had evidently ordered guerrilla tactics, and its unwieldy army soon split up into innumerable small units that made use of the military equipment uneconomic. A crestfallen field force therefore withdrew from the combat area after about a month."
I'd say it comes down to a question of whether birds are significantly more distinct physiologically from other branches of the Dinosaur clade than those other branches were from one another, since that seems like the strongest principle on which to split a clade into a paraphylectic group and a crown group.
I don't have a confident answer to that question. Going through differences between birds and their closest living non-dinosaur relatives (crocodiles and alligators), several are know or suspected to be widely shared among many stem dinosaurs (endothermy, erect hind limbs, "bird" hips, bipedalism, body feathers, taloned feet, hollow long bones, "avian" lungs, four-chambered hearts), while others are either unique to true birds or are shared only with closely-related protobirds (hard toothless beaks, avian-style wings, deeply keeled breastbones). And some, like the ZW chromosome mechanism for sex determination, seem to be open research questions.
So is the former list more significant than the latter, and are the latter more significant than similar lists of unique traits among other dinosaur subclades?
Ugh, hit post too soon.
So is the former list more significant than the latter, and are the latter more significant than similar lists of unique traits among other dinosaur subclades? My gut feel is yes and no respectively, both of which argue in favor of birds being dinosaurs, but neither list is comprehensive and both were based on top-of head recollections supplemented by light googling. I'm prepared to have other commenters who are better versed in the subject jump in and explain why I'm wrong.
Birds are dinosaurs in the same sense that humans are apes and apes are monkeys and tetrapods are bony fish and land plants are green algae and ants are wasps. I'd say that insisting that all terminology be monophyletic is not likely to be conducive to effective communication. But if you want to be precise, you can say "non-avian dinosaurs".
I knew that the first reply would bring up "non-avian dinosaurs"! ;-)
To me that sounds like "non-terrestrial fish" (to exclude reptiles, mammals, etc.) or "non-aquatic ungulates" (to exclude whales): biologically correct, but misleading outside of scientific contexts, because although reptiles descended from fish and whales descended from ungulates, they are sufficiently different that mammals aren't considered to be fish and whales aren't considered to be hooved mammals.
https://www.metafilter.com/192879/What-I-learned-about-my-writing-by-seeing-only-the-punctuation#8157764
There's a program which strips out everything but the punctuation-- it turns out that punctuation patterns are distinctive.
SSC/ACX got a shoutout on today's Ben Shapiro show, episode 3150, 26 minutes in. Shapiro likes the _Revolt of the Public_ book review and spends several minutes quoting a big chunk of it. He especially likes the notion of the public wanting experts to press - or criticizing for failing to press - a secret "cause miracle" button.
It is amusing how despite being a liberal, Scott is loved by conservatives. "Small Men on the Wrong Side of History", an average-size political book, cites him *seven times*.
My pet theory is that in an era of leftist political hegemony, the 'autistic', society-ignoring curiosity of rationalists gets you to right-wing conclusions because it's all the things the (left) powers that be sweep under the rug. 70 years ago they would have been liberals.
Scott is by no means a liberal on the American political spectrum. On the culture war, which is by far the most significant fault line in American politics today, Scott is clearly a conservative.
I don't think that's true. Scott has publicly defended eg the use of preferred pronouns for trans people, believes in climate change, supports COVID vaccines and lockdowns, etc. He differs from both mainline conservative and mainline progressive stances in significant ways, but he's much closer to mainline progressive.
I think the meaning of liberal and conservative is in flux enough that it's hard to know what it means.
That would not be true 10 years ago.
Is it even worthwhile to tag worldviews by categories that shift over less than a generation, while the worldview itself stays in place?
Yes. Yes it is. A shifting categorization can coney just as much information as a static one.
The idea that being liked by people with different political opinions is somehow controversial, is itself an evidence of strong polarization of (American) society. What is the "normal"? People only able to appreciate good texts written by people with the same political opinion, regardless of the quality of text? (Should I feel weird for liking some Chesterton quotes? Or perhaps, should Chesterton feel weird for being liked by me?)
"I have a dream that one day right here on the internet little conservative boys and little conservative girls will be able to join hands with little progressive boys and progressive girls as sisters and brothers. I have a dream that my four little children will one day live in a nation where they will not be judged by the color of their tribe but by the content of their character."
I've seen "centrist" hurled as an insult on nerd hobby discords.
At this point instead of communities filtering out crazy members, the members need to filter out crazy communities.
Have no fear, your dream will come true. Of course, the reason it'll come true is that we'll find another reason to hate each other. It might be one of the good oldies like race, nationality, or wealth, or it might be an entirely new dividing line, like whether you were genetically modified or not.
For your consideration, a link from twitter: https://gidmk.medium.com/is-ivermectin-for-covid-19-based-on-fraudulent-research-part-4-f30eeb30d2ff
Re. a hilariously badly faked data set.
In a further bit of humor, a user on said hellsite pointed out that the data repeats every 22 rows, and 22 rows is the amount viewable on screen in a default install of excel at 100% zoom.
Oh, geez.
Thanks for the link, Gideon's entire series on this is quite good.
It's a good article and pretty shocking. You'd think if someone wanted to make fraudulent data, they'd at least put a little bit of effort into making it look believable. Publishing a Cohen's d effect size of 3.2 in addition to the repeating data...
Why bother when faking badly works just as well? So few people actually check the data or care
I was tempted to answer "pride in craftsmanship", but then it occurred to me that in a way the incentives actually cut the other direction: if you fake something too well, then you risk nobody ever appreciating your efforts.
Kinda like the line in Christopher Clark's "Sleepwalkers' about the laughably bad secrecy of the Black Hand organization, e.g. holding "secret" meetings in public coffee houses, which Clark attributed to a sentiment of "What was the point of belonging to a secret society if nobody knew you did?"
If people think you produced good, honest data, isn't that a higher honor than if people know it's a lazy fake?
The thing is, lots of people probably do put effort into making fraudulent data look believable. We only catch the incompetent ones.
Reading Kyle Harper's "The Fate of Rome," I was struck by a reference in a table entitled "All Known Epidemics, 50 BC - AD 165" (on page 89, for those of you who may have the book). The description of an epidemic in 90 AD -- the source being Cassius Dio -- reads:
"People died from being smeared with needles, not only in Rome, but virtually the whole world (This obscure notice has defied understanding, and Dio does not actually claim there was an epidemic.)"
Naturally, this raised the question, "What? What the - what? What?" At least, those were my thoughts.
So I looked up the mention in Dio LXXIII:14:3, describing events during the reign of Commodus. (Heh.)
Cassius Dio LXXIII:14:3
https://penelope.uchicago.edu/Thayer/e/roman/texts/cassius_dio/73*.html
"Moreover, a pestilence occurred, the greatest of any of which I have knowledge; for two thousand persons often died in Rome in a single day. 4 Then, too, many others, not alone in the City, but throughout almost the entire empire, perished at the hands of criminals who smeared some deadly drugs on tiny needles and for pay infected people with the poison by means of these instruments."
(Note that 3 is referencing a disease of some sort; the needle thing comes in at 4.)
That's when I discovered that there had been another such run years before in the reign of Domitian!
Cassius Dio 67:11:6
https://penelope.uchicago.edu/Thayer/e/roman/texts/cassius_dio/67*.html
"During this period some persons made a business of smearing needles with poison and then pricking with them whomsoever they would. Many persons who were thus attacked died without even knowing the cause, but many of the murderers were informed against and punished. And this sort of thing happened not only in Rome but over practically the whole world."
So....what in the world was going on here? Some sort of mass hysteria? Ninja porcupines? Strangely aggressive pine trees? Johan Larson's aliens with blowguns?
If I take it as a straight account, it's very strange. Who would be paying for those killings?
Alternatively, there was no payment, just mass killings as sometimes happens in the modern world. Or maybe it was assassination for inheritances.
And there might be some hyperbole about how common it was.
My tentative theory is that it's the result of erroneous copying of a text which said something else, but I have no idea what, and I realize this is a not a good approach for handling weird things in ancient texts.
The modern world will swamp future historians with such a huge amount of material (much of it lies or fiction) that it will be just as hard to figure out what's going on.
In Greek:
Πολλοὶ δὲ καὶ ἄλλως οὐκ ἐν τῷ ἄστει μόνον ἀλλὰ καὶ ἐν ὅλῃ ὡς εἰπεῖν τῇ ἀρχῇ ὑπ´ ἀνδρῶν κακούργων ἀπέθανον· βελόνας γὰρ μικρὰς δηλητηρίοις τισὶ φαρμάκοις ἐγχρίοντες ἐνίεσαν δι´ αὐτῶν ἐς ἑτέρους ἐπὶ μισθῷ τὸ δεινόν· ὅπερ που καὶ ἐπὶ τοῦ Δομιτιανοῦ ἐγεγόνει.
The specific words of interest are βελόνα and φαρμάκοις. βελόνα does mean needle. But it's also the word for syringe. φαρμάκοις means drug, potion, medicine, poison, etc. You'd probably recognize the word phonetically: pharmakon. I'd take this as saying that assassins were injecting people with the disease for pay. Though it could also be an unrelated poison.
I'd put my money on mass hysteria - something like the London Monster: https://en.wikipedia.org/wiki/London_Monster
Was there a known poison in ancient times that could kill with only a needle-prick? I'm a bit rusty on my poisons, but if you don't have a poison dart frog handy I was under the impression that most natural poisons are kind of hit and miss in the effectiveness department. What did the Romans have at their disposal poison wise? Arsenic wouldn't work, or deadly nightshade: you need more of a dose than a needle prick for those to be deadly, or even sicken.
Are the symptoms recorded? Faeces would probably suffice to make people dangerously ill if you get it into the blood, though I don't know how reliably a needle prick gets a coating into the bloodstream.
Yeah, I doubt it was actually a poison. Maybe there were one or a few such cases, but I'd be surprised if most of the accusations weren't due to mass hysteria.
Ricin was known. 100% ricin would definitely be dangerous via unnoticed needle-stick (notoriously, it was used by the KGB to murder Georgi Markov with an umbrella gun), but I'm not sure they'd have been able to purify it. 5% ricin would need on the order of 25 milligrams to reach LD50, which is quite a bit for a needle without a syringe behind it.
Cyanide, maybe? I've found mixed answers as to whether or not Roman poisoners made use of cyanide.
Lethal dose for cyanide appears to be ~100 mg, which is a bit much for a needle stick. Unless "needle" means "syringe", but I don't think that's likely.
Classic blaming of natural disasters on a part of the population. See also, Black Death, Rome's fire, and so on.
That -- and/or the already-mentioned mass hysteria -- was my working theory. I do wonder, though, if there was something going on to give the people of the time any good reason for thinking of it in the first place, though. Such as maybe an asbestos mine emitting fibers or some such.
It reminds of another story about Roman "poisoning". Some rich people had a fancy party at someone's house, and the weather was nice so they stayed out in the garden after dark. Then lots of people who had been at the party got sick, and they thought someone had poisoned the food. Their doctors pointed out that their symptoms were just like malaria, and being outdoors after dark is a risk factor for malaria, and the city was in the middle of a malaria epidemic.
Is it bad that twitter is a strawman factory?
The first paper I had to write in college had a sentence like "Some people argue [POSITION I NEED TO ATTACK]". The paper came back with that underlined, and a comment: "who says this?" Of course, no one said this. And if they did say it, it would probably have enough nuance that their position would require a more complex counterargument. I knew about strawmanning before before I wrote that, but like now I had a very nice concrete way to check if I was doing it — if I said something like "people think X", an alarm would go off and I'd go do research on what people actually think, and make sure I had an actual representation of their argument.
But like, now, if I was writing that I FOR SURE can find a tweet that says whatever I was strawmanning. I can link the tweet, say look at this, here's why it's wrong. And it will be so shortly phrased that it won't contain any of the couching or caveats that good arguments always have. And it will be phrased in the most controversial (incorrectest) form, because that's what twitter likes?
Maybe there are two notions of strawman:
1. An argument you construct that no one actually holds
2. An argument you construct that no INFORMED person actually holds
I guess maybe it's ok to counter 2? Because if people are tweeting 2, and people are reading 2, I guess it's worth explaining why it's wrong. But like, no one reading your blog will think 2, because they are INFORMED, right?
Anyways, I wonder if banning twitter arguments is an epistemic best practice.
#2 seems to be a defense of nutpicking, and nutpicking is bad. Yes, someone on twitter somewhere said something really stupid and extreme and wholly devoid of nuance. Probably two someones said approximately the same thing. Therefore it is technically true that "some people argue..."
But technically correct is not in fact the best kind of correct, and if "some people" are a tiny irrelevant handful of nuts, then you should say "a tiny irrelevant handful of nuts argue...", and then ask yourself why you are getting involved.
If you can't find anything but tweets, it's probably a handful of nuts.
"Weakman" is the term for a dumb and easily defeated position that someone in your outgroup genuinely and actually holds.
Also, a lot of news media seems to work off the exact "find someone mad about it on Twitter" model.
I've been trying to promote "tinman" as an improved term for "weakman", as the latter term sounds like it could be referring to physical or moral weakness rather than being cherry-picked for making a weakly persuasive argument for a disfavored position.
"Tin" on the other hand connotes something stronger than straw, and superficially appearing more solid still, but nevertheless still weak and artificial (c.f. "tin-plated dictator" or "little tin god"). It's also a natural companion to "strawman", per the Scarecrow and the Tin Woodman from The Wizard of Oz. Which has additional apropos implications, as the Scarecrow was an artificial construct from the beginning, while the Tin Man had started out as a flesh-and-blood human.
That's one of my least favorite trends in "journalism" today, where instead of doing any kind of actual research or interviews, a reporter will just browse Twitter until they find some opinion they can write negatively about.
Yeah, sometimes some "reporter" finds two tweets by people I've never heard of, that might even be troll accounts - and then proceeds to write an article that essentially treats the absurd position stated in the tweets as if it was the rock-solid consensus of the entirety of [the reporter's political outgroup]. But here's the real important question here: When I deplore the fact that people in my own political outgroup tend to go around approvingly citing such articles, am I myself committing a similar kind of quasi-strawman argument?
I came across this paper from Roger Pielke Sr. Thought I'd share. Over the years I've come to respect Pielke's fortitude in being a gadfly to climate modelers. He's been called a denialist, but he's not denying AGW, but rather he's pointing out that models aren't doing a very good job of prediction when compared to the observed.
https://issues.org/climate-change-scenarios-lost-touch-reality-pielke-ritchie/#.YVxxJDFpEeo.twitter
Please note, I'm not just ranting about climate models here. I'm ranting about models in general! ;-)
I've often heard the platitude about models that they don’t necessarily try to predict what will happen, but they can help us understand possible futures. But it seems to me that a model should logically be seen as a hypothesis. If it can't make an accurate prediction, something is wrong with assumptions being made in the model. Saying a model will "help us understand our possible futures" is a cop out in my view. Assuming that the laws of probability rule the workings of many events, what good does it do us if a model or the models keep predicting the improbable?
Over the past pandemic year-and-a-half I've been tracking the COVID-19 epidemiological models posted up on the CDC website. None of the epidemiological models for COVID-19 have been able to predict case-loads beyond two weeks out—and only a minority of the models can do it moderately within that two-week time horizon! So, the best epidemiological models are working at about the level of weather forecasting, and those can give us an OK picture of where what the case-loads will be in a week to ten days. But the rest might as well be based on astrology. Worse yet, these models don't seem to be improving as we learn more about SARS-CoV-2. And no one seems to be discussing the elephant in the room. What good is knowing the range of all possible future worlds when most are absurdly unlikely?
On the other hand, weather forecasting models have become much more accurate over the past couple of decades. I suspect it’s because their results get a lot more attention from a wider audience, and the predictions are such a short time horizon, that the modelers can see whether they’re off track within a few days.
On the longer term, from the data I’ve seen *most* of the long-term climate models have been overpredicting the actual warming we’ve observed. I’ve been tracking the global warming narrative/arguments/predictions* since 1985. I was taking a course in Glacial Quarternary Geology to familiarize myself with the climate history surrounding the emergence of genus Homo. The geologist teaching our course introduced us to the theory of climate modeling—and he did so when the tide of climate modeling opinion had flipped from the prediction that we’d soon be entering an ice age to one where we’d soon be entering a hothouse. Personally, I was alarmed by the some of the predictions (>3°C by 2025) that I continued to follow the research in Science and Nature — and the advent of the World Wide Web, gave me access to wider range of papers. It became clear to me around 2005 that initial model predictions were wrong. By that time newer models had churned out somewhat more conservative predictions, but I had become less enamored of the usefulness of these models — and any sort of predictive modeling in general.
I see a model as being a hypothesis that is trying to describe a system in way that’s accurate enough to predict the outputs. If the model outputs (predictions) don’t match the observed results, then there’s something wrong with the system described in the model. I complained to a Physicist friend that if you run any of the climate models backwards they can’t predict the past states of climate history. He pointed out that all scientific models fail on that count! It took a while for the implications of that idea to sink in!
* it’s difficult to find an agnostic term to describe the debate that isn’t pro or con to the theory
Its totally unsurprising that we can't model Covid-19 more than 2 weeks in advance. Covid 19 cases are part of a dynamical system subject to a not-particularly-good controls system whose goal is to keep the entire system at a point of instability.
Consider an inverted pendulum on a sliding table. There's a controls system that constantly measures the position of the bob of the pendulum and slides the table so that the hinge will be directly underneath when the pendulum loses all its velocity to gravitational potential energy. But sometimes the control systems sensor are wrong about where the pendulum bob is and these inaccuracies manifest as the pendulum swinging wildly before the controls system saves it (or not). Watching this in action https://www.youtube.com/watch?v=hQK_3C6S4Ak is much better than me describing it.
The mechanics of this system are known perfectly. Without the control system, any deviation away from the unstable fixed point increases (at least initially,) exponentially. However, if you're modeling both, you have to model the real system, but also model the control system's model of the real system. And anything you get wrong about either will grow exponentially until it overwhelms whatever you got right. Covid-19 is like that. It's insufficient to model the covid, you also have to model the fear: all 7,000,000,000 instances of it.
The caution I would have for considering climate models is that if the variable you care about is subject to a controls system, then models might not be able to predict it at all. For a concrete example of this look at the collapse of the Grand Banks fish stocks: https://en.wikipedia.org/wiki/Collapse_of_the_Atlantic_northwest_cod_fishery . The ecosystem looked fine until it totally collapsed. It's not likely that the whole climate is like this, but we should at least consider the possibility that some parts of it that we like are.
I understand most of this except for the part where you say "Covid 19 cases are part of a dynamical system subject to a not-particularly-good controls system whose goal is to keep the entire system at a point of instability." What is this point of instability, & why do we want it?
(I'm also wondering whether you meant to say "if the variable you care about is /not/ subject to a controls system.)
Re. "It's not likely that the whole climate is like this, but we should at least consider the possibility that some parts of it that we like are", that's supported by the IPCC 2015 report, which concluded, "There is little evidence in global climate models of a tipping point or critical threshold in the transition from a perennially ice-covered to a seasonally ice-free Arctic Ocean, beyond which further sea-ice loss is unstoppable and irreversible" (p. 74). It mentions "medium confidence" that there is a Boreal [Arctic tundra (frozen deserts) and boreal forests (shrub pines)] tipping point, but says there are "few adaptation options in the Arctic" (no obvious actions to take); and "low confidence" that there is an Amazon tipping point where "Moist Amazon forests could change abruptly to less-carbon-dense, drought-and-fire-adapted ecosystems". (p. 70)
Marine ecosystems don't get much consideration in the report; the oceans are mostly considered only in terms of how they redistribute heat and CO2. Some mention of coral reefs, acidification, & shellfish; but no mention of tipping points. The oceans haven't been divided up into discrete types of ecosystems to the extent that the land has, and so I suppose aren't as easily analyzed.
Re: Covid-19. Consider the simplest possible model there are only Susceptible and Infected individuals. This model is quite close to reality for a novel disease at the very beginning when the ratio of Susceptible to Recovered is very low. In this model, the only variable is the number (or ratio) of Infected. This differs from the pendulum model in that there's no velocity; it has 2 variables (position and velocity) where this just has 1. This model has 2 stable points: if R_0 is less than 1, the disease dies out if it's greater than 1, it exponentially increases until everyone is infected. What cannot happen is that the number of infected just kinda stays the same. This is what we saw generally during covid: R_0 would be greater than 1, cases would go up, people would get scared and R_0 would go down, cases would go down and then people would relax. The aggregate effect of all this stressing and relaxation has the appearance of "wanting" to balance new cases with recoveries. My point in all this is that there is good reason to believe that modeling the dynamics of covid is more akin to modeling the dynamics of the stock market than it is to modeling hurricanes. Because the dynamics of covid are dependent on the covid models of the people who might be infected.
For the climate stuff. I can't point to anything which might be a tipping point. I'm just generally worried that they might be in there somewhere and we won't know about them until after we fall of the ledge---despite our best efforts to identify them in advance. Although, if pressed, I would point to a potential shutdown of the gulf stream. Would it be a disaster for the whole world? No. Would it significantly harm Britain in particular and Western Europe in general? Maybe. I don't think that there has to be a tipping point for the whole climate for us to get blindsided by one. The thing that keeps me up at night is that we're really interested in a measure of total ecosystem health, but if a few of the numbers that we consider important are, like the abundance of fish in the North Atlantic, subject to a controls system, the ecosystem might look healthy right up to the point it totally collapses.
Ah, so when you mentioned a "controls system whose goal is to keep the entire system at a point of instability", you meant a sort of unconscious collective goal, not the goal of the government. And when you say "subject to a controls system", you don't mean a control system deliberately imposed by humans, but an emergent one.
The sudden abundance of wildfires on the west coast could be just such a "collapse"--an accumulation of dry wood, say, over a period of decades, which passed a critical point just now. But that one is self-correcting. Most tipping points in ecosystems are self-correcting, I suppose because they evolved, and ecosystems that weren't self-correcting crashed and died.
Global temperature is not really an ecosystem nor a living thing, so might not be self-correcting. Yet the climate record shows that it is; global temperature oscillates. Insert anthropomorphic argument here if you like.
The great disasters for life aren't the global heating periods, but the global ice ages, which are an existential risk or close to it, which global warming is not. We don't yet know very well what causes ice ages, and I'd like to see more money put into studying that right now.
Whenever you see someone making a prediction based on a model, ask how the model was validated. If it was, see if you're still in the approximate domain where it was validated. If it wasn't, or if that information is hidden where you can't find it, ignore the prediction, the model, and whoever put forth the model as something you should take seriously.
Every model is a gross oversimplification of reality, based on educated guesses as to what parts of the problem can be ignored or modeled at extremely coarse resolution. For any remotely complex problem, and both climate and COVID are quite complex, nobody will get all those guesses right the first time, just by thinking real hard with their might science brains. You've got to test your guesses against experimental or observational data.
And not in hindsight; that usually just means overfitting to produce a "model" that accurately predicts the past because all it is is an obfuscated curve fit to the past. It is sometimes possible to use blinded historical data to validate a model, but that's rarely done well.
And, yeah, most climate modeling and almost all epidemiological modeling is unvalidated crap.
> On the other hand, weather forecasting models have become much more accurate over the past couple of decades. I suspect it’s because their results get a lot more attention from a wider audience, and the predictions are such a short time horizon, that the modelers can see whether they’re off track within a few days.
Note that there is a massive and immediate feedback. For example predicting path of hurricanes, predicting storms and floods will have immediate effects and can save lives (not only) on timescale of hours and days.
So there is massive benefit of good models and there is zero incentive to be biased toward some result, and noone will complain about results for ideological or political reasons[1].
[1] exceptions apply - but compare to climate models where there is bias of various kinds, extreme politics and so on.
I've built and studied complex models in physical sciences for decades, and your skepticism is if anything far more moderate than deserved. Models of physical systems that are any more complicated than an apple falling from a tree should *always* be treated with deep skepticism. (Parenthetically, I think part of the problem is that people confuse their properties with models of *digital* systems, such as models of digital circuits, or computer programs, which don't suffer from some of the crucial limitations of models of what we might call the "analog" systems constitute the real physical world.)
In general, most complex systems are chaotic, which is both a good and a bad thing. By "chaotic" I mean in the sense that the future values of dynamic variables are exquisitively sensitive to their initial values and on the quality of the evaluation of their propagation. So on the *bad* front, it means almost any practical evaluation of the dynamics will cause your specific dynamic variables to diverge exponentially from what they would be in the real world so fast that if you are relying on their particular values you will get garbage almost immediately. On the "good" front it means that if (and this is the big if!) the important result is driven by thermodynamic (or thermodynamic-like) properties of the system, then your model will rapidly evolve to the correct end result even if you pick stupid initial conditios, or your simulation of the dynamics is imperfect (or you're using double precision math in your program instead of infinite precision ha ha).
So if you are modeling something where you have good reason to suspect some kind of thermodynamic or thermodynamic-like governing principle controls the outcome, then models are robust and valuable. They are a way of discovering what the governing principle dictates, in situations that are otherwise far too complex to discover by direct evaluation. Roughly speaking dynamic models are methods of approximately solving horribly large sets of coupled differential equations when the solution is known to be stable and constrained by some global condition (that's your thermodynamic condition).
But if you are *not* -- if you are attempting to solve for the actual dynamics in a complex system where you have no idea whether there is some robust global constraint, or even worse it is clear there is not -- then you are going to go wrong so fast that usually an informed guess is better.
That doesn't mean such modeling is worthless, though, even when its specific predictions are. You can use models to explore how sensitive your results are to your initial conditions, to various parameters, to various approximations you make to the governing dynamics, and from the point of view of understanding complex dynamics these are all exceedingly valuable things. Indeed, much of our understanding of how choatic systems behave has come from modeling studies which we know don't give the correct results -- but how they go wrong, and how fast, is deeply informative.
With respect to climate modeling, there are certainly governing thermodynamic principles up to a point, because the atmosphere is a thermodynamic system of course, but part of the problem is that you're trying to model a rare deviation from equilibrium and the thermodynamic constraints are less helpful because they aren't as strong. It feels to me a lot like trying to model phase transitions in condensed systems (e.g. freezing of liquids), which is well-known to be very, very difficult, in part because the thermodynamic constraints are by definition weaker at this point of instability. But I'm not in this business, so I may have the wrong impression.
With respect to epidemiology, I can't imagine what the thermodynamic constraints are, aside from there are a finite number of people who can get sick. I would expect that any modeling of the course of an epidemic is therefore essentially worthless past the point where you could do pretty much as well by a simple extrapolation from the present. It's an interesting thing to study, and may have some practical use in terms of discovering things like how sensitive are your results to input data like R0 or the distribution of population density, et cetera, but I would never take *the actual predictions* as actionable.
Carl, you wrote:
> Roughly speaking dynamic models are methods of approximately solving horribly large sets of coupled differential equations when the solution is known to be stable and constrained by some global condition (that's your thermodynamic condition).
Can you give me an example of models where thermodynamic or thermodynamic-like governing principle controls the outcome? Not that I'm doubting what you say, I just need an example so I can pin it on to my brain as a type of modeling situation that works.
And that trouble-maker <#snarkasm>, Judith Curry, has just posted some observations about the IPCC AR6. It looks like the IPCC is starting to hedge its modeling bets a bit...
https://judithcurry.com/2021/10/06/ipcc-ar6-breaking-the-hegemony-of-global-climate-models/#more-27876
Sure. Let's say you're trying to model how a mutant S protein from a SARS-CoV-2 virus binds to a human ACE2 receptor. You do this with some pretty physical model, meaning you're representing at least individual domains of the two proteins, if not individual atoms, and you've got some model of the forces that is derived from the actual physical forces -- ionic attractions, van der Waals attractions, some model for hydrogen-bonding and/or the hydrophobic effect (or else you're expensively including discrete water molecules). Your purpose, let us say, is to find out whether the binding of the mutant is stronger or weaker than the wild type.
The governing constraint is that you know[1] the underlying system is going to minimize the free energy. But thermodynamics only technically applies in the limit of infinite numbers of degrees of freedom, and how much of the detail of the degrees of freedom and their nature matters in the limit that there are an infinite number of them? Some details, without doubt: we know infinity water molecules behave quite differently than infinity carbon atoms in a diamond lattice. But it's a reasonable hope (and borne out repeatedly empirically) that almost all of the fine details of the interaction and dynamics are washed out, don't matter, and you get the same result whether or not your model of the carbon atom is a hard sphere or a somewhat squishy one, whether you model your ionic interactions perfectly or fudge it with a dielectric constant or a cut-off distance, and whether you solve Newton's equations perfectly or only with 32-bit precision. So there's a lot of detail you can screw up and your model will still reach an accurate (at the level of interest) representation of the real end point, because the system (both in reality and in your model) is being driven to a particular small class of end points by the thermodynamic constraint[2].
This is not by the way some kind of obvious conclusion. When people first started doing computer simulation of complex physical systems in the 1950s (piggybacking off the hardware and algorithms nuclear physicists developed for simulationg fusion bombs), this was an unproved hypothesis, and there were plenty of people who were skeptical about it. It took some time before it was generally accepted that when you're looking for something driven by thermodynamics, you can indeed ignore the fact that your simulated dynamics is going to deviate from the real dynamics very quickly. Doesn't matter, because it's all driven to the same thermodynamic endpoint, both reality and your not-too-far-from reality model.
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[1] You actually don't *know* that, you assume that, but the empirically-proved applicability of thermodynamics to even shockingly small systems has been a staple of the biz since Count Rumford. I wouldn't say we really know *why* it's true, but it is.
[2] Experience tells us you *do* need to make sure you handle certain things pretty well, e.g. you had better make sure energy is conserved. It doesn't have to be collision-by-collision, but it better be overall.
The models I've seen have two major things missing: they don't model transportation or population density. I don't know why; it isn't very hard. You can use general models about the relationship between city size, density, and travel destination frequency to construct a model of both, without needing specific data about real cities. This is a crucial consideration for covid, which seems to spread mainly in urban areas.
Covid models have a tough job in any case, because the data collected hasn't been chosen to make models useful. For instance, last I checked, we don't count deaths caused by covid; we count "covid-related deaths", which in practice means people who died and tested positive for covid (in either order). This is like estimating how many people die of smoking from the number of people who die while they're smokers. Also, hospitals and nursing homes are financially incentivized to declare deaths as covid-related.
We count covid cases, and eventually we started counting number of people tested; but AFAIK we've never recorded the reasons these people were tested, and in particular whether or not they were symptomatic. This would be necessary to use the "number tested" data together with the "number of cases detected" data to estimate the frequency of covid in the population, because the availability of covid tests has varied greatly from time to time and place to place, meaning you can't treat the people tested as a random sample of the population.
I don't know if this even matters anymore. I think both covid and climate change have become too politicized for data or models to be trusted. They have the epistemological status of medieval proofs for the existence of God.
And even that doesn't really matter, since nobody reads the reports. That 2014 IPCC report that was widely reported as saying we're all doomed by 2030 actually said that the economic impact of global warming would be 0.2 to 2.0% of worldwide GNP by 2100 AD--an amount which would be completely eclipsed by a single year of even mediocre economic growth. The "irreversibly doomed by 2030" claim, as best as I can tell, comes from an estimate that, under the very worst-case scenario (in which we inexplicably decide to greatly increase our CO2 emissions right now), using data and parameters from the worst-case scenarios of earlier studies, then there will be enough CO2 in the air by 2033 that, even if all CO2 emissions stop then, the Greenland ice sheet will still eventually melt, raising sea levels by up to 7 feet (worst case) by 4000 AD.
For a while there, the scare headlines were that Greenland was losing the equivalent of Lake Eerie volume of water every year from its ice sheet. Just out of curiosity I looked up the volume of Lake Eerie, and the estimated volume of the Greenland ice sheet to figure out how many Lake Eeries it held. Granted the volume of ice and liquid water are not quite equal, and then I have to worry about the volume of compressed ice, but a quick estimate showed that at the current rate of melting it will be around another 5,000 years. The entire Laurentide ice sheet was larger than the Greenland ice sheet, but it took close to 12K years to melt away. Although the melting started when temperatures were somewhat cooler than today, there was a long period between 10Kya and 8Kya when global temps were between 1.5°-2.5°C warmer than today. That was the period when the last of the Laurentide Ice Sheet disappeared. Anyway, I don't think rising sea levels will be a major concern for several generations at least. We have tide gauge data from past 150 years from geologically stable coastlines (where there's no geological subsidence or uplift going on) that shows no increase in the rate of sea level rise in recent decades.
Data from Wismar Germany going back to 1848 that show a very steady sea level rise of 1.41 mm/year (+/- 0.1 mm). There has been no upward incline in this rate in ~170 years. As an ironic aside, the Heartland Institute took the raw NOAA data, and re-graphed it, and they show the Wismar sea-level rising at a slightly higher rate than the NOAA graph (1.43 vs 1.41 mm/year). But both graphs show no upward incline in the trend.
Likewise, San Francisco shows a steady 1.97 mm/year (+/- 0.18mm) with no upward incline in the trend. (OTOH, cities like Miami in Florida, where aquifer depletion has caused land subsidence, show a rapid sea level rise over the past 30 years.)
Wismar Germany, average sea levels since 1848:
https://tidesandcurrents.noaa.gov/sltrends/sltrends_global_station.shtml?stnid=120-022
San Francisco average sea-levels since 1850:
https://tidesandcurrents.noaa.gov/sltrends/sltrends_station.shtml?id=9414290
Even if you ignore the future impacts of climate change entirely, it has already caused immense damage *today*. For example, record setting wildfires are now an annual occurrence.
Also observing that there is uncertainty in modeling is not an excuse for inaction - it actually makes the tail risks **more** dangerous, not less.
I'm not sure you can lay the California wildfires at the feet of climate change. These fires didn't start spontaneously.
1. PG&E was responsible for a large percentage of them for implementing their restarter technology (which was never approved for deployments in fire-prone areas). This was done to save money on sending out technicians to manually reset failures in the lines. Likewise, PG&E decided to save even more money by contracting out tree trimming around the lines—which it turns out often didn't get done by the contractors.
2. The second most common cause of the fires was arson. There's nothing like a forest fire in the news to get an arsonist motivated to set their own.
3. The third cause of fires was lightning strikes.
Moreover, the forests had been unnaturally shielded from fires for over a century by state and federal forest services. So there was a huge biomass that was ready to burn, burn, burn.
In California, the Native Americans set off regular "controlled" burns. Indeed, if we look at old tree ring data, it seems like they were setting off burns quite frequently—so the flammable biomass never accumulated to the levels it has today. Also, there are accounts from the early white settlers in the California interior that tell of forest fires that would burn for months until the rains came.
Yes, the drought no doubt made things extra flammable, but in an area where we've had severer droughts in the past, it's difficult blame all this on climate change. Rather, I blame it on human stupidity.
The idea that a large wilderness area will or can be expected to go many years with zero ignition events is not plausible. The only cause that matters is the accumulation of a high areal density of dry fuel. Trying to figure out exactly where the spark came from and saying "that's what caused it!", might be the basis for a nice lawsuit but is otherwise pointless.
Four of the last five years have burned >1.5 mil acres, something that almost never happened historically. Nearly all of the biggest wildfires in CA history have happened in the last two years.
What do you think changed five years ago? Did nature suddenly invent lightning?
As for forest policies, the policies people like to criticize go back decades. What changed is not policy, but temperature and drought. One of the reasons that people don't do controlled burns any more is because the new climate means there is no such thing. Those innocuous fires of the past would grow out of control and torch the state if they happened today.
It's also hard to square the "forest management" scapegoating with the global nature of the recent wildfires. What do Siberia and Greece have in common with the American West? I'm pretty sure it's not forest management.
Also, I'll refer you a US Forest Service document that that says: "Today’s
forests are more spatially uniform, with higher densities of fire-intolerant species and suppressed trees."
https://www.fs.fed.us/projects/hfi/2003/november/documents/forest-structure-wildfire.pdf
When we think about the natural world we often make the mistake of assuming that what we see today in "wild areas" is like it's always been, and that humans have somehow left the uninhabited these landscapes untouched.
For instance, if you were to visit the countryside of southern New England for a fall foliage excursion, you'll see rolling hills covered in deciduous forests of predominantly maple and oak. If you were to go back in time and visit those same places 150 years ago, you would have seen rolling hills used for dairy farming virtually denuded of trees except for small lots set aside for maples ("sugar bushes" for maple syrup) and wood lots for fire wood. But there were very few extant forests left in Connecticut, Massachusetts and Rhode Island during the 19th Century. If you were to visit southern New England 450 years ago, you would see it covered in mostly climax conifer forests, areas denuded by fires set by Native Americans, and other patches of deciduous forest that had grown up in the agricultural spots abandoned by Native Americans. A good book that describes this is Changes in the Land: Indians, Colonists, and the Ecology of New England, by William Cronon...
https://www.amazon.com/gp/product/0809016346/ref=ppx_yo_dt_b_asin_title_o06_s01?ie=UTF8&psc=1
Archaeological evidence now suggests that the Amazon rainforest, before the Europeans arrived, was once home to civilizations with an agricultural base that could have supported tens of millions of people. The Amazon rain forest may have only existed in patches 1,000 years ago. But it would be ironic, indeed, if the current Amazon rainforest is an artifact of European colonial expansion which killed off 80-90 percent of native inhabitants with measles and to a lesser extent smallpox.
No, but about a decade ago PG&E started deploying their (illegal) restarter units. According this report, PG&E was responsible for about 1500 fires between 2012 and 2019.
https://www.businessinsider.com/pge-caused-california-wildfires-safety-measures-2019-10
And the recent 30,000 acre Dixie fire *was* caused by PG&E. At least 5 of the 10 most destructive fires in the past 5 years were linked to PG&E equipment, and PG&E and equipment and/or policies were implicated in the other two. Arson comes up as the next most common cause of wildfires in California.
I've lived in California for nigh on 25 years, and in almost every year of those I've heard about things that have happened that have never happened historically. More rain than ever recorded! Less rain than ever recorded! Highest temperature ever in X! Lowest temperature ever in Y! Biggest/lowest yield of crop A, worst floods in county Z, and so on.
In part I think that's because there's a whole lot of things that can happen, and in part it's because California's history isn't very long, and the part of it that contains detailed records of everything that can happen is even shorter.
If we were talking about something that hadn't happened in the last 100,000 years, and we had good records to confirm it, I'd be impressed. But fires...? Meh. I would need a lot better argument than "we haven't recorded this in the 60-100 years people have been keeping somewhat decent track." California is famous for having big burn seasons every now and then even in its recorded history, and it's clearly been going on for a very long time -- far longer than humans have been building combustion engines -- for there to be the many noted adaptions of Western pines to forest fires, including cones that don't even open until the forest has been burned.
I don't mean in that paragraph to say that climate change should be ignored, only to express my despair in noting that it doesn't matter what our models say; politicians will say whatever helps them, the newpapers will repeat whatever quotes they like best, and people will repeat and believe them.
Be careful, though: Record-setting wildfires are always an annual occurrence, in that every year there's a record-setting wildfire somewhere. Checking https://www.oregon.gov/odf/Documents/fire/odf-century-fire-history-chart.pdf , https://en.wikipedia.org/wiki/List_of_California_wildfires , and https://en.wikipedia.org/wiki/List_of_California_wildfires , I see that there have been a lot of big fires on the west coast in the 2010s, and also that 2020 was bizarre--it's something like ten standard deviations above the recent average in terms of acres burned, which would be too large and sudden to be accounted for by climate change if we could model acres burned with a normal distribution. Probably it /doesn't/ have a normal distribution, but a power-law distribution.
Your second point doesn't make sense to me. Uncertainty in modeling gives you bigger tails, in which both lower and higher risks are enclosed. It doesn't change the expected value. It sounds to me like you want to base policy on the worst-case scenario (which is, in fact, what's happening) rather than on the expected value.
But in any case I agree we should take action immediately, and build more nuclear power plants.
Going by that Wikipedia link, four of the last five years have burned >1.5 mil acres, while only two of the preceding 17 years did. There really does seem to have been a major change in the last couple years where cataclysmic wildfires are now a routine event.
Obviously, it's not like the global temperature suddenly jumped in 2017 (and dipped back down in 2019), but there's also no way you can argue that the recent wildfires are within historical parameters. It's clear that the long term warning trend has led to conditions under which wildfires are much more destructive than before.
How confident are you that the acreage burned over the next 10 years will be similar to the current rate instead of something closer to the historical average?
A Bloomberg article has this chart for acreage burned in US wildfires: https://assets.bwbx.io/images/users/iqjWHBFdfxIU/iISDydT73c1M/v1/-1x-1.png
So it certainly looks like it's been increasing since around 1995. And it makes intuitive sense that warmer weather would dry things out and cause fires.
Likewise, global mean temperatures have been increasing somewhat steadily since about 1910: https://earthobservatory.nasa.gov/ContentFeature/GlobalWarming/images/giss_temperature.png
Still, if that's the extent of the evidence that global warming *caused* the increase in fires, then the evidence isn't that strong. There looks to be about as much correlation between global temperature and wildfires as there is between obesity rates in the US and wildfires.
Once we've established causation, the next question is how much of the wildfires are due to the increase in temperature. How much land would have burned if we hadn't warmed the Earth? Is all the increase in wildfires due to global warming?
How do you know it has caused immense damage today? You know that bad things have happened and people who are concerned with climate change blame them on climate change. People who are concerned that preventing small wildfires and restricting timber harvesting produce big wildfires blame them on that. I expect there are other people blaming them on other things. With or without climate change, rare bad things sometimes happen.
Has there been any notable change in the timber management policies of Siberia in the last couple years?
A "rare bad thing" happening once could be just bad luck. But when it happens year after year and all around the world, you'd have to be willfully obtuse to ignore it.
https://www.nytimes.com/2021/10/06/magazine/laurie-anderson.html
Laurie Anderson is a spectacularly good and weird artist. She is dong a big show at the Hirshhorn in DC. She's 72 and they wanted her to do a retrospective, but she's not interested in going over her past work, so it's a new show, running September 24 to July 31.
Note that a visit could be combined with Worldcon.
She might be of interest for the evolution of art discussion. Her work is avant garde, but it isn't hostile. She's trying to introduce people to non-obvious things, but she isn't punishing them for not seeing them already.
I saw Anderson's Forty-Nine Days in the Bardo which was about pet dog that died.
,
https://fabricworkshopandmuseum.org/artist/laurie-anderson/?doing_wp_cron=1633701319.6193389892578125000000
I'd have sworn I wrote something about it, but I can't find it.
Thing to learn: if you want a really great remembrance after you're dead, be loved by an excellent artist.
Anyway, here are some things I remember. A little statue of the dog which had the cremated ashes worked into the clay and a description of bringing back the smell of wet dog.
A little white statue (maybe a madonna) with a film clip projected on it, giving an illusion of 3D movement. I'm surprised people haven't done more what that technology.
BIG black and white paintings. The only one I remember is a portrait of the dog's face. I think there were others about the confusion of being between lives.
A song from the exhibit: https://www.youtube.com/watch?v=JG8PPLP3ROM
Not something I remember, and I hope the afterlife isn't that challenging.
She turned it into a marvelous movie entitled "Heart of Dog". (Full disclosure: I love Laurie Anderson.)
https://www.youtube.com/watch?v=8PLWVXICQyM
Yeah, she's something very special.
For all the math and physics nerds, a clue from today today's NYT's XWord:
Clue: Obtain a sum via special relativity?
Answer: INHERIT
Not one of their most perversely creative word play clues but it seemed like it might find an audience here.
One more example from today’s Sunday Times XWord.
No tie in to physics. Just one that tickled my love of word play.
This was a themed puzzle with a series of clues being movie titles. The trick is to think of a - sometimes twisted - alternative meaning for the title. Answers are generally caps locked in the solutions.
Clue: Top Gun
ROT13’d Answer: GFUVEGPNAABA
Without the intersecting letters from the down answers there is no way I could have solved this. If someone can come up with the answer without that support they are either really lucky or perhaps clairvoyant.
If you want to try to get the puzzle experience without the intersecting words, I suppose you could randomly decipher the ROT13'd letters one or two at a time.
That seems more like misdirection than a genuine pun, but maybe I'm missing some meaning of "inherit" in the physics sense.
Yeah, it's not a pun. I'd just call it word play. There is no physics meaning in the answer. The way the question is set up sends the solver in that - incorrect -direction with its 'special relativity' phrasing.
As Edward Scizorhands mentions below, the puzzle creator usually give warning of this sort of misdirection by ending the clue with a '?'
FWIW appreciation of this sort of word play is not universal. When I show my wife one of these she gets pretty annoyed, complete with some choice obscenities.
My comment regarding math and physics nerds possibly enjoying the little word game was the clue set up. It *looks* like they are talking about physics, until you have the rug pulled out from under you with the 'aha moment'.
Even though I do enjoy these sorts of twists - big endorphin payoff when I get it - the words 'those bastards' or something similar can come out of my mouth.
Another example from earlier in the week. Warning I'm not going to RO13 the answer cause I'm just demonstrating the technique.
Clue: What jelly rolls are filled with? - Note the ? mark
Answer: ELLS - The words 'jelly rolls' have four occurrence of the letter 'L' . They are filled with ELLS.
If that one annoys you as much as it annoys my wife, then the current NYT XWord is probably not your cup of tea.
No, I enjoy crossword puzzles, and I'm familiar with the clue paradigm. I was just wondering if I was missing something here.
I start to suspect that I am your wife.
I guess it would be help if I paraphrase what my wife says about the meaning of a '?' at the end of a clue:
"It means they messin' with ya!"
First of all SPOILERS
Second of all -- only that clue interests the math and physics nerds, not the answer, right?
Oh no! You haven't done the Times Friday puzzle yet?
Not sure if you're kidding me. I guess I could have ROT13'd the answer.