Two Views of the State
Huntington generally treats political order as a positive feature; Scott is more attuned to the way in which the state endangers freedom.
Both make from great reading.
Read Huntington: https://t.co/ltYaAJOVpv
Read Scott: https://t.co/RaTpxNZqZu
More on Causality
Mario Bunge's book provides a wide-ranging study of causality. He discusses causality from a philosophical perspective and considers matters of ontology.
For information on the book: https://t.co/ybxvfFuagn
I am bewildered, and not very impressed, by the visceral, naked, irrational hatred spat out by some defenders of Jason Arday. If a Cambridge professor is accused of being an unqualified charlatan, the accusation might be racially motivated. On the other hand it might not, depending on the evidence. The correct question to ask is not, ”What is the colour of his skin” but “Is it in fact true that he is an unqualified charlatan?” Please examine the evidence before leaping to the assumption of racism.
As for the idea that journalists “piled in on him” and “hounded him to his death”, most attacks were against Cambridge University. Jason himself was widely regarded as an unfortunate victim of foolish promotion way beyond his ability to cope. In appointing him to a professorship for which he was manifestly unqualified – in ludicrously describing him as “the best in the world” – certain senior members of the university showed a level of patronising condescension towards black people that could fairly be described as racism, while at the same time making him tragically vulnerable to such attacks as came his way.
Some equations are more than symbols on a page. They changed the way we understand the universe.
From Pythagoras proving a² + b² = c² around 530 BC to Einstein introducing E = mc² in 1905, these 17 equations shaped mathematics, physics, engineering, computing, and modern technology.
MAMDANI’S PROMISE
Mamdani wants five city-owned grocery stores where a core basket of everyday food will sell at 30% below “typical retail prices” for an entire month. The city says the plan saves the average family about $1,000 a year.
INTENTIONS ARE NOT RESULTS
Over 40% of New York families say they struggle to afford food. Friedman would take the problem seriously while separating intentions from consequences. Government intervention, he and Rose Friedman warned, “is subject to laws of its own” and may produce unintended results.
THE HIDDEN BILL
That 30% Mamdani has promised has to come from somewhere. A lower shelf price does not erase the remaining cost. Taxpayers absorb what shoppers do not pay. Friedman would ask whether groceries became cheaper, or whether part of the bill merely changed hands.
THE ARBITRAGE PRIZE
The 30% gap also creates an arbitrage prize. A reseller can buy subsidized goods cheaply and sell them elsewhere. Purchase limits and resale bans may restrain this trade, but they replace open market access with rationing and government control.
WHERE SCARCITY AND THE BILL APPEAR
The plan is not a citywide price ceiling. Yet the subsidized prices will raise the quantity demanded. If inventories or budgets cannot expand accordingly, queues, stockouts, or purchase limits will follow.
FRIEDMAN’S RETORT
Friedman’s answer would be direct: Mayor, you can legislate the price printed on a shelf or lease, but not abolish the scarcity beneath it. If you want more affordable groceries, remove barriers to supply, and leave the price system alone!
Starting September 2026, Google will block any Android app whose developer hasn't registered and provided government ID. This affects every Android device worldwide. Learn more: https://t.co/aoVyY82yoP @AlteredDeal#KeepAndroidOpen
Bayes’ theorem is probably the single most important thing any rational person can learn.
So many of our debates and disagreements that we shout about are because we don’t understand Bayes’ theorem or how human rationality often works.
Bayes’ theorem is named after the 18th-century Thomas Bayes, and essentially it’s a formula that asks: when you are presented with all of the evidence for something, how much should you believe it?
Bayes’ theorem teaches us that our beliefs are not fixed; they are probabilities. Our beliefs change as we weigh new evidence against our assumptions, or our priors. In other words, we all carry certain ideas about how the world works, and new evidence can challenge them.
For example, somebody might believe that smoking is safe, that stress causes mouth ulcers, or that human activity is unrelated to climate change. These are their priors, their starting points. They can be formed by our culture, our biases, or even incomplete information.
Now imagine a new study comes along that challenges one of your priors. A single study might not carry enough weight to overturn your existing beliefs. But as studies accumulate, eventually the scales may tip. At some point, your prior will become less and less plausible.
Bayes’ theorem argues that being rational is not about black and white. It’s not even about true or false. It’s about what is most reasonable based on the best available evidence. But for this to work, we need to be presented with as much high-quality data as possible. Without evidence—without belief-forming data—we are left only with our priors and biases. And those aren’t all that rational.