Hello, everyone. I hope you have had a lovely summer. We ended up scaling back a bit on our regular schedule, doing about half as much formal “schoolwork” as usual and twice as much riding bikes and going to the playground.
Here are some of the books we found particularly useful/enjoyable this summer:
I was looking for a book to introduce simple geometry and shape construction. Instead, I found this delightful history of geometry. It is appropriate for children who understand simple fractions, ratios, and the Pythagorean theorem, but it is not a mathematics textbook and only contains a few equations. (I’m still looking for an introduction to geometry, if anyone has any recommendations.)
This is a new edition of a book originally published in 1965, but its age isn’t really important because geometry hasn’t changed much in the intervening years.
The story begins with geometry in nature–the shapes of trees and flowers, spiderwebs and honeycombs–then develops a speculative account of how early stoneage humans might have become increasingly aware of and attuned to these shapes. Men saw the shapes of the sun and moon in the sky, and might have observed that an ox tied to a pole traced out a similar shape in the dirt.
Then Egyptian surveyors developed right triangles, used for measuring the corner of fields and pyramids. The Mesopotamians developed astronomy, and divided the circle into 360 degrees. Then came the Greeks–clever Thales, mystical Pythagoras, and practical Archimedes. And finally, at the end, Eratosthenes (who used geometry–literally, earth measuring–to measure the circumference of the Earth,) and a few paragraphs about Euclid.
There are many books and workbooks in this series, so you can pick the ones that best suit your child’s ability level. (The “look inside the book” feature is great for judging which level of textbook you want.)
I am sure these books are not everyone’s cup of tea. They may not be yours. But they were what we needed.
My eldest children are fairly different in writing needs, but I do not have time for separate curricula. One is a good speller, the other bad. One has acceptable handwriting, the other awful. One will write independently, the other hates writing and plays dead if I try to get them to write. These books have worked well for everyone. Spelling, handwriting, and general willingness to write have all improved.
Even if you aren’t homeschooling, this book might make a good supplement to your kids’ regular curriculum.
Petri dishes are cheap, agar is easy to make at home (it’s just like making jello,) and kids can learn things like “doorknobs are dirty” and “that’s why mom makes me wash my hands before dinner.”
Just be careful when handling large quantities of bacteria. Even if it’s normal household bacteria that you’re exposed to regularly, you’re not used to it in these quantities. The instructions recommend wearing gloves and safety goggles while handling bacteria and making slides out of them–and besides, kids like dressing up “like scientists” anyway.
Our pattern blocks have been in the family for decades–passed down to me by my grandmother–but the geoboards are a new acquisition. I remember geoboards in elementary school–they sat behind the teacher’s desk and we never actually used them. I didn’t know what, exactly, geoboards were for, so I went ahead and got new workbooks for both them and the pattern blocks.
We are only a few lessons in, but so far I am very pleased with these. We have been talking about angles and measuring the degrees in different shapes with the pattern blocks–360 in a circle, 180 in a triangle, 720 in a hexagon, etc–which dovetails nicely with the geometry reading. The geoboards let us construct and examine a variety of different shapes, like right and equilateral triangles. The lesson plans are easy to use and the kids really enjoy them. Just watch out for rubber bands flying across the room.
Super Source makes workbooks for different grade levels, from K through 6th.
This book introduces Python, and is a nice step up from the Scratch workbooks. You may have to install a couple of programs, like Python and the API spigot, but the book walks you through this and it is not bad at all. There are then step-by-step instructions for making simple programs, along with bonus challenges to work out on your (or your kid’s) own.
The book covers strings, booleans, if statements, loops, etc, in kid-friendly ways. Best for people who already love Minecraft and can type.
Welcome to our final discussion of Auerswald’s The Code Economy. Today we will be finishing the text, chapters 13-15. Please feel free to jump in even if you haven’t read the book.
After a hopefully entertaining digression about Peruvian Poutine and Netflix’s algorithms*, we progress to the discussion of Bitcoin and the Blockchain. Now, I don’t know anything about Bitcoin other than the vague ideas I have picked up by virtue of being a person on the internet, but it was an interesting discussion nonetheless.
Auerswald likens blockchain to an old-fashioned accountant’s ledger; the “blocks” are the rectangles in which a business’s earnings and expenses are recorded. If there is any question about a company’s profits, you can look back at the information recorded in the chain of blocks.
The problem with this system is that there is only one ledger. If the accountant has made a mistake (or worse, a theft,) there is nothing else to compare it to in order to determine the mistake.
In the modern, distributed version, there are many copies of the blockchain. If on most of these copies of the chain, block 22 says -$400, and on one copy it says +$400, we conclude that the one that disagrees is most likely in error. Like the works of Shakespeare, there are so many copies out there that a discrepancy a single copy cannot be claimed to be authoritative; it is the collective body of work that matters.
“Blockchain” is probably going to get used here as a metaphor for “distributed systems of confirming authority” a lot. For example, “Democracy is a blockchain for deciding who gets to rule a country.” Or “science is a blockchain.”
In Rhodes’s “The Making of the Atomic Bomb,” he recounts the process by which something becomes accepted as “true” (or reasonably likely to be true,) in the scientific community. Let’s suppose scientist M is the foremost authority in his field–perhaps organic LEDs. Scientists L and N are doing work that overlaps M’s, and can therefore basically evaluate M’s work and vouch for whether they think it is sound or not. Scientists J, K, O, and P do work that overlaps a lot with L and N and a little with M; they can evaluate M’s work a little and vouch for whether they think L and N are trustworthy. The chain continues down to little cats scientists A and Z, who can’t really evaluate scientist M, but can tell you whether or not they think B and Y’s results are trustworthy.
This community of science has both good and bad. In general, the structure of science has been extremely successful at inventing things like computers, atomic bombs, and penicillin; at times it creates resistance to new ideas just because they are so far outside of the mainstream of what other scientists are doing. For example, Ignaz Semmelweis, a physician, discovered that he could reduce maternal deaths at his hospital from around 10-18% to 2% simply by insisting that obstetricians wash their hands between dissecting cadavers and delivering babies. Unfortunately, the rest of the medical establishment had not yet accepted the Germ Theory of disease and believed that disease was caused by imbalanced humors. Semmelweis’s idea that invisible corpse particles were somehow transferring corpse-ness from dead people to live people seemed absurd, and further, blamed the doctors themselves for the deaths of their patients. Semmelweis’s tragic tail ends with him being stomped to death in an insane asylum. (His mental ill-health was probably induced by a combination of the stress of being rejected by his profession; and syphilis, contracted via charity work delivering babies for destitute prostitutes.)
Luckily for mothers everywhere, medical science eventually caught up with Semmelweis and puerperal fever is no longer a major concern for laboring women. Science, it seems, can correct itself. (We may want to be cautious about being too eager to reject new ideas–especially in cases where there is clearly a lot of room for improvement, like an 18% death rate.)
Niti Aayog is working with Apollo Hospitals and information technology major Oracle on applying blockchain (decentralised) technology in pharmaceutical supply chain management to detect spurious drugs, Chief Executive Officer of NITI Aayog Amitabh Kant said here today.
Addressing a gathering through video-conferencing at the inaugural session of International Blockchain Congress 2018 for which Niti Aayog was a co-host, Kant said the organisation was working on applying the blockchain technology to pressing problems of the country in areas such as land registry, health records and fertiliser subsidy distribution m among others.
Blockchain technology can enable India to find solutions to huge logjams in courts …
With two-thirds of all civil cases pertaining to registration of property or land, the country’s policy think-tank is working with judiciary to find disruptive ways to expedite registrations, mutations and enable a system of smart transactions that is free of corruption and middlemen.
… There are three crore cases currently pending in Indian courts, including 42.5 lakh cases in high courts and 2.6 crore* cases in lower courts. Even if 100 cases are disposed off every hour without sleeping and eating, it would take more than 35 years to catch up, he said. …
On transforming the land registry system using blockchain, Niti Aayog is in advanced stage of implementing proof of concept pilot in Chandigarh to assess its potential to solve the problem of India’s land-based registry system. …
“It’s powerful because it allows multiple parties to collaborate and come to consensus without any need of third party,” he said.
*A crore is an Indian unit equivalent to 10 million.
I probably do not need to review Auerswald’s summary of Bitcoin’s history, as you are probably already well aware of it, but the question of “is Bitcoin real money?” is interesting. In 1875, Jevons, “cofounder of the neoclassical school in economics,” wrote that a material used as money should have the following traits:
“1 Utility and value
6 Stability of value
I am not sure about all of the items on this list; cigarettes and ramen noodles, for example, are used as currency in prisons, even though they are very easy to destroy. It seems like using a currency that you are going to eat would be problematic, yet the pattern recurs over and over in prisons (where perhaps people cannot get their hands on non-consumable goods, or perhaps people simply have no desire for non-consumable ornaments like gold.)
Gold–the “gold standard” of currencies–is a big odd to me, because it has very few practical uses. You can’t eat it. You can’t plant with it, cure parasites with it, or build with it. Lots of people talk about how you’d want a hard currency like gold in the case of societal collapse in which people stop accepting fiat currency, but if zombies were invading, the gas stations had run out of gasoline, and the grocery stores were out of food, I can’t imagine that I’d trade what few precious commodities I had left for a pile of rocks.
People argue that fiat currency is “just paper,” but gold is “just rocks,” and unless you’re a jeweler, the value of either is dependent entirely on your expectation that other people will accept them as currency.
For the past 40 years the world’s currencies have been untethered from gold or any other metal. National “fiat” currencies are nothing more or less than tradeable trust, whose function as currency is based entirely on government-enforced scarcity an verifiability not tethered to its intrinsic usefulness.
I think Auerswald overlooks the role of force in backing fiat currencies. We don’t use Federal Reserve Notes because we trust the government like it’s our best friend from the army who pulled us out of a burning foxhole that one time. We use Federal Reserve Notes because the US government has a lot of guns and bombs to back up its claim that this is real money.
Which means the power of a dollar is dependent on the US government’s ability to enforce that value.
As for Bitcoin:
Bitcoin… satisfies all the criteria for being “money” that William Stanley Jevon set forth… with on exception intrinsic utility and value. That does not mean that Bitcoin will grow in significance as a means of exchange, much less achieve any position of dominance. But with digital transactions via mobile phones–Apple Pay and the like–becoming ever more command the concept of a digital currency not backed by any government gaining rapid acceptance, the prospect of one or another digital currency competing successfully with fiat currencies is not nearly as far-fetched today as it was even three years ago.
The biggest problems I see for digital currencies:
Keeping value–if people decide they won’t accept DogeCoin, then what do you do with all of your DogeCoins?
Ease of entry into the market makes it difficult for any one Coin to retain value
Most people are happy using currencies not associated with illegal activity
The upside to digital currencies is they may be a real blessing for people caught in countries where local fiat currencies are being manipulated all to hell.
Anyway, Auerswald envisions a world in which blockchains (with coins or not) enable a world of peer-to-peer authentication and transactions:
By their very structure, Peer-to-peer platforms start out being distributed. The challenge is how to organize all of the energy contained in such networks so that people are rewarded fairly for their contributions. …Blockchain-based systems for governing peer0to0eer networks hold the promise–so far unrealized–of incorporating the best features of markets when it comes to rewarding contribution and of organizations when it comes to keeping track of reputations.
In other words, in areas where economies are held back because the local governments do a bad job of enforcing contracts and securing property rights, “blockchain”-like algorithms may be able to step into the gap and provided an accepted, distributed, alternative system of enforcement and authentication.
(This is the point where I start ranting to anyone within earshot about communists not recognizing the necessity of secure property rights so that people can turn their property into capital in order to start businesses. Without that seed money to start a business, you can’t get started. Even something simple, like driving for Uber, requires a car to start with, and cars cost money. If you can’t depend on having money tomorrow because all of your property just got confiscated, or you can’t depend on having a car tomorrow because private property is for bourgeois scum, then you can’t get a job driving for Uber. If no one can convert property to capital and thus to businesses, then you don’t get business and you have no economy and people suffer.
Communists see that some people have property that they can convert to capital and other people don’t have said capital, and their solution is to just take everybody’s stuff away and declare the problem fixed, when what they really want is for everyone to have enough basic property and capital to be able to start their own business.]
But back to Auerswald:
Earlier… I alluded to the significant advance in democracy, science, and financial systems that occurred simultaneously during …the Age of Enlightenment. That systems of governance, inquiry, and economics should have advanced all at the same time… is no coincidence at all. Each of these foundational developments in human social evolution is, at its core, an algorithm for authentication and verification. …
It is only because of the disciplinary fragmentation of inquiry that has occurred in the past century that we do not immediately perceive in the evolved historical record the patterns connecting systems of authentication and verification in politics, science, and economics as they have jointly evolved. … Illuminating those patterns has been the point of this book.
Chapter 14 begins with a history of Burning Man, which the author defends thus:
Still, it makes for an interesting case study in the building of cities (and why laws get enacted): Like everything about Black Rock City, the layout is the product of both planning and evolution. Cities are what physicists refer to as dissipative structures: highly complex organisms worse existence depend on a constant throughput of energy. If you were to close down all bridges and tunnels into New your City … grocery stores would have only a three-day supply of food. The same is generally true of a city’s other energy requirements. All cities are temporary, and they survive only because we feed them. …
The evolution of Black Rock is for urbanists what a real-life Jurassic Park would be for a Paleontologist. We really have no idea what the experience of living in humanity’s first cities might have been–whether Uruk in Mesopotamia or Catalhoyuk in Anatolia. And yet all cities also have elements of planning. Where Black Rock City has its Larry Harvey, London had its Robert Hooke and Washington, D.C., had its Pierre L’Enfant. Each had a notion of how to bound a space, build symmetry and flow, and in so doing provide a platform where the human experience can unfold.
I have a somewhat dim view of “Burning Man” as a communist utopia that’s only open to rich people, filled with environmentalist hippies leaving an enormous carbon footprint in order to get high with a close-knit community of 70,000 other people, but maybe my sight is obscured from the outside.
The question remains, though: will code be a blessing, or a curse? What happens to employment as “traditional” jobs disappear? Will blockchain and other new platforms and technologies make us freer, or simply find new ways to control us?
The advance of code reduces individual power and autonomy while it increases individual capabilities and freedom.
So far, Auerswald points out, there has been good reason to be optimistic:
In 1990, a staggeringly high 43 percent of people in the “developing world,” approximately 1.9 billion people, lived in extreme poverty. By 2010, that number had fallen to 21 percent. …
For the past two centuries, the vehicle for that progress has been the continual capacity of economies to generate more and better jobs. … “Gallup has discovered that having a good job is now the great global dream … ‘A good job’ is now more important than having a family, more compelling than democracy and freedom, religion, peace and so on… Stimulating job growth is the new currency of all leaders because if you don’t deliver on it you will experience instability, brain drain, sometimes revolution…
There is something concerning about this, though. “Jobs creation” is now widely agreed to be in the hands of national leaders, not individuals. Ordinary people are no longer seen as drivers of innovation. People can start businesses, of course, but whether those businesses survive or fail depends on the government; for the average person, jobs are no longer created by human ingenuity but awarded by an opaque power structure.
Thus the liberal claim that “structural racism” (rather than “individual racism”) is the real cause of continued black impoverishment and high unemployment rates. In a world where employment is granted or withheld by the powerful based on whether or not they like you, not based on your own innate ability to make your own economic contribution to the world, then it is imperative to make sure that the powerful see it as important to employ people like you.
It is, in sum, an admission of the powerlessness of the individual.
Still, Auerswald is hopeful that with the rise of the Peer-to-Peer economy and end of traditional factory work, not only will work be more interesting (as boring, repetitive jobs are most easily automated,) but also that people will no longer be dependent on the whims of a small set of powerful people for access to jobs.
I think he underestimates how useful it is to have steady, long-term employment and how difficult it is for individuals to compete against established corporations that have much larger economies of scale and access to far more relevant data than they do. Take, for example, YouTube vs. Netflix. Netflix can use its troves of data to determine which kinds of shows customers would like to watch more of, then hire people to make those shows. This is pretty nice work if you can get it. YouTube, of course, just lets pretty much anyone put up any video they want, and most of the videos are probably pretty dull, but a few YouTubers put up quality material and an even smaller few actually make a decent amount of money. YouTuber PewDiePie, for example, holds the record at 61+ million subscribers, which has earned him $124 million. But most people who try to become YouTube stars do not become PewDiePie; most earn very little. And why should they, when most of them are amateurs low-budget amateurs with no data on what audiences are interested in going up against other TV options like Orange is the New Black, Breaking Bad, and yes, PewDs himself?
I have a friend who is a very talented amateur clothing designer and dressmaker. I have encouraged her to open a shop on Etsy and try sell some of her creations, but can she really compete with Walmart, The Gap, or Nordstrom? Big Clothing has a massive lead in terms of factories mass-producing clothes for sale. (Her only hope would be to extremely upscale–wedding dresses, movie costumes, etc.)
So what does the future hold?
In the next round of digital disruption, tasks that can be automated (the “high-volume, low-price” option resulting from ongoing code-driven bifurcations…) will yield only small dividends for most people. The exception is the relatively small number of people who will maintain the platforms on which such tasks are performed…
The promising pathway for inclusive well-being is humanized work (the “low-volume, high-price” pathway resulting from ongoing code-driven bifurcations…) this pathway includes everything about value creation that is differentiated, personal, and human.
In his Conclusion, Auerswald writes:
To be human is to think critically. To collaborate, to Communicate. To be creative. What we call “the economy’ is one extension of these activities. It is the domain in which we develop and advance code.
But the singularity approaches:
We are not at the center of our cognitive universe. Our own creations are eclipsing us.
For each of us, redefining work requires nothing less than redefining identity. This is because production is not something human beings do just to consume. In fact, the opposite is true. We are living beings. We consume in order to produce.
Well, that’s the end of the book. I hope you have enjoyed it as much as I have. What do you think the future holds? Where do you think code is taking the economy? What are the best–and worst–opportunities for growth? And what (if anything) should we read next?
*An Aside On Netflix and the use of algorithms to produce movies/TV:
…consider the fate of two films that premiered the same night at the 2015 Sundance Film Festival. … One of these films, What Happened, Miss Simone? was a documentary about singer and civil rights icon Nina Simone. That film was funded by Netflix, whose corporate decision to back the film was based in part on insights algorithmically gleaned from the vast trove of data it has collected on users of its streaming video and movie rental services. The second film was a comedy titled The Bronze, which featured television star Melissa Rauch as a vulgar gymnast. The Bronze was produced by Duplass Brothers production and privately financed by “a few wealthy individual” whose decision to back the film was presumably not based on complex impersonal algorithms but rather, as has been the Hollywood norm, on business intuition.
I’ve often wondered why so many terrible movies get made.
A documentary about a Civil Rights leader might not be everyone’s cup of tea (people like to say they watch intellectual movies more than they actually do,) but plenty of people will at least abstractly like it. By contrast, a “vulgar gymnast” is not an interesting premise for a movie. Vulgarity can be funny when it is contrasted with something typically not vulgar–eg, “A vulgar mobster and a pious nun team up to save an orphanage,” or even “A vulgar nun and pious mobster…” The humor lies in the contrast between purity and vulgarity. But gymnasts aren’t known for being particularly pure or vulgar–they’re neutral–so there’s no contrast in this scenario. A vulgar gymnast doesn’t sound funny, it sounds rude and unpleasant. And this is the one sentences summary chosen to represent the movie? Not a good sign.
As you might have guessed already, What Happened, Miss Simone, did very well, and The Bronze was a bomb. It has terrible reviews on IMDB and Rotten Tomatoes. As folks have put it, it’s just not funny.
Davidowitz notes in Everybody Lies that the industries most ripe for “big data”fication are the ones where the current data is not very good. Industries where people work more on intuition than analysis. For example, the choice of horses in horse racing, until recently, was based on pedigree and intuition–what experienced horse people thought seemed promising in a foal. There was a lot of room in horse racing for quantification and analysis–and the guy who started using mobile x-ray machines to measure horse’s heart and lung sizes was able to make significantly better predictions than people who just looked at the horses’s outsides. By contrast, hedge funds have already put significant effort into quantifying what the prices of different stocks are going to do, and so it is very hard to do better data analysis than they already are.
The selection of movies and TV pilots to fund fall more into the “racing horses picked by intuition” category than the “extremely quantified hedge funds” category, which means there’s lots of room for improvement for anyone who can get good data on the subject.
Incidentally, “In 2015… Netflix accounted for almost 37 percent of all downstream internet traffic in North America during peak evening hours.”
I have yet to find any “science kits” that actually teach science–most are just science-themed toys. There’s nothing wrong with that, but don’t expect your kid to re-derive the principles of chemistry via a baking soda volcano.
Smaller kids aren’t ready for the kind of thinking required for actual scientific research, but they can still learn plenty of science the mundane way: by reading. So here are some of our favorite science books/activities:
We did geology over the winter, centered around Rocks, Rivers, and the Changing Earth. It’s a lovely book (reading level about second grade?) with instructions for many simple experiments (eg, put rocks, sand, water in a glass jar and carefully shake/swirl to observe the effects of different water speeds on riverbanks) and handily complements any nature walks, rock collecting trip, or expeditions to the seashore.
WARNING: This book was published before plate tectonics became widely accepted and so has a confused chapter or two on how mountains form. SKIP THIS CHAPTER.
We also tried making polished stones in a rock tumbler (verdict: not worth the cost.)
I like to read this with a globe and children’s atlas at hand, so I can easily demonstrate things like latitude and longitude, distances, and different map projections.
With spring’s arrival we also began a study of plants and insects.
If you’ve never started your own plants from seed, any common crop seeds sold at the store–beans, peas, corn, squash, and most flowers–will sprout quickly and easily. If you want to keep your plants indoors, I recommend you get a bag of dirt at the garden center. This dirt is supposed to be “clean”; the dirt found outside in your yard is full of bugs that you probably weren’t intending on studying in your living room.
Speaking of bugs, we bought the “raise your own ladybugs” and butterflies kits, but I don’t recommend these as real caterpillars are nowhere near as cute and interesting as the very hungry one in the story. I think you’re better off just collecting ladybugs in the wild and reading about them at home.
Super Science: Matter Matters is a fabulous pop-up/lift-the-flap book about chemistry. We were very lucky to receive this as a birthday gift. (Birthday hint: the homeschooling families in your life would always like more books.) The book is a little fragile, so not appropriate for younger children who might pull too hard on the tabs, but great for everyone else.
Note: “Memes” on this blog is used as it is in the field of memetics, representing units of ideas that are passed from person to person, not in the sense of “funny cat pictures on the internet.”
“Mitochondrial memes” are memes that are passed vertically from parent to child, like “it’s important to eat your dinner before desert” or “brush your teeth twice a day or your teeth will rot out.”
“Meme viruses” (I try to avoid the confusing phrase, “viral memes,”) are memes that are transmitted horizontally through society, like chain letters and TV news.
I’ve spent a fair amount of time warning about some of the potential negative results of meme viruses, but today I’d like to discuss one of their greatest strengths: you can transmit them to other people without using them yourself.
Let’s start with genetics. It is very easy to quickly evolve in a particular direction if a variety of relevant traits already exist in a population. For example, humans already vary in height, so if you wanted to, say, make everyone on Earth shorter, you would just have to stop all of the tall people from reproducing. The short people would create the next generation, and it would be short.
But getting the adult human height below 3″ tall requires not just existing, normal human height variation, but exploiting random mutations. These are rare and the people who have them normally incur huge reductions in fitness, as they often have problems with bone growth, intelligence, and giving birth.
Most random mutations simply result in an organism’s death. Very few are useful, and those that are have to beat out all of the other local genetic combinations to actually stick around.
Suppose you happen to be born with a very lucky genetic trait: a rare mutation that lets you survive more easily in an arctic environment.
But you were born in Sudan.
Your genetic trait could be really useful if you could somehow give it away to someone in Siberia, but no, you are stuck in Sudan and you are really hot all of the time and then you die of heatstroke.
With the evolution of complex thought, humans (near alone among animals) developed the ability to go beyond mere genetic abilities, instincts, and impulses, and impart stores of knowledge to the next generation. Humanity has been accumulating mitochondrial memes for millions of years, ever since the first human showed another human how to wield fire and create stone tools. (Note: the use of fire and stone tools predates the emergence of homo Sapiens by a long while, but not the Homo genus.)
But mitochondrial memes, to get passed on, need to offer some immediate benefit to their holders. Humans are smart enough–and the utility of information unpredictable enough–that we can hold some not obviously useful or absurd ideas, but the bulk of our efforts have to go toward information that helps us survive.
(By definition, mitochondrial memes aren’t written down; they have to be remembered.)
If an idea doesn’t offer some benefit to its holder, it is likely to be quickly forgotten–even if it could be very useful to someone else.
Suppose one day you happen to have a brilliant new idea for how to keep warm in a very cold environment–but you live in Sudan. If you can’t tell your idea to anyone who lives somewhere cold, your idea will never be useful. It will die with you.
But introduce writing, and ideas of no use to their holder can be recorded and transmitted to people who can use them. For example, in 1502, Leonardo da Vinci designed a 720-foot (220 m) bridge for Ottoman SultanBeyazid II of Constantinople. The sultan never built Leonardo’s bridge, but in 2001, a bridge based on his design was finally built in Norway. Leonardo’s ideas for flying machines, while also not immediately useful, inspired generations of future engineers.
Viral memes don’t have to be immediately useful to stick around. They can be written down, tucked into a book, and picked up again a hundred years later and a thousand miles away by someone who can use them. A person living in Sudan can invent a better way to stay warm, write it down, and send it to someone in Siberia–and someone in Siberia can invent a better way to stay cool, write it down, and send it back.
Many modern scientific and technological advances are based on the contributions of not one or two or ten inventors, but thousands, each contributing their unpredictable part to the overall whole. Electricity, for example, was a mere curiosity when Thales of Miletus wrote about effects of rubbing amber to produce static electricity (the word “electricity” is actually derived from the Greek for “amber”;) between 1600 and 1800, scientists began studying electricity in a more systematic way, but it still wasn’t useful. It was only with the invention of the telegraph from many different electrical parts and systems, (first working model, 1816; first telegram sent in the US, 1838;) that electricity became useful. With the invention of electric lights and the electrical grids necessary to power them (1870s and 80s,) electricity moved into people’s homes.
The advent of meme viruses has thus given humanity two gifts: 1. People can use technology like books and the internet to store more information than we can naturally, like external hard-drives for our brains; and 2. we can preserve and transmit ideas that aren’t immediately useful to ourselves to people who can use them.
The other day on Twitter, Nick B. Steves challenged me to find data supporting or refuting his assertion that Nerds vs. Jocks is a false stereotype, invented around 1975. Of course, we HBDers have a saying–“all stereotypes are true,” even the ones about us–but let’s investigate Nick’s claim and see where it leads us.
(NOTE: If you have relevant data, I’d love to see it.)
Unfortunately, terms like “nerd,” “jock,” and “chad” are not all that well defined. Certainly if we define “jock” as “athletic but not smart” and nerd as “smart but not athletic,” then these are clearly separate categories. But what if there’s a much bigger group of people who are smart and athletic?
Or what if we are defining “nerd” and “jock” too narrowly? Wikipedia defines nerd as, “a person seen as overly intellectual, obsessive, or lacking social skills.” I recall a study–which I cannot find right now–which found that nerds had, overall, lower-than-average IQs, but that study included people who were obsessive about things like comic books, not just people who majored in STEM. Similarly, should we define “jock” only as people who are good at sports, or do passionate sports fans count?
For the sake of this post, I will define “nerd” as “people with high math/science abilities” and “jock” as “people with high athletic abilities,” leaving the matter of social skills undefined. (People who merely like video games or watch sports, therefore, do not count.)
Nick is correct on one count: according to Wikipedia, although the word “nerd” has been around since 1951, it was popularized during the 70s by the sitcom Happy Days. However, Wikipedia also notes that:
An alternate spelling, as nurd or gnurd, also began to appear in the mid-1960s or early 1970s. Author Philip K. Dick claimed to have coined the nurd spelling in 1973, but its first recorded use appeared in a 1965 student publication at Rensselaer Polytechnic Institute.Oral tradition there holds that the word is derived from knurd (drunk spelled backward), which was used to describe people who studied rather than partied. The term gnurd (spelled with the “g”) was in use at the Massachusetts Institute of Technology by 1965. The term nurd was also in use at the Massachusetts Institute of Technology as early as 1971 but was used in the context for the proper name of a fictional character in a satirical “news” article.
suggesting that the word was already common among nerds themselves before it was picked up by TV.
Terman’s goal was to disprove the then-current belief that gifted children were sickly, socially inept, and not well-rounded.
This belief was especially popular in a little nation known as Germany, where it inspired people to take schoolchildren on long hikes in the woods to keep them fit and the mass-extermination of Jews, who were believed to be muddying the German genepool with their weak, sickly, high-IQ genes (and nefariously trying to marry strong, healthy German in order to replenish their own defective stock.) It didn’t help that German Jews were both high-IQ and beset by a number of illnesses (probably related to high rates of consanguinity,) but then again, the Gypsies are beset by even more debilitating illnesses, but no one blames this on all of the fresh air and exercise afforded by their highly mobile lifestyles.
(Just to be thorough, though, the Nazis also exterminated the Gypsies and Hans Asperger’s subjects, despite Asperger’s insistence that they were very clever children who could probably be of great use to the German war effort via code breaking and the like.)
The results of Terman’s study are strongly in Nick’s favor. According to Psychology Today’s account:
His final group of “Termites” averaged a whopping IQ of 151. Following-up his group 35-years later, his gifted group at mid-life definitely seemed to conform to his expectations. They were taller, healthier, physically better developed, and socially adept (dispelling the myth at the time of high-IQ awkward nerds).
…the first volume of the study reported data on the children’s family, educational progress, special abilities, interests, play, and personality. He also examined the children’s racial and ethnic heritage. Terman was a proponent of eugenics, although not as radical as many of his contemporary social Darwinists, and believed that intelligence testing could be used as a positive tool to shape society.
Based on data collected in 1921–22, Terman concluded that gifted children suffered no more health problems than normal for their age, save a little more myopia than average. He also found that the children were usually social, were well-adjusted, did better in school, and were even taller than average. A follow-up performed in 1923–1924 found that the children had maintained their high IQs and were still above average overall as a group.
Of course, we can go back even further than Terman–in the early 1800s, allergies like hay fever were associated with the nobility, who of course did not do much vigorous work in the fields.
My impression, based on studies I’ve seen previously, is that athleticism and IQ are positively correlated. That is, smarter people tend to be more athletic, and more athletic people tend to be smarter. There’s a very obvious reason for this: our brains are part of our bodies, people with healthier bodies therefore also have healthier brains, and healthier brains tend to work better.
At the very bottom of the IQ distribution, mentally retarded people tend to also be clumsy, flacid, or lacking good muscle tone. The same genes (or environmental conditions) that make children have terrible health/developmental problems often also affect their brain growth, and conditions that affect their brains also affect their bodies. As we progress from low to average to above-average IQ, we encounter increasingly healthy people.
In most smart people, high-IQ doesn’t seem to be a random fluke, a genetic error, nor fitness reducing: in a genetic study of children with exceptionally high IQs, researchers failed to find many genes that specifically endowed the children with genius, but found instead a fortuitous absence of deleterious genes that knock a few points off the rest of us. The same genes that have a negative effect on the nerves and proteins in your brain probably also have a deleterious effect on the nerves and proteins throughout the rest of your body.
Controlling for age, physical maturity, and mother’s education, a significant curvilinear relationship between intelligence and coital status was demonstrated; adolescents at the upper and lower ends of the intelligence distribution were less likely to have sex. Higher intelligence was also associated with postponement of the initiation of the full range of partnered sexual activities. … Higher intelligence operates as a protective factor against early sexual activity during adolescence, and lower intelligence, to a point, is a risk factor.
Here we see the issue plainly: males at 120 and 130 IQ are less likely to get laid than clinically retarded men in 70s and 60s. The right side of the graph are “nerds”, the left side, “jocks.” Of course, the high-IQ females are even less likely to get laid than the high-IQ males, but males tend to judge themselves against other men, not women, when it comes to dating success. Since the low-IQ females are much less likely to get laid than the low-IQ males, this implies that most of these “popular” guys are dating girls who are smarter than themselves–a fact not lost on the nerds, who would also like to date those girls.
In 2001, the MIT/Wellesley magazine Counterpart (Wellesley is MIT’s “sister school” and the two campuses allow cross-enrollment in each other’s courses) published a sex survey that provides a more detailed picture of nerd virginity:
I’m guessing that computer scientists invented polyamory, and neuroscientists are the chads of STEM. The results are otherwise pretty predictable.
Unfortunately, Counterpoint appears to be defunct due to lack of funding/interest and I can no longer find the original survey, but here is Jason Malloy’s summary from Gene Expression:
By the age of 19, 80% of US males and 75% of women have lost their virginity, and 87% of college students have had sex. But this number appears to be much lower at elite (i.e. more intelligent) colleges. According to the article, only 56% of Princeton undergraduates have had intercourse. At Harvard 59% of the undergraduates are non-virgins, and at MIT, only a slight majority, 51%, have had intercourse. Further, only 65% of MIT graduate students have had sex.
The student surveys at MIT and Wellesley also compared virginity by academic major. The chart for Wellesley displayed below shows that 0% of studio art majors were virgins, but 72% of biology majors were virgins, and 83% of biochem and math majors were virgins! Similarly, at MIT 20% of ‘humanities’ majors were virgins, but 73% of biology majors. (Apparently those most likely to read Darwin are also the least Darwinian!)
How Rolling Stone-ish are the few lucky souls who are doing the horizontal mambo? Well, not very. Considering all the non-virgins on campus, 41% of Wellesley and 32% of MIT students have only had one partner (figure 5). It seems that many Wellesley and MIT students are comfortingly monogamous. Only 9% of those who have gotten it on at MIT have been with more than 10 people and the number is 7% at Wellesley.
Someone needs to find the original study and PUT IT BACK ON THE INTERNET.
But this lack of early sexual success seems to translate into long-term marital happiness, once nerds find “the one.”Lex Fridman’s Divorce Rates by Profession offers a thorough list. The average divorce rate was 16.35%, with a high of 43% (Dancers) and a low of 0% (“Media and communication equipment workers.”)
I’m not sure exactly what all of these jobs are nor exactly which ones should count as STEM (veterinarian? anthropologists?) nor do I know how many people are employed in each field, but I count 49 STEM professions that have lower than average divorce rates (including computer scientists, economists, mathematical science, statisticians, engineers, biologists, chemists, aerospace engineers, astronomers and physicists, physicians, and nuclear engineers,) and only 23 with higher than average divorce rates (including electricians, water treatment plant operators, radio and telecommunication installers, broadcast engineers, and similar professions.) The purer sciences obviously had lower rates than the more practical applied tech fields.
The big outliers were mathematicians (19.15%), psychologists (19.26%), and sociologists (23.53%), though I’m not sure they count (if so, there were only 22 professions with higher than average divorce rates.)
I’m not sure which professions count as “jock” or “chad,” but athletes had lower than average rates of divorce (14.05%) as did firefighters, soldiers, and farmers. Financial examiners, hunters, and dancers, (presumably an athletic female occupation) however, had very high rates of divorce.
According to the survey recently taken by the “infidelity dating website,” Victoria Milan, individuals working in the finance field, such as brokers, bankers, and analysts, are more likely to cheat than those in any other profession. However, following those in finance comes those in the aviation field, healthcare, business, and sports.
With the exception of healthcare and maybe aviation, these are pretty typical Chad occupations, not STEM.
The Mirror has a similar list of jobs where people are most and least likely to be married. Most likely: Dentist, Chief Executive, Sales Engineer, Physician, Podiatrist, Optometrist, Farm product buyer, Precision grinder, Religious worker, Tool and die maker.
Least likely: Paper-hanger, Drilling machine operator, Knitter textile operator, Forge operator, Mail handler, Science technician, Practical nurse, Social welfare clerk, Winding machine operative, Postal clerk.
I struggled to find data on male fertility by profession/education/IQ, but there’s plenty on female fertility, eg the deceptively titled High-Fliers have more Babies:
…American women without any form of high-school diploma have a fertility rate of 2.24 children. Among women with a high-school diploma the fertility rate falls to 2.09 and for women with some form of college education it drops to 1.78.
However, among women with college degrees, the economists found the fertility rate rises to 1.88 and among women with advanced degrees to 1.96. In 1980 women who had studied for 16 years or more had a fertility rate of just 1.2.
As the economists prosaically explain: “The relationship between fertility and women’s education in the US has recently become U-shaped.”
Here is another article about the difference in fertility rates between high and low-IQ women.
But female fertility and male fertility may not be the same–I recall data elsewhere indicating that high-IQ men have more children than low IQ men, which implies those men are having their children with low-IQ women. (For example, while Bill and Hillary seem about matched on IQ, and have only one child, Melania Trump does not seem as intelligent as Trump, who has five children.)
Of the 1,508,874 children born in 1920 in the birth registration area of the United states, occupations of fathers are stated for … 96.9%… The average number of children ever born to the present wives of these occupied fathers is 3.3 and the average number of children living 2.9.
The average number of children ever born ranges from 4.6 for foremen, overseers, and inspectors engaged in the extraction of minerals to 1.8 for soldiers, sailors, and marines. Both of these extreme averages are easily explained, for soldier, sailors and marines are usually young, while such foremen, overseers, and inspectors are usually in middle life. For many occupations, however, the ages of the fathers are presumably about the same and differences shown indicate real differences in the size of families. For example, the low figure for dentists, (2), architects, (2.1), and artists, sculptors, and teachers of art (2.2) are in striking contrast with the figure for mine operatives (4.3), quarry operatives (4.1) bootblacks, and brick and stone masons (each 3.9). …
As a rule the occupations credited with the highest number of children born are also credited with the highest number of children living, the highest number of children living appearing for foremen, overseers, and inspectors engaged in the extraction of minerals (3.9) and for steam and street railroad foremen and overseer (3.8), while if we exclude groups plainly affected by the age of fathers, the highest number of children living appear for mine and quarry operatives (each 3.6).
Obviously the job market was very different in 1920–no one was majoring in computer science. Perhaps some of those folks who became mine and quarry operatives back then would become engineers today–or perhaps not. Here are the average numbers of surviving children for the most obviously STEM professions (remember average for 1920 was 2.9):
The Journal-Constitution studied 54 public universities, “including the members of the six major Bowl Championship Series conferences and other schools whose teams finished the 2007-08 season ranked among the football or men’s basketball top 25.”…
Football players average 220 points lower on the SAT than their classmates. Men’s basketball was 227 points lower.
University of Florida won the prize for biggest gap between football players and the student body, with players scoring 346 points lower than their peers.
Georgia Tech had the nation’s best average SAT score for football players, 1028 of a possible 1600, and best average high school GPA, 3.39 of a possible 4.0. But because its student body is apparently very smart, Tech’s football players still scored 315 SAT points lower than their classmates.
UCLA, which has won more NCAA championships in all sports than any other school, had the biggest gap between the average SAT scores of athletes in all sports and its overall student body, at 247 points.
From the original article, which no longer seems to be up on the Journal-Constitution website:
All 53 schools for which football SAT scores were available had at least an 88-point gap between team members’ average score and the average for the student body. …
Football players performed 115 points worse on the SAT than male athletes in other sports.
The differences between athletes’ and non-athletes’ SAT scores were less than half as big for women (73 points) as for men (170).
Many schools routinely used a special admissions process to admit athletes who did not meet the normal entrance requirements. … At Georgia, for instance, 73.5 percent of athletes were special admits compared with 6.6 percent of the student body as a whole.
On the other hand, as Discover Magazine discusses in “The Brain: Why Athletes are Geniuses,” athletic tasks–like catching a fly ball or slapping a hockey puck–require exceptionally fast and accurate brain signals to trigger the correct muscle movements.
Ryan Stegal studied the GPAs of highschool student athletes vs. non-athletes and found that the athletes had higher average GPAs than the non-athletes, but he also notes that the athletes were required to meet certain minimum GPA requirements in order to play.
But within athletics, it looks like the smarter athletes perform better than dumber ones, which is why the NFL uses the Wonderlic Intelligence Test:
NFL draft picks have taken the Wonderlic test for years because team owners need to know if their million dollar player has the cognitive skills to be a star on the field.
What does the NFL know about hiring that most companies don’t? They know that regardless of the position, proof of intelligence plays a profound role in the success of every individual on the team. It’s not enough to have physical ability. The coaches understand that players have to be smart and think quickly to succeed on the field, and the closer they are to the ball the smarter they need to be. That’s why, every potential draft pick takes the Wonderlic Personnel Test at the combine to prove he does–or doesn’t—have the brains to win the game. …
The first use of the WPT in the NFL was by Tom Landry of the Dallas Cowboys in the early 70s, who took a scientific approach to finding players. He believed players who could use their minds where it counted had a strategic advantage over the other teams. He was right, and the test has been used at the combine ever since.
For the NFL, years of testing shows that the higher a player scores on the Wonderlic, the more likely he is to be in the starting lineup—for any position. “There is no other reasonable explanation for the difference in test scores between starting players and those that sit on the bench,” Callans says. “Intelligence plays a role in how well they play the game.”
A large study conducted at the Sahlgrenska Academy and Sahlgrenska University Hospital in Gothenburg, Sweden, reveals that young adults who regularly exercise have higher IQ scores and are more likely to go on to university.
The study was published in the Proceedings of the National Academy of Sciences (PNAS), and involved more than 1.2 million Swedish men. The men were performing military service and were born between the years 1950 and 1976. Both their physical and IQ test scores were reviewed by the research team. …
The researchers also looked at data for twins and determined that primarily environmental factors are responsible for the association between IQ and fitness, and not genetic makeup. “We have also shown that those youngsters who improve their physical fitness between the ages of 15 and 18 increase their cognitive performance.”…
I have seen similar studies before, some involving mice and some, IIRC, the elderly. It appears that exercise is probably good for you.
I have a few more studies I’d like to mention quickly before moving on to discussion.
Overall, it looks like smarter people are more athletic, more athletic people are smarter, smarter athletes are better athletes, and exercise may make you smarter. For most people, the nerd/jock dichotomy is wrong.
However, there is very little overlap at the very highest end of the athletic and intelligence curves–most college (and thus professional) athletes are less intelligent than the average college student, and most college students are less athletic than the average college (and professional) athlete.
Additionally, while people with STEM degrees make excellent spouses (except for mathematicians, apparently,) their reproductive success is below average: they have sex later than their peers and, as far as the data I’ve been able to find shows, have fewer children.
Even if there is a large overlap between smart people and athletes, they are still separate categories selecting for different things: a cripple can still be a genius, but can’t play football; a dumb person can play sports, but not do well at math. Stephen Hawking can barely move, but he’s still one of the smartest people in the world. So the set of all smart people will always include more “stereotypical nerds” than the set of all athletes, and the set of all athletes will always include more “stereotypical jocks” than the set of all smart people.
In my experience, nerds aren’t socially awkward (aside from their shyness around women.) The myth that they are stems from the fact that they have different interests and communicate in a different way than non-nerds. Let nerds talk to other nerds, and they are perfectly normal, communicative, socially functional people. Put them in a room full of non-nerds, and suddenly the nerds are “awkward.”
Unfortunately, the vast majority of people are not nerds, so many nerds have to spend the majority of their time in the company of lots of people who are very different than themselves. By contrast, very few people of normal IQ and interests ever have to spend time surrounded by the very small population of nerds. If you did put them in a room full of nerds, however, you’d find that suddenly they don’t fit in. The perception that nerds are socially awkward is therefore just normie bias.
Why did the nerd/jock dichotomy become so popular in the 70s? Probably in part because science and technology were really taking off as fields normal people could aspire to major in, man had just landed on the moon and the Intel 4004 was released in 1971. Very few people went to college or were employed in sciences back in 1920; by 1970, colleges were everywhere and science was booming.
And at the same time, colleges and highschools were ramping up their athletics programs. I’d wager that the average school in the 1800s had neither PE nor athletics of any sort. To find those, you’d probably have to attend private academies like Andover or Exeter. By the 70s, though, schools were taking their athletics programs–even athletic recruitment–seriously.
How strong you felt the dichotomy probably depends on the nature of your school. I have attended schools where all of the students were fairly smart and there was no anti-nerd sentiment, and I have attended schools where my classmates were fiercely anti-nerd and made sure I knew it.
But the dichotomy predates the terminology. Take Superman, first 1938. His disguise is a pair of glasses, because no one can believe that the bookish, mild-mannered, Clark Kent is actually the super-strong Superman. Batman is based on the character of El Zorro, created in 1919. Zorro is an effete, weak, foppish nobleman by day and a dashing, sword-fighting hero of the poor by night. Of course these characters are both smart and athletic, but their disguises only work because others do not expect them to be. As fantasies, the characters are powerful because they provide a vehicle for our own desires: for our everyday normal failings to be just a cover for how secretly amazing we are.
But for the most part, most smart people are perfectly fit, healthy, and coordinated–even the ones who like math.
We had a lovely, windy day, so we grabbed the kites, invited the neighbors, and headed out to the park.
Homeschooling does put additional responsibility on the parents to help their kids socialize. That doesn’t mean homeschooled kids are necessarily at a disadvantage viz their typically-schooled peers when it comes to comes to socializing (I went to regular school and still managed to be terribly socialized;) it’s just one more thing homeschooling parents have to keep in mind. So I am glad that we’ve had the good luck recently to make several friends in the neighborhood.
I’ve been looking for good, educational YouTube channels. Now I haven’t watched every video on these channels and I make no guarantees, but they seem good so far:
The Usborne Times Tables Activity Book is a rare find: a book that actually makes multiplication vaguely fun. Luckily there’s no one, set age when kids need to learn their multiplication tables–so multiple kids can practice their tables together.
In math we’ve also been working with number lines, concept like infinity (countable and uncountable,) infinitesimals, division, square roots, imaginary numbers, multi-digit addition and subtraction, graphing points and lines on the coordinate plane, and simple functions like Y=X^2. (Any kid who has learned addition, subtraction, multiplication and division can plot simple functions.)
If you’re looking for board game to play with elementary-aged kids, Bejeweled Blitz is actually pretty good. Two players compete to place tiles on the board to match 3 (or more) gems, in a row or up and down. (A clever play can thus complete two rows at once.) We play with slightly modified rules. (Note: this game is actually pretty hard for people who struggle with rotating objects in their heads.)
Picture Sudoku is fun for little kids (and probably comes in whatever cartoon characters you like,) while KenKen and magic squares and the like are good for older kids (I always loved logic puzzles when I was a kid, so I’d like to get a book of those.)
I’ve found a website called Memrise which seems good for learning foreign languages if you don’t have access to a tutor or know somene who speaks the language you want to learn. They probably have an app for phones or tablets, so kids could practice their foreign langauge on-the-go. (Likewise, I should stow our spelling book in the car and use car rides as a chance to quiz them.)
And of course we’re still reading Professor Astro Cat/working in the workbook, which involves plenty of writing.
For Social Studies we’ve been reading about fall holidays.
Hope you all have a lovely October! What are some of your favorite educational videos?
I’m a really boring person who gets excited about finding math workbooks at the secondhand shop. I got lucky this week and snagged two math and 1 science workbooks, plus Bedtime Math 2 at the library. Since new workbooks/manipulatives/materials can be pricey,* I’ve been keeping an eye out for good deals for, well, pretty much my kids’ whole lives. For example, a few years ago I found Hooked on Math ($45 on Amazon) at Goodwill for a couple of bucks; I found some alphabet flashcards at a garage sale for 50c.
I’m also lucky to have several retired teachers in the family, so I’ve “inherited” a nice pile of teaching materials, from tangrams to fractions.
*That said, sometimes you need a particular workbook now, not whenever one shows up at the second hand shop, so thankfully plenty of workbooks are actually pretty cheap.
But full “curriculums” can be pretty expensive–for example, Saxon Math plus manipulatives runs about $200; a Lifepack 4 or 5-subject curriculum is about $320; Montessori math kit: $250; Horizons: $250. I have no idea if these are worth the money or not.
So I’m glad I already have most of what I need (for now.)
This week we started typing (I went with the first website that came up when I searched for “typing tutor” and so far it’s gone well.) We finished Bedtime Math and moved on to Bedtime Math 2. (We’re also working out of some regular old math books, as mentioned above.)
In science we’re still reading Professor Astro Cat’s Frontiers of Space (today we discussed eclipses,) and we started Professor Astro Cat’s Intergalactic Workbook, which has been fun so far. It has activities based on space gloves, weightlessness, Russian phrases (used on the International Space Station,) Morse Code, etc.
(The gloves activity was difficult for youngest child–in retrospect, one pair of glove would have been sufficient. Eventually they got frustrated and started using their feet instead of hands to complete the activities.)
Professor Astro Cat has therefore been the core of our activities this week.
To keep things light, I’ve interspersed some games like Trucky3, Perplexus, and Fraction Formula. They’re also useful when one kid has finished an activity and another hasn’t and I have to keep them occupied for a while.
Coding continues apace: learned about loops this week.
Spelling is one of our weak points, so I want to do at least some spelling each day, (today we spelled planets’ names) but I’m not sure what the best approach is. English spelling is pretty weird.
Welcome! Highly unscientific polling has revealed an interest in a regular or semi-regular feature focused on homeschooling.
Note that I am NOT some homeschooling guru with years of experience. We are just beginning, so I want some other people to discuss things with. I don’t have a curriculum picked out nor a coherent “philosophy,” but I am SO EXCITED about all of the things I have to teach I couldn’t even list them all.
I was thinking of starting with just a focus on what has been successful this week–which books/websites/projects we liked–and perhaps what was unsuccessful. I invite all of you to come and share your thoughts, ideas, questions, philosophies, recommendations, etc. Parents whose kids are attending regular schools but want to talk about learning materials are also welcome.
One request: Please no knee-jerk bashing of public schools or teachers. (I just find this really annoying.) Thoughtful, well-reasoned critique of mainstream schooling are fine, but let’s try to focus on the homeschooling.
Like many parents, I thought it’d be useful to learn some basic coding, but have no idea where to start. I once read HTML for dummies, but I don’t know my CSS from Perl, much less what’s best for kids.
After a bit of searching, I decided to try the the DK Coding with Scratch series. (This particular workbook is aimed at kids 6-9 yrs old, but there are others in the series.)
Scratch is a free, simple, child-friendly coding program available online at https://scratch.mit.edu/. You don’t need the workbook to use Scratch, (it’s just a helpful supplement.) There are also lots of helpful Youtube videos for the enterprising young coder.
Note: my kids really want to code because they want to make their own video games.
In general, I have found that toys and games that claim they will teach your kids to code actually won’t. (Eg, Robot Turtles.) Some of these games are a ton of fun anyway, I just wouldn’t expect to become a great coder that way.
I’m still trying to figure out how to do hands-on science activities without spending a bundle. Most of the “little labs” type science kits look fun, but don’t pack a lot of educational bang for your buck. For example, today we built a compass (it cost $10 at the toy store, not the $205 someone is trying charge on Amazon.) This was fun and I really like the little model, but it also took about 5 minutes to snap the pieces together and we can’t actually carry it around to use it like a real compass.
Plus, most of these labs are basically single-use items. I like toys with a sciency-theme, but they’re too expensive to run the whole science curriculum off of.
Oh, sure, I hand them a page of math problems and they start squawking at me like chickens. But bedtime rolls around and they’re like, “Where’s our Bedtime Math? Can’t we do one more page? One more problem? Please?”
There are only three math problems every other page (though this does add up to over 100 problems,) the presentation is fun, and the kids like the book better than going to sleep.
The book offers easy, medium, and hard problems in each section, so it works for kids between the ages of about 4 and 10.
There’s an inherent tension in education between emphasizing subjects that kids are already good at and working on the ones they’re bad at. The former gives kids a chance to excel, build confidence, and of course actually get good at something, while the latter is often an annoying pain in the butt but nevertheless necessary.
Since we’ve just started and are still getting in the swing of things, I’m trying to focus primarily on the things they’re good at and enjoy and have just a little daily focus on the things they’re weak at.
I’d like to find a good typing tutor (I’ll probably be trying several out soon) because watching the kids hunt-and-peck at the keyboard makes my hair stand on end. I’d also like to find a good way to hold up workbooks next to the computer to make using the DK books easier.
That’s about it, so I’ll open the floor to you guys.
This all occasioned some very annoying conversations along the lines of “White skin tone couldn’t possibly have evolved within the past 20,000 years because humans evolved in Europe! Don’t you know anything about science?”
Ohkay. Let’s step back a moment and take a look at what Graecopithecus is and what it isn’t.
This is Graecopithecus:
I think there is a second jawbone, but that’s basically it–and that’s not six teeth, that’s three teeth, shown from two different perspectives. There’s no skull, no shoulder blades, no pelvis, no legs.
By contrast, here are Lucy, the famous Australopithecus from Ethiopia, and a sample of the over 1,500 bones and pieces of Homo naledi recently recovered from a cave in South Africa.
Now, given what little scientists had to work with, the fact that they managed to figure out anything about Graecopithecus is quite impressive. The study, reasonably titled “Potential hominin affinities of Graecopithecus from the Late Miocene of Europe,” by
Jochen Fuss, Nikolai Spassov, David R. Begun, and Madelaine Böhm, used μCT and 3D reconstructions of the jawbones and teeth to compare Graecopithecus’s teeth to those of other apes. They decided the teeth were different enough to distinguish Graecopithecus from the nearby but older Ouranopithecus, while looking more like hominin teeth:
G. freybergi uniquely shares p4 partial root fusion and a possible canine root reduction with this tribe and therefore, provides intriguing evidence of what could be the oldest known hominin.
My hat’s off to the authors, but not to all of the reporters who dressed up “teeth look kind of like hominin teeth” as “Humans evolved in Europe!”
First of all, you cannot make that kind of jump based off of two jawbones and a handfull of teeth. Many of the hominin species we have recovered–such as Homo naledi and Homo floresiensis, as you know if you already read the previous post–possessed a mosaic of “ape like” and “human like” traits, ie:
The physical characteristics of H. naledi are described as having traits similar to the genus Australopithecus, mixed with traits more characteristic of the genus Homo, and traits not known in other hominin species. The skeletal anatomy displays plesiomorphic (“ancestral”) features found in the australopithecines and more apomorphic (“derived,” or traits arising separately from the ancestral state) features known from later hominins.
If we only had six Homo naledi bones instead of 1,500 of them, we might be looking only at the part that looks like an Australopithecus instead of the parts that look like H. erectus or totally novel. You simply cannot make that kind of claim off a couple of jawbones. You’re far too likely to be wrong, and then not only will you end up with egg on your face, but you’ll only be giving more fuel to folks who like to proclaim that “Nebraska Man turned out to be a pig!”:
In February 1922, Harold Cook wrote to Dr. Henry Osborn to inform him of the tooth that he had had in his possession for some time. The tooth had been found years prior in the Upper Snake Creek beds of Nebraska along with other fossils typical of North America. … Osborn, along with Dr. William D. Matthew soon came to the conclusion that the tooth had belonged to an anthropoid ape. They then passed the tooth along to William K. Gregory and Dr. Milo Hellman who agreed that the tooth belonged to an anthropoid ape more closely related to humans than to other apes. Only a few months later, an article was published in Science announcing the discovery of a manlike ape in North America. An illustration of H. haroldcookii was done by artist Amédée Forestier, who modeled the drawing on the proportions of “Pithecanthropus” (now Homo erectus), the “Java ape-man,” for the Illustrated London News. …
Examinations of the specimen continued, and the original describers continued to draw comparisons between Hesperopithecus and apes. Further field work on the site in the summers of 1925 and 1926 uncovered other parts of the skeleton. These discoveries revealed that the tooth was incorrectly identified. According to these discovered pieces, the tooth belonged neither to a man nor an ape, but to a fossil of an extinct species of peccary called Prosthennops serus.
That basically sums up everything I learned about human evolution in highschool.
Second, “HUMANS” DID NOT EVOLVE 7 MILLION YEARS AGO.
Scientists define “humans” as members of the genus Homo, which emerged around 3 million years ago. These are the guys with funny names like Homo habilis, Homo neanderthalensis, and the embarrassingly named Homo erectus. The genus also includes ourselves, Homo sapiens, who emerged around 200-300,000 years ago.
Homo habilis descended from an Australopithecus, perhaps Lucy herself. Australopithecines are not in the Homo genus; they are not “human,” though they are more like us than modern chimps and bonobos are. They evolved around 4 million years ago.
Regardless, humans didn’t evolve 7 million years ago. Sahelanthropus and even Lucy do not look like anyone you would call “human.” Humans have only been around for about 3 million years, and our own specific species is only about 300,000 years old. Even if Graecopithecus turns out to be the missing link–the true ancestor of both modern chimps and modern humans–that still does not change where humans evolved, because Graecopithecus narrowly missed being a human by 4 million years.
If you want to challenge the Out of Africa narrative, I think you’d do far better arguing for a multi-regional model of human evolution that includes back-migration of H. erectus into Africa and interbreeding with hominins there as spurring the emergence of H. sapiens than arguing about a 7 million year old jawbone. (I just made that up, by the way. It has no basis in anything I have read. But it at least has the right characters, in the right time frame, in a reasonable situation.)
Sorry this was a bit of a rant; I am just rather passionate about the subject. Next time we’ll examine very exciting news about Bushmen and Pygmy DNA!
There has been SO MUCH EXCITING NEWS out of paleoanthropology/genetics lately, it’s been a little tricky keeping up with it all. I’ve been holding off on commenting on some of the recent developments to give myself time to think them over, but here goes:
Ancient hominins in the US?
Humans evolved in Europe?
In two days, first H Sap was pushed back to 260,000 years,
Here we describe the Cerutti Mastodon (CM) site, an archaeological site from the early late Pleistocene epoch, where in situ hammerstones and stone anvils occur in spatio-temporal association with fragmentary remains of a single mastodon (Mammut americanum). The CM site contains spiral-fractured bone and molar fragments, indicating that breakage occured while fresh. Several of these fragments also preserve evidence of percussion. The occurrence and distribution of bone, molar and stone refits suggest that breakage occurred at the site of burial. Five large cobbles (hammerstones and anvils) in the CM bone bed display use-wear and impact marks, and are hydraulically anomalous relative to the low-energy context of the enclosing sandy silt stratum. 230Th/U radiometric analysis of multiple bone specimens using diffusion–adsorption–decay dating models indicates a burial date of 130.7 ± 9.4 thousand years ago. These findings confirm the presence of an unidentified species of Homo at the CM site during the last interglacial period (MIS 5e; early late Pleistocene), indicating that humans with manual dexterity and the experiential knowledge to use hammerstones and anvils processed mastodon limb bones for marrow extraction and/or raw material for tool production.
Note that “Homo” here is probably not H. sapiens, but a related or ancestral species, like Denisovans or Homo erectus, because as far as we know, H. sapiens was still living in Africa at the time.
This is obviously a highly controversial claim. Heck, “earliest human presence in the Americas” was already controversial, with some folks firmly camped at 15,000 years ago and others camped around 40,000 yeas ago. 130,000 years ago wasn’t even on the table.
Unfortunately, the article is paywalled, so I can’t read the whole thing and answer simple questions like, “Did they test the thickness of mineral accumulation on the bones to see if the breaks/scratches are the same age as the bones themselves?” That is, minerals build up on the surfaces of old bones over time. If the breaks and scratches were made before the bones were buried, they’ll have the same amount of buildup as the rest of the bone surfaces. If the breaks are more recent–say, the result of a bulldozer accidentally backing over the bones–they won’t.
They did get an actual elephant skeleton and smacked it with rocks to see if it would break in the same ways as the mammoth skeleton. A truck rolling over a rib and a rock striking it at an angle are bound to produce different kinds and patterns of breakage (the truck is likely to do more crushing, the rock to leave percussive impacts.) I’d also like to know if they compared the overall butchering pattern to known stone-tool-butchered elephants or mammoths, although I don’t know how easy it would be to find one.
They also looked at the pattern of impacts and shapes of the “hammerstones.” A rock which has been modified by humans hitting it with another rock will typically have certain shapes and patterns on its surface that can tell you things like which angle the rock was struck from during crafting. I’ve found a few arrowheads, and they are pretty distinct from other rocks.
Here’s a picture of an Oldowan stone chopper, about 2 million years old, which is therefore far older than these potential 130,000 year old tools. Homo sapiens didn’t exist 2 million years ago; this pointy rock was probably wielded by species such as Australopithecus garhi,H. habilis, orH. ergaster. Note that one side of this chopper is rounded, intended for holding comfortably in your hand, while the other side has had several chunks of rock smacked off, resulting in convex surfaces. Often you can tel exactly where the stone tool was struck to remove a flake, based on the shape and angle of the surface and the pattern of concentric, circular lines radiating out from the impact spot.
Homo erectus, who lived after the Oldowan tool makers and had a fancier, more complicated lithic technology, did make it out of Africa and spread across southeast Asia, up into China. This is, as far as I know, the first case of a hominin species using tools to significantly expand its range, but we have no evidence of erectus ever expanding into places that get significantly cold in the winter, and boat-building is a pretty advanced skill. We don’t even think erectus made it to Madagascar, which makes it sailing to the Americans rather doubtful.
I dislike passing judgment on the paper without reading it, but my basic instinct is skepticism. While I think the peopling of the Americas will ultimately turn out to be a longer, more complex, and interesting process than the 15,000 years camp, 130,000 years is just too interesting a claim to believe without further evidence (like the bones of said hominins.)
Still, I keep an open mind and await new findings.