Lecture on Debye model for solids

 I just finished preparing my undergraduate lecture on the Debye model for solids. Here are my slides. The course is a third-year course on statistical mechanics. In the previous lecture, they learned about blackbody radiation and derived the Planck spectrum.

(Note. The derivations are not included, as I sketch them by hand on a document viewer. This slows down the pace of the lecture and engages the students as they detect mistakes I make. :) ) 

A few things I find interesting about the lecture content.

The Debye theory is very similar to Planck's theory of blackbody radiation. The main difference is that for Debye there is a high-frequency cutoff for the phonon spectrum. This defines the Debye temperature.

Given its simplicity, the success of Debye theory, qualitatively and quantitatively, is impressive. Arguably, this is because it is an effective theory that is constrained to be consistent with the long-wavelength physics (elasticity theory) and the classical limit (number of modes of lattice vibration).

The beautiful textbook by Schroeder is a bit confusing on page 312. He claims that the Debye temperature lead (88K) is much less than that for diamond (1860 K) because the former is "soft and dense" whereas the latter is "stiff and light".  The speed of sound in diamond is about ten times that in graphite. The mass density is not particularly relevant. However, the number density of atoms (which is what enters the Debye formula) in diamond is actually 5 times larger than lead because of the strong covalent bonding which makes the interatomic distance small.  

A few historical notes I found interesting.  

Einstein's model for solids (1907) was important because it provided significant evidence for quantum theory, i.e., that the energy of lattice vibrations was quantised.

Sommerfeld said that his biggest discovery was his student Peter Debye.

Around 2006, there were moves to "cancel" Debye because of alleged Nazi sympathies. However, because the evidence was ambiguous, these moves faltered.

Lecture on degenerate Fermi gases at low temperatures

Here are the slides for an undergraduate lecture I gave today. The slides also include the derivations I gave by hand on the document viewer.

For historical background, I found a book chapter from Out of the Crystal Maze, interesting and helpful.

Some fascinating context concerning Arnold Sommerfeld. Over a period of 32 years, he built up an amazing school of theoretical physics in Munich. He mentored seven future Nobel laureates. However, sadly, when he retired in 1934 from a Chair in Theoretical Physics, it took four years to replace him because of interference from the Nazi Party. Even worse, in the end, Wilhelm Muller, a Nazi loyalist, was appointed. According to Wikipedia

"Müller, an aerodynamicist, had not been thought of as a theoretical physicist before this time, and opposed the "new" theoretical physics promoted by scientists such as Albert Einstein. His appointment is seen by historians as political, and during his tenure he would teach only classical physics"

Questions to consider when evaluating AI

 I am a slow adopter of new technologies. I have recently been playing around with AI at a very basic level on some research problems. Colleagues are also telling me about their experiences. I want to write something about its potential, both good and bad, for research and teaching. I want to hear from more people, particularly in condensed matter theory. However, before that, I think it is worth stepping back and asking some bigger questions than "Can AI help me publish more papers?" or "How do we stop students cheating on assessment?", as important as they are. I know the mathematics community is going through some angst and has issued a declaration about AI, and it is good to see that level of reflection.

Neil Postman (1931-2003) was a media theorist and cultural critic at New York University who spent a lifetime wrestling with questions about the broader implications of new technologies. In a talk given in 1998, he considered five things we need to know about technological change. Postman's enduring influence and relevance are marked by the fact that these five things featured in a column in The Washington Post, "Is the Internet Evil?" by Christine Emba, published in 2018.

Below, I summarise the five ideas from Postman's talk and provide questions (in italics) we should ask about any technology, particularly Artificial Intelligence (AI).

1. All technological change is a trade-off. 

"the greater the wonders of a technology, the greater will be its negative consequences" 

Don't just ask the question "What will a new technology do?" Also ask, "What will a new technology undo?"

"a sophisticated perspective on technological change includes one’s being skeptical of Utopian and Messianic visions drawn by those who have no sense of history or of the precarious balances on which culture depends."

Through adoption of the technology, what will we lose, individually and as a society?

2. The advantages and disadvantages of a new technology are never distributed evenly among the population.

Who will benefit? Who will be harmed? 

Winners will try to persuade losers that they will benefit as well.

Benefits and harms can relate to employment, finances, social status, health, and political power.

3.  Embedded in every technology are powerful ideas. 

"These ideas are often hidden from our view because they are of a somewhat abstract nature. But this should not be taken to mean that they do not have practical consequences."

"The telegraphic person values speed, not introspection. The television person values immediacy, not history... the computer person values information, not knowledge, certainly not wisdom." 

"The medium is the message."

What ideas are embedded in the technology?

How does it make us use our minds and bodies?

How does it affect our personal relationships and social cohesion?

4. Technological change is not additive; it is ecological. It changes everything.

"The consequences of technological change are always vast, often unpredictable and largely irreversible."

The entrepreneurs who started the television industry "did not mean to turn political discourse into a form of entertainment."

The consequences can be social, economic, political, environmental, religious, and health-related.

What are the unintended consequences of the technology?

5. When a technology becomes mythic, it is always dangerous because it is then accepted as it is, and is therefore not easily susceptible to modification or control.

"...our enthusiasm for technology can turn into a form of idolatry and our belief in its beneficence can be a false absolute. The best way to view technology is as a strange intruder, to remember that technology is not part of God’s plan but a product of human creativity and hubris, and that its capacity for good or evil rests entirely on human awareness of what it does for us and to us."

How does the technology lead to idolatry? Do some people worship it, its creators, or its owners?

Finally,

Do we use the technology or does the technology use us? 

In different words, will we shape our lives to fit the requirements of the technology, rather than have our values shape our use of the technology?

Measuring the social, ethical, and political values of different AI models

I continue to enjoy reading my hard copy of The Economist every week. Occasionally, I post examples of insightful graphics presented in articles.

Here are some graphics that struck me recently. They are taken from a fascinating article. AI models’ values are very different from most people’s

The first figure shows a comparison of the answers given to the World Values Survey by different Large Language Models and people from different regions (cultures) of the world. The vertical axis goes from traditional values at the bottom to secular values at the top. The horizontal axis goes from survival (or communal) values on the left to self-expression on the right.

Note how the different cultures do not overlap. Furthermore, the LLMs are distant from almost everyone. Just a few are close to the English speaking world. 

The second graph compares answers to the VOTER survey of political questions. The horizontal and vertical axes correspond to Social and Economic issues respectively. Positive and negative values correspond to conservative and liberal respectively. Answers from LLMs are compared to a sample of Trump and Biden voters from the 2020 USA Presidential election. Note the clear political polarisation. Furthermore, the AI models are all liberal.

I offer no comments on whether any of this is good or bad. I do suggest two implications. First, extensive use of AI will tend to shift peoples values in a particular direction, just like media (music, TV, movies, art) does. Second, given the conflict of values with most people these biases will offend or concern many communities and increase the backlash against AI companies and its widespread adoption. Consequently, some will modify the training of their models so they align more with the values of vocal communities. Whether or not that is seen as a good thing, will depend on whether you think some of those values should be affirmed.

What do you think?

Scandals in Australian universities

In Australia, scandals about the management of public universities continue to be covered in the media. A recent one is the use of billions of dollars to pay consulting firms to tell management which staff to sack and courses to cut because they are not making a profit.

Below is a recent episode of an ABC (Australian equivalent of BBC or PBS in USA) show on the topic, Chaos on Campus.

I tend to avoid engaging too much with media lamenting the state of unversities as I find it too disturbing. However, I was asked to reference the show in something I was asked to write and so felt I should watch it. It was painful.

This is definitely a scandal. However, it got me reflecting on something that I think gets virtually no media coverage and when I talk to people outside the university, they are pretty surprised and shocked. Anecdotal evidence from my colleagues is that attendance at lectures is now typically around 10-30 per cent of enrolment. Even before COVID-19, lectures at UQ were all recorded. Faculty have no choice. But only a few per cent of students watch the videos. This is quite demoralising for faculty.

What does this low level of student engagement mean for learning outcomes?

What is happening elsewhere? 

Here are some links from Google AI. 

I did not find them that insightful.

One link is an article from The Guardian in Australia from last year. It highlights how moving things to online and lowering standards is driven by financial incentives. This ties in with the scandals in the video. The values of Australian universities are money, marketing, management, and metrics.

What is your own experience with the level of disengagement? How do you think this is affecting student learning? How are you and your colleagues adapting? Are academic standards being lowered? Any suggestions on ways forward?

Responding to scientific uncertainty

Science provides an impressive path to certainty in some areas, particularly in physics. However, as scientists seek to describe increasingly complex entities, moving from chemistry to biology, and then to humans and societies, the level of uncertainty increases.

One observes a wide range of responses to scientific knowledge being uncertain. Here are a few.

Denial. Science is about facts and absolute truth. There really isn’t a problem. We should just trust the scientists.

Minimisation. There is some uncertainty, but it isn’t anything to be concerned about. Some scientists will also minimise any uncertainty about their own research. This may occur because of career ambition. Others will minimise public discussion of uncertainty to try and avoid promoting the science scepticism discussed below.

Optimistic perseverance. The uncertainty is openly acknowledged. Some of the uncertainty does not matter for what we need to know. Other uncertainties can be reduced by further scientific work, such by more precise measurements with new instruments or by developing more sophisticated theories.

Total scepticism. There is a suspicion about the validity of most scientific knowledge, particularly that which is perceived to have philosophical, religious, or political implications.

Suspicion about science

In spite of the success of science at describing the material world and leading to powerful and useful technologies, there is much public suspicion of science. On the one hand, this is understandable given that science has led to technologies with undesirable health, environmental and social consequences. Some scientists, governments and companies have lied about these consequences and hidden them from the public. Human subjects have been abused in medical experiments. Drugs that were claimed to be effective and safe turned out to be ineffective or have undesirable side effects. Science has been used for ideological purposes. Sometimes scientists have faked results to advance their own careers. However, these failures should not undermine our trust in reliable scientific knowledge. Distinctions should be made between the bodies of knowledge, the applications of that knowledge, and the actions of institutions. I now discuss several common claims in public discussion that are used to justify scepticism of scientific knowledge.

Science is always changing. 

One day, scientists tell you that chocolate is good for your health, and the next year they say it is bad for you. And that is just the start. Then there are eggs, wine, running marathons, and cheese. They just can’t make up their mind. So why should we trust them? At one time, they believed in phlogiston and the aether. Now they say they don’t exist. Aristotle was replaced by Newton, who was replaced by Einstein. So why believe in human-induced climate change, biological evolution, vaccines, the Big Bang theory, or Einstein’s theories?

It is true that scientific knowledge does develop and change over time. However, today we have incredibly detailed observations and theories in physics, astronomy, chemistry, biology, and geology. Any future changes will be relatively minor because they will have to be consistent with all the knowledge we have now. Furthermore, when theories change, such as when Einstein superseded Newton, they don’t show that the old theory was completely wrong, but rather that it applied in a limited domain. For example, Newton’s theories of motion and gravity are extremely reliable when it comes to objects that are much larger than atoms, less dense than a black hole, and are moving at speeds less than about 10,000 kilometres per second. This is why engineers spend years learning Newton’s theories, not Einstein’s. If you want to build a good bridge or a rocket, Newton is good enough. He is not wrong.

Update. (Jan. 19). I just discovered that the NY Times had a recent op-ed Science Keeps Changing. So Why Should We Trust It?

“Well, that’s just a theory.” 

In popular debate, such a refrain may be applied to the theory of biological evolution, the Big Bang theory in cosmology, or human-induced climate change. The claimant usually wants to dismiss a particular theory as just idle speculation. Here, the term “theory” is used in the same sense as everyday speculations, such as “I have a theory as to why the president resigned,” or “I have a theory about why my computer is running so slowly.” These are just stories that sound somewhat plausible. In contrast, scientific theories in physics, such as quantum theory and Einstein’s theories of relativity, have precisely defined mathematical formulations that have been checked for logical consistency, made specific predictions, and tested to great precision in experiments. They are not “just theories.” For example, for the Big Bang theory about the beginning of the universe and Darwin’s theory of biological evolution and diversity, there are many independent lines of evidence that are consistent with each theory.  

Scientists cannot be trusted. 

They are not committed to the truth, but rather to their own interests and agendas, related to their careers, politics, and religion. They close ranks and support the status quo of current scientific “dogma”, rather than being open to original thinkers who critique it and propose alternative theories. They don’t want to lose their well-paid jobs and lucrative grants. 

On the one hand, scientists can be conservative and resistant to new ideas. On the other hand, there are significant career incentives to overturn existing knowledge and have your radical new theory accepted. That is how some scientists become famous and win Nobel Prizes. The reasons it does not happen very often are not necessarily for social or ideological reasons. Many of the theories we have today can explain an awful lot. It requires a lot of evidence, carefully acquired and checked, to convince people that those theories need to be modified, let alone abandoned. This may take decades. But it does happen. An example is the Big Bang theory of the universe, whose acceptance was initially resisted because it went against the prevailing view that the universe did not have a beginning. In biology, the discovery in 1970 of the enzyme reverse transcriptase went against a popular version of the “Central dogma” of molecular biology that DNA was always converted to RNA and not the reverse. That discovery led to a Nobel Prize.

I don’t trust scientists. I will do my own research. There is lots of good material from unbiased sources on the internet.

The internet provides a range of information and perspectives on practically any issue imaginable, including science. The material is particularly vast and controversial on biological evolution, the beginning of the universe, fundamental physics, the age of the earth, climate change, and medicine. Since the covid-19 pandemic, scepticism of the effectiveness and safety of vaccines has increased. 

Ivermectin is a drug that was developed as a treatment for parasite worms. Its incredible success was recognised by the award of the 2015 Nobel Prize in Physiology or Medicine to William Campbell and Satoshi Omura, who discovered the drug. During the pandemic, high-profile politicians and social media influencers promoted ivermectin as a treatment for covid-19, even after systematic medical studies showed it was ineffective. Recently, it has gained a reputation as a “miracle” drug that can even cure cancer, but this is being suppressed by the medical establishment. All clinical trials have shown the drug is ineffective for human ailments, beyond deworming. Nevertheless, there are groups on social media with hundreds of thousands of members that discuss the conspiracy, how to get the drug, and the experiences of participants using it to treat a wide range of ailments. Danny Lemoi, a founder of one of the largest groups, died in 2023 after taking massive daily doses of the drug for several years to treat a heart condition. Afterwards, one member of the group wrote “No one can convince me that he died because of ivermectin. He ultimately died because of our failed western medicine which only cares about profits and not the cure.”

Fans of ivermectin claim that they are escaping the biases and vested interests of the medical establishment and Big Pharma as they pursue the truth. However, they are not escaping bias and vested interests. Successful social influencers build their reputations and million-dollar incomes from promoting scepticism. If there is no conspiracy, just scientific uncertainty and occasional incompetence and malpractice, their following collapses. Populist politicians build their careers on criticism of and stoking resentment towards elites, such as the medical establishment. The authority of the medical establishment is replaced with the authority of the popular opinion of a group of people whose views are shaped by social media algorithms, intuition, and anecdotal experience.

My purpose in giving the example of Ivermectin is not to start a detailed critique of science scepticism. Rather, it is to illustrate the role that the interplay of trust, authority, and tradition plays in how we determine what is true and what to act on. There are two competing traditions here: the populism of alternative medicine and the elitism of professional medicine. Each has its own sources of authority. In the end, it boils down to who we trust. We do not have the time, energy, resources or inclination to check the veracity of every single piece of information we have access to. We take shortcuts. This is what tradition does for us, for better and worse. Thus, we cannot escape tradition. We are all swimming in traditions, many of which are in conflict with one another. The question is whether we are aware of it and what we do with that awareness.

My best blog posts of 2025?

 Best wishes for the New Year!

Here is a list of the posts that I wrote last year that I hope get the most interest.

My review article on emergence. I wrote posts about emergence in a range of systems: thermodynamics, quantum gravity, economics,... They were drafts of sections for my review article. It may be best to just read the article.

Why is the state of universities such an emotional issue for me?

Undergraduates need to learn about the Ising model

I wrote a series of posts on so-called "spin-crossover" compounds. Here are two: Spin crossover is a misnomer, and Elastic interactions and complex patterns in binary systems

2025 Nobel Prize in Physics: Macroscopic quantum effects

As always, I welcome comments, feedback, and suggestions for new posts.

Why is the state of universities such an emotional issue for me?

It all about values!

Universities have changed dramatically over the course of my lifetime. Australian universities are receiving increasing media attention due to failures in management and governance. But there is a lot more to the story, particularly at the grassroots level, of the everyday experience of students and faculty. It is all about the four M's: management, marketing, metrics, and money. Learning, understanding, and discovering things for their own sake is alien and marginalised. I have stopped writing posts about this. So why come back to it?

I am often struck how emotional this issue is for me and how hard it is to sometimes talk about it, particularly with those with a different view from me. Writing blog posts (e.g. this one) about it has been a somewhat constructive outlet, rather than exploding in anger at an overpaid and unqualified "manager" or one of their many multiplying minions.

A few weeks ago, I listened to three public lectures by the Australian historian Peter Harrison. [He is my former UQ colleague. We are now both Emeritus. I benefited from excellent seminars he ran at UQ, some of which I blogged about].

The lectures helped me understand what has happened to universities and also why it is a sensitive subject for me. Briefly, it is all about values and virtues.

The lectures are nicely summarised by Peter in the short article, 

How our universities became disenchanted: Secularisation, bureaucracy and the erosion of value

Reading the article rather than this blog post is recommended. I won't try and summarise it, but rather highlight a few points and then make some peripheral commentary.

I agree with Peter's descriptions of the problems we see on the surface (bureaucracy, metrics, and management features significantly). His lectures are a much deeper analysis of underlying cultural changes and shifting worldviews that have occurred over centuries, leading universities to evolve into their current mangled form.

A few things to clarify to avoid potential misunderstanding of Peter's arguments.

Secularisation is defined broadly. It does not just refer to the decline in the public influence of Christianity in the Western world. It is also about Greek philosophy, particularly Aristotle, and the associated emphasis on virtues and transcendence. Peter states:

"The intrinsic motivations of teachers, researchers and scholars can be understood in terms of virtues or duties. According to virtue ethics, the “good” of an activity is related to the way it leads to a cultivation and expression of particular virtues. These, in turn, are related to a particular conception of natural human ends or goals. (Aristotle’s understanding of human nature, which informs virtue ethics, proposes that human beings are naturally oriented towards knowledge, and that they are fulfilled as persons to the extent that they pursue those goals and develop the requisite intellectual virtues.)"

The virtue ethics of Aristotle [and Alisdair MacIntyre] conflicts with competing ethical visions, including duty-oriented (deontological) ethics, consequentialist ethics, and particularly utilitarianism. This led to a shift away from intrinsic goods to what things are "good for", i.e., what practical outcomes they produce. For example, is scientific research "good" and have "value" because it cultivates curiousity, awe, and wonder, or because it will lead to technology that will stimulate economic growth?

Peter draws significantly on Max Weber's ideas about secularisation, institutions, and authority. Weber argued that a natural consequence of secularisation was disenchantment (the loss of magic in the world). This is not simply "people believe in science rather than magic". Disenchantment is a loss of a sense of awe, wonder, and mystery.

Now, a few peripheral responses to the lectures.

Is secularisation the dominant force that has created these problems for universities? In question time, Peter was asked whether capitalism was more important. i.e., universities are treated as businesses and students as customers? He agreed that capitalism is a factor but also pointed out how Weber emphasised that capitalism was connected to the secularising effects of the Protestant Reformation.

 I think that two other factors to consider are egalitarianism and opportunism. These flow from universities being "victims" of their own success. Similar issues may also be relevant to private schools, hospitals, and charities. They have often been founded by people of "charisma" [in the sense used by Weber] motivated by virtue ethics. Founders were not concerned with power, status, or money. What they were doing had intrinsic value to them and was "virtuous". In the early stages, these institutions attracted people with similar ideals. The associated energy, creativity, and common vision led to "success." Students learnt things, patients got healed, and poverty was alleviated. But, this success attracted attention and  the institution then had power, money, status, and influence.

The opportunists then move in. They are attracted to the potential to share in the power, money, status, and influence. The institution then takes on a life of its own, and the ideals and virtue ethics of the founders are squeezed out. In some sense, opportunism might be argued to be a consequence of secularisation. 

[Aside: two old posts considered a similar evolution, motivated by a classic article about the development of businesses.]

One indicator of the "success" of universities is how their graduates join the elite and hold significant influence in society. [Aside: ignoring the problem of distinguishing correlation and causality. Do universities actually train students well or just select those who will succeed anyway?]  Before (around) 1960, (mostly) only the children of the elite got to attend university. Demands arose that more people should have access to this privilege. This led to "massification" and an explosion in the number of students, courses, and institutions. This continues today, globally. Associated with this was more bureaucracy. Furthermore, the "iron triangle" of cost, access, and quality presents a challenge for this egalitarianism. If access increases, so does cost and quality decreases, unless you spend even more. It is wonderful that universities have become more diverse and accessible. On the other hand, I fear that for every underprivileged student admitted whose mind is expanded and life enriched, many more rich, lazy, and entitled students suck the life out of the system.

Metrics are pseudo-rational

Peter rightly discussed how the proliferation of the use of metrics to measure value is problematic, and reflects the "rationalisation" associated with bureaucracy (described by Weber). Even if one embraces the idea that "rational" and "objective" assessment is desirable, my observation is that in practice, metrics are invariably used in an irrational way. For example, managers look at the impact factor of journals, but are blissfully oblivious to the fact that the citation distribution for any journal is so broad and with a long tail that the mean number is meaningless. The underlying problem is that too many of the people doing assessments suffer from some mixture of busyness, intellectual laziness, and arrogance. Too many managers are power hungry and want to make the decisions themselves, and don't trust faculty who actually may understand the intellectual merits and weaknesses of the work being assessed.

The problems are just as great for the sciences as the humanities

On the surface, the humanities are doing worse than the sciences. For example, if you look at declining student numbers, threats of job cuts, political criticism, and status within the university. This is because science is associated with technology which is associated with jobs and economic growth. However, if you look at pure science that is driven by curiousity, awe, and wonder, then one should be concerned. There is an aversion to attacking difficult and risky problems, particularly those that require long-term investment or have been around for a while. The emphasis is on low-lying fruit and the latest fashion. Almost all physics and chemistry research is framed in terms of potential applications, not fundamental understanding. Sometimes I feel some of my colleagues are doing engineering not physics. In a similar vein, biochemists frame research in terms of biomedical applications, not the beauty and wonders of how biological systems work. 

Are universities destined for bureaucratic self-destruction?

Provocatively, Peter considered the potential implications of the arguments of historian and anthropologist Joseph Tainter concerning the collapse of complex societies. On the technical side, this reminded me of a famous result in ecology by Robert May, that as the complexity of a system (the number of components and interactions) increases, it can become unstable.

I don't think universities as institutions will collapse. They are too integrated into the fabric of modern capitalism. What may collapse is the production of well-educated (in the Renaissance sense) graduates and research that is beautiful, original, and awe-inspiring. This leads naturally into the following question.

Is the age of great discoveries over?

Peter briefly raised this issue. On the one hand, we are victims of our own success. It is amazing how much we now know and understand. Hence, it is harder to discover truly new and amazing things. On the other hand, because of emergence we should expect surprises.

There is hope on the margins

Peter did not just lament the current situation but made some concrete suggestions for addressing the problems, even though we are trapped in Weber's "iron cage" of bureaucracy.

• Re-balancing the structures of authority
• Finding a place for values discourse in the universities
• Develop ways of resolving differences with a sense of the rationality of Alisdair MacIntyre in mind

On the first, I note the encouraging work of the ANU Governance Project.

Peter also encouraged people to work on the margins. I also think that this is where the most significant scholarship and stimulus for reform will happen. A nice example is the story that Malcolm Gladwell tells in a podcast episode, The Obscure Virus Club.

What Americans might want to know about getting a job in an Australian university

Universities and scientific research in the USA are facing a dire future. Understandably, some scientists are considering leaving the USA. I have had a few enquiries about Australia. This makes sense, as Australia is a stable English-speaking country with similarities in education, culture, democracy, and economics. At least compared to most other possible destinations. Nevertheless, there are important differences between Australia and the USA to be aware of, particularly when it comes down to how universities function (and dis-function!) and how they hire people. 

A few people have asked me for advice. Below are some comparisons. Why should you believe me? I spent eleven years in the US (1983-1994) and visited at least once a year until 2018. On the other hand, there are some reasons to take what I say with a grain of salt. I have never been a faculty member in a US university. I retired four years ago from a faculty position in Australia. I actually haven't sat on a committee for almost ten years :). Hopefully, this post will prompt other readers to weigh in with other perspectives.

There are discussions in Australia about trying to attract senior people from the USA to come here. Whether that will come to anything substantial remains to be seen.

The best place to look for advertised positions is on Seek. 

Postdocs

This is where the news is best. Young people in the USA can apply for regular postdoc positions. Most are attached to specific grants and so involve working on a specific project. 

Ph.D. students

Most of the positions go to Australian citizens who get there own scholarship (fellowship) from the government. These are not tied to a grant or a supervisor (advisor) There are a few positions for international students, but not many. Usually they go to applicants with a Masters degree and publications.

Ph.D's are funded for 3 to 3.5 years. There is no required course work. Australian students have done a 4-year undergraduate degree and no Masters. This means tackling highly technical projects in theory is not realistic, except for exceptional students.

Faculty hiring is adhoc 

There is no hiring cycle. Positions tend to be advertised at random times depending on local politics, whims and bureaucracy. Universities and Schools (departments) claim they have strategic plans, but given fluctuations in funding, management, and government policy positions appear and disappear at random. Typically, the Dean (and their lackies), not the department, control the selection process, particularly for senior appointments. The emphasis is on metrics. Letters of reference are sometimes not even called for before short listing. Some hiring is done purely from online interviews and seminars.

Bias towards insiders 

People already in the Australian system know how to navigate it best. They may also already have a grant from the Australian Research Council and have done some teaching and (positive) student evaluations. They are known quantities to the managers and so a safer bet than outsiders. If you want to get a junior faculty position here (a lectureship) your chances may be better if you first come as a postdoc. However, there are exceptions...

Current funding crunches

Unfortunately, I fear the faculty market may be quite cool for the next few years. Many universities are actually trying to sack (fire) people due to funding shortfalls. These budget crises are due to post-covid, mismanagement, and the government trying to reduce international student numbers (due to the politics of a housing and cost-of-living crisis).

Australian Research Council

This is pretty much the sole source of funding in physics and chemistry. This is quite different to the USA where there were (pre-Trump) numerous funding agencies (NSF, DOE, DOD, ...).  They are currently reviewing and redesigning all their programs and so we will have to wait to see how this may impact the prospects of scientific refugees from the USA. (They used to have quite good Fellowship schemes for all career stages that were an excellent avenue for foreigners to come here). Some of my colleagues recommend following ARC Tracker on social media to be informed about the latest at ARC.

Thirty years ago, I came back to Australia from the USA. I had a wonderful stint doing science, largely because of generous ARC funding. Unfortunately, the system has declined. But I am sure it is better than being the USA right now.

There are many more things I could write about. Some have featured in previous rants about metrics and managerialism. Things to be aware of before accepting a job include faculty having little voice or power, student absenteeism, corrupt governance, and there is no real tenure or sabbaticals.

Lamenting the destruction of science in the USA

I continue to follow the situation in the USA concerning the future of science with concern. Here are some of the articles I found most informative (and alarming).

Trump Has Cut Science Funding to Its Lowest Level in Decades (New York Times). It has helpful graphics.

On the proposed massive cuts to the NSF budget, the table below [courtesy of Doug Natelson] is informative and disturbing. At the end of the day it is all about people [real live humans and investment in human capital]

APS News | US physics departments expect to shrink graduate programs [I was quite surprised the expect shrinking isn't greater].

From an Update on NSF Priorities

Are you still funding research on misinformation/disinformation?

Per the Presidential Action announced January 20, 2025, NSF will not prioritize research proposals that engage in or facilitate any conduct that would unconstitutionally abridge the free speech of any American citizen. NSF will not support research with the goal of combating "misinformation," "disinformation," and "malinformation" that could be used to infringe on the constitutionally protected speech rights of American citizens across the United States in a manner that advances a preferred narrative about significant matters of public debate.

The Economist had a series of articles in the May 24 issue [Science and Technology section] that put the situation concerning research and universities in a broader context. The associated editorial is MAGA’s assault on science is an act of grievous self-harm, featuring the graphic below.

I welcome comments and suggestions of other articles.

Remembering the student protestors who died 36 years ago

Memorial plaque in the Great Court of the University of Queensland today.

Lamenting the disintegration of elite USA universities

Elite universities in the USA have nurtured and enhanced my whole academic life. In 1983, I moved to the USA as an international student, commenced a Ph.D. at Princeton, and then worked at Northwestern and Ohio State. After I returned to Australia in 1994, I visited the USA every year for several weeks for conferences, collaborations, and university visits. Much of my research was shaped by ideas I got from those trips. This blog started through the influence of I2CAM, a wonderful institution funded by the NSF. My movement into chemical physics was facilitated by attending workshops at the Telluride Science Center. I deeply appreciate my colleagues (and their institutions) for their stimulation, support, interest, encouragement, and hospitality. 

My trips to the USA only ended with COVID-19, retirement, family health issues, and my new general aversion to international travel. Currently I would be too scared to travel to the USA, based on what I read in the Travel Section of The Sydney Morning Herald.

Most importantly, what I have learned and done has been built largely on intellectual foundations laid by people in these elite universities.  Other parts of the world have played a role too, but my focus here is the USA due to current political events leading to the impending disintegration of these universities.

I readily acknowledge that these universities have flaws and need reform. On this blog, I occasionally discussed issues, such as the obsession with money, metrics, management, and marketing. Teaching undergraduates and robust scholarship has sometimes become subsidiary. I have critiqued some of the flaky science published in luxury journals by groups from these universities.

Nevertheless, if something is broken you do not fix it by smashing it. Consider a beautiful ancient vase with a large crack. You do not restore the vase by smashing it and hiring your teenage cousin to make a new one.

Reading about what is happening raises multiple questions. What is really happening? Why is it happening? How significant is it? What might it lead to? How should individuals and institutions respond? 

Today when I was on the UQ campus it was serene and the challenges my colleagues are facing, as formidable and important as they are, seem trifling compared to what I imagine is happening on Ivy campuses right now. In passing, I mention that Australia is not completely immune to what is happening in the USA. Universities here that receive some research grant funding from the USA government have had it paused or cancelled.

I can't imagine what it would be like to be an international student at Princeton right now.

On the one hand, I do not feel qualified to comment on what is happening as I am so distant. On the other hand, I do want to try and express some solidarity with and appreciation of institutions and colleagues that have blessed me and the world. I make a few general observations. This is my advice, for what it is worth, to my younger self.

Protect your mental health. You and your colleagues and your institutional are encountering an existential crisis, perhaps like none encountered before. Don't live in denial. But also don't let this consume you and destroy you as a person or a community. Limit your intake of news and how much you think about it and discuss it. Practise the basics: exercise; eat, drink, and sleep well; get help sooner than later; limit screen time; rest.

Expect the unexpected. Expect more surprises, pain, uncertainty, instability, intra-institutional conflict, and disappointments. 

Get the big picture. This is about a lot more than federal funding for universities. There are broader issues about what a university is actually for. What do you want to preserve and protect? What are you willing to compromise on? Beyond the university, many significant issues are at stake concerning politics, democracy, economics, pluralism, culture, and the law. This is an opportunity, albeit a scary one, to think about and learn about these issues.

Make the effort to have conversations across the divides. Try to  have civil and respectful discussions with people with different perspectives on how individuals and institutions should respond to the current situation. Talk to colleagues in the humanities and social sciences. Talk to those with different political perspectives, both inside and outside the university.

Read widely. History is instructive but not determinative. I recommend two very short books that I think are relevant and helpful.

On Tyranny: Twenty Lessons from the Twentieth Century by Timothy Snyder.

The Power of the Powerless, by Vaclav Havel, first published in 1978 in the context of living in communist totalitarian Czechoslovakia. I have a Penguin Vintage edition which includes a beautiful introduction by Timothy Snyder, written in 2018, for a 40th Anniversary edition. 

I thank Charles Ringma for bringing both books to my attention.

What do you think? I would love to hear from people in US universities who are living through this.

An authoritarian government takes over universities: one case history

Adventures of a Bystander, by Peter Drucker, contains the following account. Drucker was a faculty member at Frankfurt University in 1933.

“[S]everal weeks after the Nazis had come to power, was the first Nazi-led faculty meeting at the University. Frankfurt was the first university the Nazis tackled, precisely because it was the most self-confidently liberal of major German universities, with a faculty that prided itself on its allegiance to scholarship, freedom of conscience, and democracy. The Nazis knew that control of Frankfurt University would mean control of German academia altogether. So did everyone at the University. 

Above all, Frankfurt had a science faculty distinguished both by its scholarship and by its liberal convictions; and outstanding among the Frankfurt scientists was a biochemist of Nobel Prize caliber and impeccable liberal credentials. When the appointment of a Nazi commissar for Frankfurt was announced around February 25 of that year and when not only every teacher but also every graduate assistant at the University was summoned to a faculty meeting to hear his new master, everybody knew that a trial of strength was at hand. … 

The new Nazi commissar wasted no time on the amenities…. [He] pointed his finger at one department chairman after another and said: ‘You either do what I tell you or we’ll put you into a concentration camp.’ 

There was dead silence when he finished; everybody waited for the distinguished biochemist. The great liberal got up, cleared his throat, and said: ‘Very interesting, Mr. Commissar, and in some respects very illuminating. But one point I didn’t get too clearly. Will there be more money for research in physiology?’ The meeting broke up shortly thereafter with the commissar assuring the scholars that indeed there would be plenty of money for ‘racially pure science’.”

I became aware of this chilling story through Peter Woit's blog who got it from a blog post by Adam Przeworski

Quantifying the obscurity of academic writing

 Occasionally The Economist publishes nice graphs capturing social and economic trends. Here is one.

It is part of a nice article

Academic writing is getting harder to read—the humanities most of all

The downward trend in the humanities and social sciences is dramatic and perhaps not surprising.

I was surprised that in the natural sciences the trend wasn't worse. The Flesch reading ease score goes from about 26 around 1960 to about 18 today. 

However, this metric misses a lot. It only measures the number of words per sentence and the number of syllables per word. Thus, it is not sensitive to the amount of technical jargon or to overall clarity.

Self-organised criticality and emergence in economics

A nice preprint illustrates how emergence is central to some of the biggest questions in economics and finance. Emergent phenomena occur as many economic agents interact resulting in a system with properties that the individual agents do not have.

The Self-Organized Criticality Paradigm in Economics & Finance

Jean-Philippe Bouchaud

The paper illustrates several key characteristics of emergence (novel properties, universality, unpredictability, ...) and the value of toy models in elucidating it. Furthermore, it illustrates the elusive nature of the "holy grail" of controlling emergent properties. 

The basic idea of self-organised criticality

"The seminal idea of Per Bak is to think of model parameters themselves as dynamical variables, in such a way that the system spontaneously evolves towards the critical point, or at least visits its neighbourhood frequently enough"

A key property of systems exhibiting criticality is power laws in the probability distribution of a property. This means that there are "fat tails" in the probability distribution and extreme events are much more likely than in a system with a Gaussian probability distribution.

Big questions

The two questions below are similar in that they concern the puzzle of how markets produce fluctuations that are much larger than expected when one tries to explain their behaviour in terms of the choices of individual agents.

A big question in economics

"A longstanding puzzle in business cycle analysis is that large fluctuations in aggregate economic activity sometimes arise from what appear to be relatively small impulses. For example, large swings in investment spending and output have been attributed to changes in monetary policy that had very modest effects on long-term real interest rates."

This is the "small shocks, large business cycle puzzle", a term coined by Ben Bernanke, Mark Gertler and Simon Gilchrist in a 1996 paper. It begins with the paragraph above. [Bernanke shared the 2022 Nobel Prize in Economics for his work on business cycles].

A big question in finance

The excess volatility puzzle in financial markets was identified by Robert Shiller: The volatility "is at least five times larger than it "should" be in the absence of feedback". In the views of some, this puzzle highlights the failings of the efficient market hypothesis and the rationality of investors, two foundations of neoclassical economics. [Shiller shared the 2013 Nobel Prize in Economics for this work]. 

"Asset prices frequently undergo large jumps for no particular reason, when financial economics asserts that only unexpected news can move prices. Volatility is an intermittent, scale-invariant process that resembles the velocity field in turbulent flows..." (page 2)

Emergent properties

Close to a critical point, the system is characterised by fat-tailed fluctuations and long memory correlations.

Avalanches. They allow very small perturbations to generate large disruptions.

Dragon Kings

Minsky moment

The holy grail: control of emergent properties

It would be nice to understand superconductivity well enough  to design a room-temperature superconductor. But, this pales in significance compared to the "holy grail" of being about to manage economic markets to prevent bubbles, crashes, and recessions.

Bouchaud argues that  the quest for efficiency and the necessity of resilience may be mutually incompatible. This is because markets may tend towards self-organised criticality which is characterised by fragility and unpredictability (Black swans).

The paper has the following conclusion

"the main policy consequence of fragility in socio-economic systems is that any welfare function that system operators, policy makers of regulators seek to optimize should contain a measure of the robustness of the solution to small perturbations, or to the uncertainty about parameters value.

Adding such a resilience penalty will for sure increase costs and degrade strict economic performance, but will keep the solution at a safe distance away from the cliff edge. As argued by Taleb [159], and also using a different language in Ref. [160], good policies should ideally lead to “anti-fragile” systems, i.e., systems that spontaneously improve when buffeted by large shocks."

Toy models

Toy models are key to understanding emergent phenomena. They ignore almost all details to the point that critics claim that the models are oversimplified. The modest goal of their proponents is simply to identify what ingredients may be essential for a phenomenon to occur. Bouchaud reviews several such models. All provide significant insight.

A trivial example (Section 2.1)

He considers an Ornstein-Uhlenbeck process for a system relaxing to equilibrium. As the damping rate tends to zero [κ⋆ → 0], the relaxation time and the variance of fluctuations diverge at the same rate. In other words, "in the limit of marginal stability κ⋆ →0, the system both amplifies exogenous shocks [i.e., those originating outside the system] and becomes auto-correlated over very long time scales."

The critical branching transition (Section 2.2)

The model describes diverse systems: "sand pile avalanches, brain activity, epidemic propagation, default/bankruptcy waves, word of mouth,..."

The model involves the parameter R0 which became famous during the COVID-19 pandemic. R0 is the average number of uninfected people who become infected due to contact with an infected individual. For sand piles R0 is the average number of grains that start rolling in response to a single rolling grain.

when R0 = 1 the distribution of avalanche sizes is a scale-free, power-law distribution 1/S^3/2, with infinite mean.

"most avalanches are of small size, although some can be very large. In other words, the system looks stable, but occasionally goes haywire with no apparent cause."

A generalised Lotka-Volterra model (Sections 3.3 and 4.2) 

This provides an analogue between economic production networks and ecology. Last year I reviewed recent work on this model, concerning how to understand the interplay of evolution and ecology.

A key result is how in the large N limit (i.e., a large number of interacting species/agents) qualitatively different behaviour occurs. Ecosystems and economies can collapse. 

 "any small change in the fitness of one species can have dramatic consequences on the whole system – in the present case, mass extinctions...

"most complex optimisation systems are, in a sense, fragile, as the solution to the optimisation problem is highly sensitive to the precise value of the parameters of the specific instance one wants to solve, like the Aij entries in the Lotka-Volterra model. Small changes of these parameters can completely upend the structure of the optimal state, and trigger large-scale rearrangements,..." 

Balancing stick problem (Section 3.4)

 The better one is able to stabilize the system, the more difficult it becomes to predict its future evolution! 

Propagation of production delays along the supply chain (Section 4.1)

An agent-based firm network model (Section 4.3)

This has the phase diagram shown below. The horizontal axis is the strength of forces counteracting supply/demand and profit imbalances. The vertical axis is the perishability of goods.

There are four distinct phases.

Leftmost region (a, violet): the economy collapses; 

Middle region (b, blue): the economy reaches equilibrium relatively quickly;

Right region (c, yellow): the economy is in perpetual disequilibrium, with purely endogenous fluctuations. 

The green vertical sliver (d) corresponds to a deflationary equilibrium

Phase diagrams illustrate how quantitative changes can produce qualitative differences.

Universality

The toy models considered describe emergent phenomena in diverse systems, including in fields other than economics and finance. 

Here are a few other recent papers by Bouchaud that are relevant to this discussion.

Navigating through Economic Complexity: Phase Diagrams & Parameter Sloppiness

From statistical physics to social sciences: the pitfalls of multi-disciplinarity

This includes the opening address from a workshop on "More is Different" at the College de France in 2022.

Straining gnats and swallowing camels on campus

The world is being run by accountants, lawyers, and marketing consultants. They work for corporations, universities, trade unions, and government. Some are "rent seekers" and parasites who project themselves as standing for justice and fairness.

We also live in a world where people are not allowed to make even small mistakes.

These painful realities were highlighted to me this week in an email some colleagues received from the President of their university.

"I am writing to advise staff about the outcome of a pay review initiated in October 2021 and the actions taken as part of this to further strengthen our pay systems and processes. 

The University commenced this external review to ensure our staff are paid accurately and in accordance with our Enterprise Agreement (EA) applicable at the time.

The review took 18 months. How much staff time and money was spent to engage these external consultants on this review? 

While staff were paid for the time they worked, the review identified 2 areas of our EA were not always correctly applied. These relate to the minimum hours of engagement for casual academic and casual professional staff and the use of a different pay rate for casual academic staff with a relevant PhD.

As a result, the University has determined that over a 7-year period (January 2017 to December 2023), an amount of $7.88 million (excluding superannuation and interest) should have been paid to 9743 staff. The median amount to be paid is $243.03.

Note. This corresponds to staff being underpaid by less than one dollar per week! 

I unreservedly apologise to those staff who have been affected by these errors – they should not have happened. I want to assure our community that affected staff will receive all the pay due, including superannuation and interest for the relevant period.

This week, we are writing individually to affected current staff outlining the payment due, with these payments to commence from 14 June.

We will also be writing individually to affected former staff outlining the payment due and the process for remediation.

A comprehensive program is underway to upgrade our systems and processes to further ensure ongoing pay accuracy. Actions being taken include the introduction of a whole-of-Univ timesheet system, compulsory training for managers and staff and additional fortnightly payroll reporting.

Does this mean faculty will now fill out time sheets? 

We are also investing further in our HR systems, with new time and attendance and payroll systems planned.

Sounds like a whole new layer of bureaucracy. 

Throughout this process we have worked closely with the Office of the Fair Work Ombudsman and have advised them of these outcomes.

Again, I apologise that this has occurred and reaffirm our commitment to ensuring staff are appropriately and accurately paid for the work they do on behalf of the University."

Meanwhile I don't hear of any external reviews or apologies for the treatment by university management of people such as Gerd Shroder-Turk, Drew Pavlou, Paul Frijters, or James Allan, ...

Two thousand years ago the following was written.

“Woe to you, teachers of the law and Pharisees, you hypocrites! You give a tenth of your spices—mint, dill and cumin. But you have neglected the more important matters of the law—justice, mercy and faithfulness. You should have practiced the latter, without neglecting the former. 

You blind guides! You strain out a gnat but swallow a camel.

Woe to you, teachers of the law and Pharisees, you hypocrites! You clean the outside of the cup and dish, but inside they are full of greed and self-indulgence."

The relevance of Labor Day to physicists and philosophers

This past Monday, May 8, was a public holiday in Queensland, marking Labor Day. I don't know why we don't celebrate it on May 1, but that does not matter.

In honour of the event, I post two relevant resources. The first resource is a moving video by Sabine Hossenfelder, who has carved out a post-academic income as a populariser of physics. The video is funny and sad, describing her own experience in academia leading to "Death of a Dream".

Sabine has many poignant observations about the dysfunctionalities of physics in academia, from the personal to the intellectual.

I find it sad that people who leave academia because they could not find a permanent job see themselves as a "failure." First,  most of the select few who get permanent jobs do so because they are at the right place at the right time, not because they are so much more brilliant and productive than others. Second, there is so much more to life than professional success. Finally, Sabine has been an incredible success. She has been able to popularise physics far beyond what has been achieved by others with big names and lots of resources. Furthermore, Sabine has made a significant contribution to the physics community by calling out hype and BS.

The second resource to mark Labor Day is an article, 

In Australian Universities, There Is No Such Thing as a Secure Job, by Danny Wardle. 

It puts a specific (alarming) incident in the broader context of the history of how and why the governance and management of Australian universities have been captured by the ideology of neoliberalism. This has been facilitated by the opportunism and vanity of mediocre academics who become "managers" with million-dollar salaries.

Physics on Netflix

The Netflix series, 3-body Problem, features physics and physicists throughout. I am not a big fan of science fiction, but watched the first episode, to try and get a sense of why the series is attracting so much attention. The opening scene (in the video above) is rooted in history. It depicts a "struggle session" during the Cultural Revolution, featuring the denunciation and killing of a physics professor, who is the father of the main character in the series.

For some more on the intellectual and political background see

Organized criticism of Einstein and relativity in China, 1949–1989, by Danian Hu

An emergentist perspective on public policy issues that divide

How is the whole related to the parts?

Which type of economy will produce the best outcomes: laissez-faire or regulated?

Can a government end an economic recession by "stimulus" spending?  

What is the relative importance of individual agency and social structures in causing social problems such as poverty and racism?

These questions are all related to the first one. Let's look at it from an emergentist perspective, with reference to physics. 

Consider the Ising model in two or more dimensions. The presence of nearest neighbour interactions between spins leads to emergent properties: long-range ordering of the spins, spontaneous symmetry breaking below the critical temperature, and singularities in the temperature dependence of thermodynamic properties such as the specific heat and magnetic susceptibility. Individual uncoupled spins have neither property. Even a finite number of spins do not. (Although, a large number of spins do exhibit suggestive properties such as an enhancement of the magnetic susceptibility near the critical temperature). Thus, the whole system has properties that are qualitatively different from the parts. 

On the other hand, the properties of the parts, such as how strongly the spins couple to an external field and interact with their neighbours, influence the properties of the whole. Some details of the parts matter. Other details don't matter. Adding some interaction with spins beyond nearest neighbours does not change any of the qualitative properties, provided those longer-range interactions are not too large. On the other hand, changing from a two-dimensional rectangular lattice to a linear chain removes the ordered state. Changing to a triangular lattice with an antiferromagnetic nearest-neighbour interaction removes the ordering and there are multiple ground states. Thus, some microscopic details do matter.

For illustrative purposes, below I show a sketch of the temperature dependence of the magnetic susceptibility of the Ising model for three cases: non-interacting spins (J=0), two dimensions (d=2), and one dimension (d=1). This shows how interactions can significantly enhance/diminish the susceptibility depending on the parameter regime.

The main point of this example is to show that to understand a large complex system we have to keep both the parts and the whole in mind. In other words, we need both microscopic and macroscopic pictures. There are two horizons, the parts and the whole, the near and the far. There is a dialectic tension between these two horizons. It is not either/or but both/and.

I now illustrate how this type of tension matters in economics and sociology, and the implications for public policy. If you are (understandably) concerned about whether Ising models have anything to do with sociology and economics, see my earlier posts about these issues. The first post introduced discrete-choice models that are essentially Ising models. A second post discussed how these show how equilibrium may never be reached leading to the insight that local initiatives can "nucleate" desired outcomes. A third post, considered how heterogeneity can lead to qualitative changes including hysteresis so that the effectiveness of "nudges" can vary significantly.

A fundamental (and much debated) question in sociology is the relationship between individual agency and social structures. Which determines which? Do individuals make choices that then lead to particular social structures? Or do social structures constrain what choices individuals make. In sociology, this is referred to as the debate between voluntarism and determinism. A middle way, that does not preference agency or structure, is structuration, proposed by Anthony Giddens.

Social theorists who give primacy to social structures will naturally advocate solving social problems with large government schemes and policies that seek to change the structures. On the other side, those who give primacy to individual agency are sceptical of such approaches, and consider progress can only occur through individuals, and small units such as families and communities make better choices. The structure/agency divide naturally maps onto political divisions of left versus right, liberal versus conservative, and the extremes of communist and libertarian. An emergentist perspective is balanced, affirming the importance of both structure and agency.

Key concepts in economics are equilibrium, division of labour, price, and demand. These are the outcomes of many interacting agents (individuals, companies, institutions, and government). Economies tend to self-organise. This is the "invisible hand" of Adam Smith. Thus, emergence is one of the most important concepts in economics. 

A big question is how the equilibrium state and the values of the associated state variables (e.g., prices, demand, division of labour, and wealth distribution) emerge from the interactions of the agents. In other words, what is the relationship between microeconomics and macroeconomics?

What are the implications for public policy? What will lead to the best outcomes (usually assumed to be economic growth and prosperity for "all")? Central planning (or at least some government regulation) is pitted against laissez-faire. For reasons, similar to the Ising and sociology cases, an emergentist perspective is that the whole and the parts are inseparable. This is why there is no consensus on the answers to specific questions such as, can government stimulus spending move an economy out of a recession? Keynes claimed it could but the debate rages on.

An emergentist perspective tempers expectations about the impact of agency, both individuals and government. It is hard to predict how a complex system with emergent properties will respond to perturbations such as changes in government policy. This is the "law" of unintended consequences.

“The curious task of economics is to demonstrate to men how little they really know about what they imagine they can design.”

Friedrich A. Hayek, The Fatal Conceit: The Errors of Socialism

I think this cuts both ways. This is also reason to be skeptical about those (such as Hayek's disciples) who think they can "design" a better society by just letting the market run free.

The challenge of useful data in the social sciences

A major challenge for the social sciences is obtaining data that is reliable, gives significant insight, and could be used to test theories. Each week I read The Economist. Many of their articles feature graphs of social or economic data. To me, some of the graphs are just random noise or show marginal trends that I am not convinced are that significant. But other graphs are quite dramatic or insightful. Previously, I posted a famous one about smoking.

This week I saw the graph below in The New York Times, as part of a long article, Childbirth Is Deadlier for Black Families Even When They’re Rich, Expansive Study Finds, based on this preprint.

The data clearly shows the distressing fact that "The richest Black women have infant mortality rates at about the same level as the poorest white women."