Category: Science
The class gap in academic career progression
There is a new and excellent paper by Anna Stansbury and Kyra Rodriguez on this topic:
Unlike gender or race, class is rarely a focus of research or DEI efforts in elite US occupations. Should it be? In this paper, we document a large class gap in career progression in one labor market: US tenure-track academia. Using parental education to proxy for socioeconomic background, we compare career outcomes of people who got their PhDs in the same institution and field (excluding those with PhD parents). First-generation college graduates are 13% less likely to end up tenured at an R1, and are on average tenured at institutions ranked 9% lower, than their PhD classmates with a parent with a (non-PhD) graduate degree. We explore three sets of mechanisms: (1) research productivity, (2) networks, and (3) preferences. Research productivity can explain less than a third of the class gap, and preferences explain almost none. Our analyses of coauthor characteristics suggest networks likely play a role. Finally, examining PhDs who work in industry we find a class gap in pay and in managerial responsibilities which widens over the career. This means a class gap in career progression exists in other US occupations beyond academia.
Here is a first-rate tweet storm by Stansbury on the paper. Via Aidan Finley.
The intelligent chicken culture that is Canada
A British Columbia chicken earned a Guinness World Record by identifying different numbers, colors and letters.
Gabriola Island veterinarian Emily Carrington said she bought five hyline chickens last year to produce eggs, and she soon started training the hens to identify magnetic letters and numbers.
“Their job was to only peck the number or letter that I taught them to peck and ignore the other ones. Even if I add a whole bunch of other letters that aren’t the letter they are supposed to peck, they will just peck the letter that I trained them to peck,” Carrington told the Nanaimo News Bulletin.
Carrington decided to have all of her chickens attempt the Guinness World Records title for the most tricks by a chicken in one minute.
One of the chickens, Lacy, emerged as the clear winner of the flock, correctly identifying 6 letters, numbers and colors in one minute.
The focused nature of the tricks led Guinness World Records to create a new category for Lacy: the most identifications by a chicken in one minute.
Here is the full story, via the excellent Samir Varma.
How Many Workers Did It Take to Build the Great Pyramid of Giza?
The Great Pyramid of Giza was built circa 2600 BC and was the world’s tallest structure for nearly 4000 years. It consists of an estimated 2.3 million blocks with a weight on the order of 6-7 million tons. How many people did it take to construct the Great Pyramid? Vaclav Smil in Numbers Don’t Lie gives an interesting method of calculation:
The Great Pyramid’s potential energy (what is required to lift the mass above ground level) is about 2.4 trillion joules. Calculating this is fairly easy: it is simply the product of the acceleration due to gravity, the pyramid’s mass, and its center of mass (a quarter of its height)…I am assuming a mean of 2.6 tons per cubic meter and hence a total mass of about 6.75 million tons.
People are able to convert about 20 percent of food energy into useful work, and for hard-working men that amounts to about 440 kilojoules a day. Lifting the stones would thus require about 5.5 million labor days (2.4 trillion/44000), or about 275,000 days a year during [a] 20 year period, and about 900 people could deliver that by working 10 hours a day for 300 days a year. A similar number might be needed to emplace the stones in the rising structure and then smooth the cladding blocks…And in order to cut 2.6 million cubic meters of stone in 20 years, the project would have required about 1,500 quarrymen working 300 days per year and producing 0.25 cubic meters of stone per capita…the grand total would then be some 3,300 workers. Even if we were to double that in order to account for designers, organizers and overseers etc. etc….the total would be still fewer than 7,000 workers.
…During the time of the pyramid’s construction, the total population of Egypt was 1.5-1.6 million people, and hence the deployed force of less than 10,000 would not have amounted to any extraordinary imposition on the country’s economy.
I was surprised at the low number and pleased at the unusual method of calculation. Archeological evidence from the nearby worker’s village suggests 4,000-5,000 on site workers, not including the quarrymen, transporters and designers and support staff. Thus, Smil’s calculation looks very good.
What other unusual calculations do you know?
Nuclear is Not Best Everywhere
Australia is having a debate over nuclear power. Hamilton and Heeney weigh in with an important perspective:
On the basis of many conversations about Australian energy policy over the years, we can divide the proponents of nuclear energy into three groups.
The first might be called the “ideologues”. They favour nuclear not because of its zero emissions, but despite it. Indeed, many are climate sceptics. They hate renewables because the left loves them, and they favour nuclear because the left hates it.
The second might be called the “engineers”. They favour nuclear energy because it’s cool. Like a Ferrari, they marvel at its performance and stability. They see it as the energy source of the future. The stuff of science fiction.
The third might be called the “pragmatists”. They are not super attentive or highly informed about the intricacies of energy policy. They superficially believe nuclear can serve as a common-sense antidote to the practical shortcomings of renewables.
Conspicuously absent are those who might be called the “economists”. They couldn’t care less about exactly how electrons are produced. They simply want the cheapest possible energy that meets a minimum standard of reliability and emissions.
On the basis of the economics, Hamilton and Heeney conclude that nuclear is expensive for Australia:
The CSIRO estimates the cost of 90 per cent renewables, with firming, transmission, and integration costs included, at $109 per megawatt hour. Based on South Korean costs (roughly one-third of the US and Europe), a 60-year lifespan, a 60 per cent economic utilisation rate (as per coal today), and an eight-year build time (as per the global average), nuclear would cost $200 per megawatt hour – nearly double.
The same electrons delivered with the same reliability, just twice as expensive under what is a fairly optimistic scenario.
Note–this is taking into account that nuclear is available when the sun doesn’t shine and the winds don’t blow–so are batteries.
I suspect that Hamilton and Heeney are right on the numbers but it’s this argument that I find most compelling:
If you need external validation of these basic economics, look no further than the opposition’s own announcement. Rather than lift the moratorium and allow private firms to supply nuclear energy if it’s commercially viable, the opposition has opted for government to be the owner and operator. A smoking gun of economic unviability if ever there were one.
I am optimistic about the potential of small modular reactors (SMRs) based on innovative designs. These reactors can ideally be located near AI facilities. As I argued in the Marginal Revolution Theory of Innovation, innovation is a dynamic process; success rarely comes on the first attempt. The key to innovation is continuous refinement and improvement. These small reactors based on different technologies give as an opportunity to refine and improve. To achieve this, we must overhaul our regulatory framework, which has disproportionately burdened nuclear energy—our greenest power source—with excessive regulation compared to more hazardous and less environmentally friendly technologies.
Electrons are electrons. We should allow all electricity generation technologies to compete in the market on an equal footing. Let the best technologies win.
Needed in Empirical Social Science: Numbers
By Aaron S. Edlin and Michael Love:
Knowing the magnitude and standard error of an empirical estimate is much more important than simply knowing the estimate’s sign and whether it is statistically significant. Yet, we find that even in top journals, when empirical social scientists choose their headline results – the results they put in abstracts – the vast majority ignore this teaching and report neither the magnitude nor the precision of their findings. They provide no numerical headline results for 63%±3% of empirical economics papers and for a whopping 92% ± 1% of empirical political science or sociology papers between 1999 and 2019. Moreover, they essentially never report precision (0.1% ± 0.1%) in headline results. Many social scientists appear wedded to a null hypothesis testing culture instead of an estimation culture. There is another way: medical researchers routinely report numerical magnitudes (98%±1%) and precision (83% ± 2%) in headline results. Trends suggest that economists, but not political scientists or sociologists, are warming to numerical reporting: the share of empirical economics articles with numerical headline results doubled since 1999, and economics articles with numerical headline results get more citations (+19% ± 11%).
Via somebody on Twitter?
“US-based academics and those at top-ranked institutions exhibit higher egocentrism and toxicity in their tweets”
Compared to other academics, that is. They are still more reasonable than the general public on Twitter. Here is the paper by Prashant Garg and Thiemo Fetzer. Here is a useful tweet storm about the paper. Via Kris Gulati.
China fact of the day
In 2022 more of the top-tier ai researchers working in America hailed from China than from America.
Of course the Canadians do their part to help make this come true. Here is a much longer survey from The Economist about science in China. Via Z.
*The Wrong Stuff: How the Soviet Space Program Crashed and Burned*
By John Strausbaugh, an excellent book. Here is one good passage of many:
Putting dogs on top of rockets was nothing new. Since so little was known about the effects that blasting off in a rocket might have on th ehuman body and brain — the g-force of acceleration, the disorientation of weightlessness, the impact of radiation, the g-force of deceleration — the Soviets and the Americans both had been using various species of animals to test conditions since the 1940s. The Americans started sending up fruit flies aboard their White Sands V-2s in 1947. An anesthetized rhesus monkey they named Albert II…went up eighty-three miles in a V-2 in 1949. Unfortunately, his parachute failed to oepn on reentry and he was smashed to death on impact with the ground. The Americans continued to send up primates in the 1940s and 1950s. Something like two-thirds of them died. They used many other species as well, maybe the oddest of which was black bears, who were strapped into a rocket-powered sled at a facility with the deceptively sweet name the Daisy Track to test the physical effects of ultra-rapid acceleration and deceleration.
Recommended.
A virtual rodent predicts the structure of neural activity across behaviors
Animals have exquisite control of their bodies, allowing them to perform a diverse range of behaviors. How such control is implemented by the brain, however, remains unclear. Advancing our understanding requires models that can relate principles of control to the structure of neural activity in behaving animals. To facilitate this, we built a ‘virtual rodent’, in which an artificial neural network actuates a biomechanically realistic model of the rat in a physics simulator. We used deep reinforcement learning to train the virtual agent to imitate the behavior of freely-moving rats, thus allowing us to compare neural activity recorded in real rats to the network activity of a virtual rodent mimicking their behavior. We found that neural activity in the sensorimotor striatum and motor cortex was better predicted by the virtual rodent’s network activity than by any features of the real rat’s movements, consistent with both regions implementing inverse dynamics. Furthermore, the network’s latent variability predicted the structure of neural variability across behaviors and afforded robustness in a way consistent with the minimal intervention principle of optimal feedback control. These results demonstrate how physical simulation of biomechanically realistic virtual animals can help interpret the structure of neural activity across behavior and relate it to theoretical principles of motor control.
Here is the new Nature article by Diego Aldarnado, et.al. Via @sebkrier.
Terence Tao on AI and mathematics
With formalization projects, what we’ve noticed is that you can collaborate with people who don’t understand the entire mathematics of the entire project, but they understand one tiny little piece. It’s like any modern device. No single person can build a computer on their own, mine all the metals and refine them, and then create the hardware and the software. We have all these specialists, and we have a big logistics supply chain, and eventually we can create a smartphone or whatever. Right now, in a mathematical collaboration, everyone has to know pretty much all the mathematics, and that is a stumbling block, as [Scholze] mentioned. But with these formalizations, it is possible to compartmentalize and contribute to a project only knowing a piece of it. I think also we should start formalizing textbooks. If a textbook is formalized, you can create these very interactive textbooks, where you could describe the proof of a result in a very high-level sense, assuming lots of knowledge. But if there are steps that you don’t understand, you can expand them and go into details—all the way down the axioms if you want to. No one does this right now for textbooks because it’s too much work. But if you’re already formalizing it, the computer can create these interactive textbooks for you. It will make it easier for a mathematician in one field to start contributing to another because you can precisely specify subtasks of a big task that don’t require understanding everything.
The entire interview is worth reading. As Adam Smith once said…
Basil Halperin, observations on academia and research
Miscellaneous things I learned in [econ] grad school: 1. The returns to experience are high(er than I thought) – Someone who has studied a single topic for a decade or two or three really does know a LOT about that topic
It is worth clicking through to read the whole thread. People should be writing more about how things actually work! This is oddly grossly undersupplied. His points about seminars are especially interesting and well-taken.
Updating the Drake equation?
Planetary scientists Robert Stern from the University of Texas at Dallas and Taras Gerya from ETH-Zurich, the two co-authors on the study, suggest that the presence of both continents and oceans, along with long-term plate tectonics, is critical for the emergence of advanced civilizations. They consequently propose the addition of two factors into the equation: the fraction of habitable planets with significant continents and oceans and the fraction of those planets with plate tectonics operating for at least 500 million years. This adjustment, however, significantly reduces the value of N in the Drake Equation…
According to the new study, plate tectonics are crucial for developing complex life and advanced civilizations. Earth’s plate movements create diverse habitats, recycle nutrients, and regulate climate—all vital for life. It’s important for plate tectonics to last for 500 million years, Gerya explained, because biological evolution of complex multicellular life is extremely slow. “On Earth, it took more than 500 million years to develop humans from the first animals, which appeared around 800 million years ago,” he said.
Here is more from George Dvorsky, via the excellent Samir Varma.
The partisanship of American inventors
Using panel data on 251,511 patent inventors matched with voter registration records containing partisan affiliation, we provide the first large-scale look into the partisanship of American inventors. We document that the modal inventor is Republican and that the partisan composition of inventors has changed in ways that are not reflective of partisan affiliation trends amongst the broader population. We then show that the partisan affiliation of inventors is associated with technological invention related to guns and climate change, two issue areas associated with partisan divide. These findings suggest that inventor partisanship may have implications for the direction of inventive activity.
Here is the full piece by Daniel Fehder, Florenta Teodoridis, Joseph Raffee, and Jino Lu. Via Kris Gulati.
My Conversation with the excellent Michael Nielsen
Here is the audio, video, and transcript. Here is the episode summary:
Michael Nielsen is scientist who helped pioneer quantum computing and the modern open science movement. He’s worked at Y Combinator, co-authored on scientific progress with Patrick Collison, and is a prolific writer, reader, commentator, and mentor.
He joined Tyler to discuss why the universe is so beautiful to human eyes (but not ears), how to find good collaborators, the influence of Simone Weil, where Olaf Stapledon’s understand of the social word went wrong, potential applications of quantum computing, the (rising) status of linear algebra, what makes for physicists who age well, finding young mentors, why some scientific fields have pre-print platforms and others don’t, how so many crummy journals survive, the threat of cheap nukes, the many unknowns of Mars colonization, techniques for paying closer attention, what you learn when visiting the USS Midway, why he changed his mind about Emergent Ventures, why he didn’t join OpenAI in 2015, what he’ll learn next, and more.
And here is one excerpt:
COWEN: Now, you’ve written that in the first half of your life, you typically were the youngest person in your circle and that in the second half of your life, which is probably now, you’re typically the eldest person in your circle. How would you model that as a claim about you?
NIELSEN: I hope I’m in the first 5 percent of my life, but it’s sadly unlikely.
COWEN: Let’s say you’re 50 now, and you live to 100, which is plausible —
NIELSEN: Which is plausible.
COWEN: — and you would now be in the second half of your life.
NIELSEN: Yes. I can give shallow reasons. I can’t give good reasons. The good reason in the first half was, so much of the work I was doing was kind of new fields of science, and those tend to be dominated essentially, for almost sunk-cost reasons — people who don’t have any sunk costs tend to be younger. They go into these fields. These early days of quantum computing, early days of open science — they were dominated by people in their 20s. Then they’d go off and become faculty members. They’d be the youngest person on the faculty.
Now, maybe it’s just because I found San Francisco, and it’s such an interesting cultural institution or achievement of civilization. We’ve got this amplifier for 25-year-olds that lets them make dreams in the world. That’s, for me, anyway, for a person with my personality, very attractive for many of the same reasons.
COWEN: Let’s say you had a theory of your collaborators, and other than, yes, they’re smart; they work hard; but trying to pin down in as few dimensions as possible, who’s likely to become a collaborator of yours after taking into account the obvious? What’s your theory of your own collaborators?
NIELSEN: They’re all extremely open to experience. They’re all extremely curious. They’re all extremely parasocial. They’re all extremely ambitious. They’re all extremely imaginative.
Self-recommending throughout.
Can they reconstitute Philosphy & Public Affairs?
Here is a recent announcement of note:
We are unanimously resigning from our editorial roles at Philosophy & Public Affairs, published by Wiley, and launching a new diamond open-access journal published by Open Library of Humanities (OLH). All of us will play the same editorial roles in the new journal and will retain the aim of publishing the best philosophical work touching on matters of public importance.
Do read the whole text, but you can imagine how the arguments run. Lots of big names are behind this, including Sen, Scheffler, Srinivasan, Waldron, and others. I am rooting for them, but can this succeed?
How sticky are reputations anyway? Nine months from now, what percentage of people on a university-wide tenure committee will know about this change? Three years from now?
Or consider the new journal itself. Without the long history of famous articles behind it, might it, with the same set of editors, have a lower reputation? Talk about mood affiliation!
Or might the existence of a “naming squabble” itself lower the reputations of both the old journal and the new venture? “Well, if they can’t get along, both outlets will have trouble managing their future reputations…”
Or might some of the highly prestigious editors, over time, be more willing to leave than would have been the case under the old moniker? Perhaps the newly reconstituted board will not be able to get along with itself, not without the final backstop of “the company” (Wiley) to enforce a core on all the bargaining.
If I am in the second year of my tenure clock in a philosophy department, and I have a great paper, do I send it to the new journal? In its old manifestation it was a top top outlet, but is it still? What risks am I running? Or do I send it to the thing still named Philosophy & Public Affairs, which presumably still has some very good new editors.
I will be watching.