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The Beauty Of Settled Science
Commenters convinced me I made a subtle mis-step in my framing of Psychology Research Is Mostly Fine. My framing emphasized that social priming studies had failed to replicate, but that many other subfields of psychology hadn’t. This naturally led commenters to point to failed replications in other subfields. Although none of these were as bad as social priming, few or none were entirely problem-free. Instead of emphasizing the difference between social priming and other subfields, I should have emphasized the difference between settled science and novel research. Here are some of my favorite psychology findings: The brain is sculpted by reinforcement learning, and a key driver of this learning is a prediction-error-based algorithm located in the nucleus accumbens and implemented through dopamine. Psychedelic drugs exert their effects through 5-HT2A receptors, pointing to a role for these receptors in some sort of construct like the balance between priors and new evidence. Certain cognitive functions are localized to certain brain areas (for example, impulse control to the frontal lobes; linguistic structure to Broca’s area, linguistic meaning to Wernicke’s area. But injure one of these areas, or render a certain function useless (eg a blind person having no more use for their visual cortex), and these mappings can gradually shift - suggesting that neurons are general-purpose compute whose specialization is a contingent fact about convenience and efficiency rather than a necessity. Most personality traits and general capabilities are about 50% genetic and 50% random, with little role for family environment or childhood history, with a few notable exceptions like partisan preference. Recent research complicates this story, but the further you go from this basic picture, the gnarlier the chains of indirect causation you require. Neurons fire together in “brain waves”, whose exact frequency corresponds with the character of consciousness; These divide neurons into natural subpopulations and linked graphs. The gamma rhythm corresponds surprisingly well to items in conscious awareness. GABA receptors seem to be involved in something like relaxation. By hitting different GABA receptors in different ways, you can modulate the exact type of relaxation you produce. Hitting GABA-A directly is too powerful and can cause dangerous levels of sedation, but allosteric modulation of GABA is an incredibly fruitful strategy that underlies drugs from benzos to barbituates to alcohol. If you know your GABA-A subunits, you can target specific subtypes of relaxation; for example, Ambien hits GABA-A1 and induces sleep. Memory divides somewhat fuzzily into bins of immediate-sensory, short-term, and long-term, with separate retrieval and storage functions, and separate systems for declarative vs. procedural learning. These can be harmed selectively, usually by hippocampal injury, so that some patients can remember their life stories but not form new long-term memories, or learn new skills like bike-riding but not new facts. The exact substrate of memory is unclear but seems to involve new synaptic connections between neurons in at least some way. The ability of modern psychology and psychiatry to treat mental illness is real but limited. SSRIs work for half or slightly fewer than half of patients; antipsychotics work with extreme side effects; benzodiazpines work but produce addiction and tolerance in many (not all) people. Most supplements are stuck in Poor Quality Study Replication Crisis Hell, but melatonin and l-theanine stand out as especially promising. Psychotherapy works with moderate effect size, but (with a few exceptions) seems to be more about the relationship with the provider than the details of the therapy itself. Mental hospitalization can sometimes defuse immediate crises but work less well than mental hospitals would like, with some studies showing overall negative effects. Schizophrenia is mostly genetic, but risk also increases with prenatal infection (especially rubella) and obstetric complications; there is suggestive evidence for roles of social stress and drug use (with psychedelics and marijuana making things worse, and nicotine if anything making things better). Bipolar and schizophrenia are so closely linked on a pathophysiological level that it seems like they might be the same disease; on the clinical level, they do seem to follow two separate courses/prognoses but can sometimes surprise clinicians by eg someone who seemed condemned to permanent schizophrenia unexpectedly recovering. The brain’s native reinforcement learning algorithms cash out in the phenomena of classical and operant conditioning; different reinforcement schedules reinforce at different levels, which can be exploited by bad actors to make especially compelling products (eg slot machines). None of these are immune to doubt. A few are speculative; one or two are genuinely unorthodox. But they’re all a step above one p = 0.049 paper that might not replicate. If they get overturned, they’ll be overturned by the same sort of genuine scientific shift that replaced Ptolemy with Copernicus or Lamarck with Darwin, not some sort of sordid discovery about someone entering random numbers into a spreadsheet. In 2008, Eliezer Yudkowsky wrote about The Beauty Of Settled Science: If you only care about scientific issues that are controversial, you will end up with a head stuffed full of garbage. The media thinks that only the cutting edge of science is worth reporting on. How often do you see headlines like “General Relativity still governing planetary orbits” or “Phlogiston theory remains false”? So, by the time anything is solid science, it is no longer a breaking headline. “Newsworthy” science is often based on the thinnest of evidence and wrong half the time—if it were not on the uttermost fringes of the scientific frontier, it would not be breaking news. Scientific controversies are problems so difficult that even people who’ve spent years mastering the field can still fool themselves. That’s what makes for the heated arguments that attract all the media attention. Worse, if you aren’t in the field and part of the game, controversies aren’t even fun. Don’t be embarrassed to read elementary science textbooks, either. If you want to pretend to be sophisticated, go find a play to sneer at. If you just want to have fun, remember that simplicity is at the core of scientific beauty [...] A steady diet of science news is bad for you: You are what you eat, and if you eat only science reporting on fluid situations, without a solid textbook now and then, your brain will turn to liquid. Psychology isn’t centrally the new paper in Annals Of Recently-Breaking News saying that an n=5 study showing that large portion sizes increase support for terrorism. Psychology is centrally ideas like brain waves, GABA receptors, reinforcement learning, twin studies, and connectionism. People who think differently are worrying too much about BREAKING NEWS!!!, and should stop. The key distinction isn’t “recent research in social psychology” vs. “recent research in cognitive/bio/behavioral psychology”, as my essay last week unfortunately implied. It’s recent research in general vs. the deposit of settled science, battle-tested hypotheses, and carefully-earmarked speculation. And part of the reason social priming in particular was such a disaster was that it defied that heuristic, building itself up over hundreds of studies until it approached or even entered the pantheon of settled science - before collapsing (5-HTTLPR was also sort of like this). This isn’t a claim that settled science is always right - Freud was “settled science” for a long time - just that there’s an intuitive distinction between the level of credence you should have in the existence of power posing vs. the existence of Broca’s Area. (I compounded this error by calling the last post “Psychology Research Is Mostly Fine”, which suggested I was talking about the new research rather than the settled science. I actually meant to distinguish between research-psychology-the-field vs. clinical-psychology-aka-therapy, but this framing unintentionally pushed against the point I wanted to make) Some commenters on the previous article understood this point, but challenged its weight. It’s very cool, they said, to know how many neurons are in which brain lobe, but the main way that Psychology affected their lives was through bad clickbait studies used to buttress dumb policies; some p = 0.049 study says that exposure to microaggressions makes minorities’ brains shrivel into raisins, and now their company has to implement punitive DEI or be sued for hazardous work conditions. I won’t dispute this as an accurate description of how the sausage gets made, but it’s worth examining the trains of thought that connect this observation to a campaign against psychology in general: The dumb woke psychology was wrong and bad, and I don’t have good heuristics for distinguishing dumb woke psychology from other psychology, so I’m going to assume it’s all wrong and bad. The dumb woke psychology was wrong and bad; it seems useful to punish/discredit psychology as a whole to assist my campaign against it, so for propaganda purposes I will try to discredit psychology as a whole. To people in the first camp, my response is: come on, your heuristics aren’t that bad. “Microaggressions makes minorities’ brains shrivel up like raisins” is in the woke category; “the hippocampal theta rhythm seems to be associated with both memory and pathfinding, suggesting an unexpected yet surprisingly compelling relationship between the two” is in the not-woke category, don’t play dumb here. To people in the second camp, my response is: deliberately exaggerated propaganda campaigns are bad and this is a confession, not an excuse. Inability to view science through anything but a political lens was what got us into this problem; doubling down on it is a temporary solution but a recipe for permanent disaster. If you pronounce entire fields of science to be acceptable collateral damage in your campaign against bad political actors, you will alienate not just scientists but patients, clinicians, and general lovers of truth. Instead, you can say the thing you mean - that woke partisans shouldn’t try to occupy and exploit the otherwise-noble science of psychology for their own political gain - and wage the same campaign with a halo rather than a comic-book-villain goatee. From the font of oracular wisdom that is Weird Sun Twitter: [ Vessel Of Spirit@VesselOfSpirit i love you all conditionally but i love the good part of you unconditionally. even if it becomes a very small part 2:11 AM · Jan 22, 2015 1 Reply · 5 Reposts · 29 Likes ](https://x.com/VesselOfSpirit/status/558084551772471298) This is how I feel about psychology1, too, but with a touch more optimism. The good part of psychology is enormous, a hoard of endless treasures. You just have to look past the headlines! 1 To play devil’s advocate - should one always be so magnamious? Astrology? Phrenology? These seem different in that their entire orientation was flawed from the start; they didn’t simply fail to find the correct constellation-personality connections, the whole project of searching for connections between constellations and personality was doomed from the start. More difficult might be asking the same question about education research, which is notoriously bad. I don’t know enough about education research to know if there’s some settled science of correct and enlightening results lurking in the background beyond the day-to-day froth of poorly-conducted and politically-motivated studies. I think if it’s 90% bad, 10% good, it’s correct to call it bad as a compact way of communicating a useful truth; I think psychology is better than that, but admit it’s a tough judgment call.
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Does public health *need* MAHA?
Last week, our friend Dr. Craig Spencer sparked an ongoing volatile discussion with his Atlantic article “Public Health Needs MAHA.” Some have come out in strong dissent, others are cheering, and others are simply lamenting that we find ourselves in such a divided world to begin with. We will dare to dip our toes in these controversial waters, too. Does public health need MAHA? We think in some ways yes, and in other ways, no. MAHA leaders versus the everyday MAHA supporter The vitriol in this debate mostly comes from one collapsed distinction: the leadership of MAHA is not necessarily the same as the people who support it. Say “MAHA” and most people picture RFK Jr. Fair enough, as he coined the term and holds most of the power. And, yes, some MAHA followers treat Kennedy as something close to a saint. But talk to the grassroots, and it’s not a monolith. They’re Republicans, Democrats, and Independents. People who distrust vaccines and vaccine supporters. It’s a wide, eclectic coalition. The data backs this too: 4 in 10 Americans support the movement—that’s a lot of people! But according to polls, vaccines and medical choice (the issues most tied to Kennedy personally) are cited by only 4% as their reason for supporting the movement. For many, the motivations are much broader. Many MAHA supporters are signing up for the idea that “something needs to change” with health in this country. They’re asking good-faith questions about corporate influence on our health systems, health care costs, nutrition, chemicals, and clean air and water. These are all questions that plenty of public health professionals recognize as legitimate and also care about very deeply. Blurring the lines between the leadership and grassroots does real damage in two important ways: It hands the 4 in 10 exactly the narrative already fed—that the health ecosystem doesn’t listen, doesn’t care, and paints every critic with the same brush. It gives the actual bad actor more power. RFK Jr. has done irreparable damage and can’t be trusted. What the MAHA movement gets right A healthy population is something the public health field was literally built on, and many of these topics are things we have dedicated our lives to. Yet the MAHA movement has captivated nearly half the country in a way the public health establishment has failed to achieve. So that means MAHA is doing something right. Some of it may be timing (after a Covid-19 pandemic and deep frustration and mistrust with institutions). The movement also does three other things really well: 1. It gives a new, louder voice to system failures. While MAHA is not a monolith, one theme stays consistent across their stories: the system failed them. For some, it was the system that flooded their communities with opioids and then walked away. For others, it was the system that let their business collapse during Covid with no safety net in sight. For others still, it was the system that failed to help them manage a complex chronic illness, bouncing them from physician to physician without any real answers. And in many ways, our health ecosystems are failing Americans. Why are medical bills so incomprehensible? Why do some kids get a healthy school lunch and others don’t? Why do an epidemiologist and a MD/PhD student have to start newsletters in the middle of the biggest public health emergency in a century, just so people can get straight information? Because the systems failed. This deep-seated frustration driving many Americans to search for solutions elsewhere needs to be recognized. 2. MAHA has brilliant comms central to their efforts. MAHA figured out something most health institutions still have not: the information landscape changed. It’s participatory now, not top-down; influence runs through many nodes in a community, not one institution; and storytelling and telling audiences “what you really think” moves people more than data dumps do. MAHA goes where audiences are listening, using podcasts, social media, and memes in ways most health institutions would scoff at—but it works. 3. They are very good at organizing. A MAHA meeting feels like a rally: energy, speakers, music, and most importantly, an action for everyone. Someone’s writing the next policy brief, someone’s seeding a narrative, someone knows the next legislative deadline, someone’s sending the text messages for a campaign. None of this is new (ask the civil rights movement), but MAHA knows it works and has capitalized on it. What MAHA gets wrong This list could be much longer, and this newsletter has spent a lot of time covering it, but here are a few things: Poor use of scientific evidence. This is the fundamental problem with many MAHA policies: the hype outpaces the science, and experts are often villainized for pointing this out. MAHA leadership has traded real solutions for cheap wins. For example, instead of taking on the powerful food industry and passing real reforms, it has celebrated french fries made of beef tallow and taken out artificial dyes from still very sugary children’s cereal. These changes won’t move the needle on America’s diet. MAHA leadership has tried to dismantle vaccine access in the U.S. While many MAHA supporters emphasize other issues, the effort to change vaccine policy has become MAHA’s signature effort. This is not surprising given RFK Jr.’s extensive track record campaigning against vaccines. It has rallied behind the wrong leader. RFK Jr. has a decades-long track record of villifying doctors, scientists, and public health workers, well before he became HHS secretary. He is known for his decades-long work sowing distrust in vaccines as well as life-saving treatments like antiretroviral therapy for HIV. This is not a serious person who can move the needle on health in the U.S, and he has already done serious damage. Public health needs more than defense Defending the evidence is absolutely necessary so health in the U.S. doesn’t move further backward. The public health establishment is very good at defense. The problem is this defense often sounds like defending the status quo, which has failed many people. Public health needs to offer an alternative to RFK Jr.’s MAHA—one that is rooted in evidence, truly listens to and addresses people’s frustrations, and has innovative solutions and the courage to change the systems. How do we get there? Find common ground. Do you know what most people care most about? The abysmal cost of healthcare. Start there. Fight for the human loudly. Too often, communications and engagement center on science with a capital S, funding mechanisms, or the CDC/FDA/NIH. Not the person. So the public doesn’t see themselves in it. Instead, they see people fighting for the very powerful systems that they feel negatively impact their health and well-being. Let the public feel and hear that you see their frustrations, you get it, and you’re fighting for them within the system. Recognize when pro-science messages are alienating people. Facts absolutely matter, but angrily venting only alienates people further. Our friend Elisabeth Marnik recently wrote a New York Times article about her experience growing up unvaccinated and how listening and empathetic conversation are the only ways to reach people that really work (a position backed by communication science). Her comments section was full of hateful comments from pro-vaccine individuals attacking her for daring to suggest we approach vaccine-hesitant individuals with empathy. It is possible to both stand firm behind scientific evidence and empathize with people who don’t trust it. Lean into politics smartly. Often, public health has shied away from politics: Don’t touch it, lest you get burned. But this fails to recognize that the third rail is what fuels the train: who is elected determines our budgets, our priorities, and our authority. Being political means being very savvy in strategy on both sides of the aisle, knowing your audience, and recognizing that political capital is as scarce as financial resources and needs to be allocated accordingly. Bottom line So does public health need MAHA? That’s not really the right question. Public health has a responsibility not to dismiss 40% of the country who feel heard by this movement and are frustrated that the system has failed them. And it has a responsibility to stick to the evidence and recognize MAHA leadership for what it is: a danger to our nation’s health. Both can, and should, be done. Love, YLE and KP A big thanks to Craig Spencer, who had the courage to put his neck out there to start a much-needed discussion at such a critical moment—one that is determining the identity of an entire field. Kristen Panthagani, MD, PhD is completing an emergency medicine residency and research fellowship focusing on health literacy and communication. In her free time, she writes the newsletters You Can Know Things debunking health myths and rumors and The Public Health Roundup. Views expressed belong to KP, not her employer. Your Local Epidemiologist (YLE) comprises a team of experts, ranging from physicians to immunologists to epidemiologists to nutritionists, working together with one goal: to “translate” ever-evolving public health science so that people are well-equipped to make evidence-based decisions. The YLE suite of newsletters reaches over 475,000 people across more than 132 countries. This newsletter is free to everyone, thanks to the generous support of fellow YLE community members. To support the effort, subscribe or upgrade below: Subscribe
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The new "science golden age" looks suspiciously like a grift
This edition of PN is made possible by paid subscribers. Become one ⬇️ 🚀 Subscribe to PN 🚀 The Trump regime is trying to usher in a “Golden Age in Science” where scientific research is run like a Trump family business, artificial intelligence is all that matters, profit is everything, and expertise is for chumps. Or at least that’s the vision emerging from a new 123-page “Report to the President” from Michael Kratsios, the Director of the White House Office of Science and Technology Policy. In a normal administration, you could probably skip over learning about a science policy document — but this is no normal administration, and this is no normal science policy document. Instead, it’s Trump’s attempt to end the actual golden age of science that was kicked off in 1945 with the publication of '“The Endless Frontier” by Vannevar Bush. [ ](https://www.publicnotice.co/p/harmeet-dhillon-portland) [ Harmeet Dhillon demonstrates danger of posting through it ](https://www.publicnotice.co/p/harmeet-dhillon-portland) Liz Dye · Jul 29 [ Read full story ](https://www.publicnotice.co/p/harmeet-dhillon-portland) Bush, at President Franklin Delano Roosevelt’s request, laid out a vision of federal support for science that centered on funding universities to do basic research, saying that as long as those institutions were “vigorous and healthy and their scientists are free to pursue the truth wherever it may lead, there will be a flow of new scientific knowledge to those who can apply it to practical problems in Government, in industry, or elsewhere.” Kratsios’s report is supposed to be the successor to Bush’s, and even apes the format, but this isn’t really a document about science policy. It’s one about ending science research as we know it in favor of shoveling cash at big tech companies. While it might be temping to wave this away as an aspirational policy document, Trump has already begun to shift billions in research funds to AI projects and has taken a hatchet to science funding across the board. He’s teed up the shift Kratsios proposes here, and since neither Congress nor the Supreme Court seem inclined to stop him from doing whatever he wants with taxpayer money, it isn’t doomering or hyperbole to say we are staring down the barrel of a world where the only “science” the government intends to support is for-profit tech and defense advancements. Science for dummies Part of how you can tell this isn’t a document about science is that you are immediately faced with an absolute wall of business-speak of the worst sort. Did you know we must “tightly couple our science and technology enterprises to ensure that groundbreaking ideas invented in the United States are rapidly prototyped, tested, manufactured, and scaled domestically”? You do now! That tone isn’t surprising, because Kratsios has no background in science or research. He has a bachelor’s in political science and spent most of his career working for Peter Thiel at Thiel Capital. After a stint in the first Trump administration as Chief Technology Officer, where he also did not do any science, Kratsios was tasked in 2020 with overseeing the Pentagon’s research budget for a brief time, a position that, as the Wall Street Journal put it, “carries a great deal of power in terms of dictating investment allocations.” He spent the Biden years at Scale AI as “head of strategy,” which you will also note is neither a science nor a research job. But Scale AI has contracts with the Department of Defense and, as the Washington Post wrote in 2023, “has been aggressively pitching itself as the company that will help the US military in its existential battle with China.” And now you have the necessary background for our new golden age, which is going to be a golden age of taking money away from scientists and universities and giving it to companies like Scale AI. A note from Aaron: Working with brilliant contributors like Lisa takes resources. If you aren’t already a paid subscriber, please become one to support our work. 👇 Subscribe In a genuinely galling move, Katsios spends a lot of time slamming universities because of “administrative burdens on researchers” and the “well-documented inefficiencies” in academia, the message being that those damn universities waste the time of amazing researchers with paperwork. Except it’s the administration that is attempting to impose inefficient, unnecessary burdens on those researchers with a proposed Office of Management and Budget rule that would require senior political appointees to approve every science grant and ensure it aligns with Trump’s personal priorities. Researchers would also have to seek prior government approval to attend conferences or publicize their research. And political appointees could terminate any grant at any time if they feel like it. [ ](https://www.publicnotice.co/p/omb-rule-science-funding) [ The murder of expertise ](https://www.publicnotice.co/p/omb-rule-science-funding) Lisa Needham · Jun 11 [ Read full story ](https://www.publicnotice.co/p/omb-rule-science-funding) But when it comes to AI, we’re going to “restore permissionless innovation.” The report proposes to give lucky ducky innovators a pile of cash up front for grants lasting five years or longer, saying “awards should be fully-funded in year one, with all resources earmarked upfront, to minimize administrative burdens and reduce pressure for researchers to generate intermediate results to secure continued funding.” Yeah, wouldn’t want to have to make the Very Special Tech Bros show results or get money parceled out year by year like the plebes at universities. The report also proposes that we should have “fast grants” with “simplified applications requiring just a few pages of writing” because that is definitely how science works, just writing a bit off the dome and getting some cash. [ ](https://www.publicnotice.co/p/trump-ai-action-plan-altman-llms) [ Tech elites are turning AI into ChatGPTrump ](https://www.publicnotice.co/p/trump-ai-action-plan-altman-llms) Paul Waldman · July 29, 2025 [ Read full story ](https://www.publicnotice.co/p/trump-ai-action-plan-altman-llms) Oh, and we should have prizes and challenges, where multiple teams compete. The proposed prizes include incentives like “advance procurement commitments,” which means the federal government agrees to buy whatever is being developed. There’s also “regulatory fast-tracking,” making sure all those great AI thingies don’t have to wait too long to be unleashed on a market. These aren’t incentives to do science. These are incentives to develop things with tax dollars that you can then sell to the government for more tax dollars. In the suggestion that might be the most unhinged, the most very opposite of how both government and research work, our new age will include “golden tickets.” That’s where an individual reviewer in an agency — yes, just one person — can “recommend unconventional proposals that may not pass consensus-driven review panels” because somehow this will “surface valuable ideas too divisive for committees and attract higher quality reviewers by empowering them to exercise independent scientific judgment.” Yes, that’s saying that a random person in an agency should be able to shovel money at some idea even if it can’t pass a review panel, and that the opportunity to do so will attract better employees because apparently all the best minds in science are chomping at the bit to be allowed to unilaterally fund AI research based on their personal vibes. But that isn’t at all how actual science works, and actual scientists aren’t unhappy about review panels. They work collaboratively, not siloed in some secret race to create the next AI chatbot. A 2020 study by the National Bureau of Economic Research examined whether peer review panels succeed in helping agencies predict which research ideas will best advance science. Peer review was better at finding “diamond in the rough” applicants than a single government program official. How about that. Trump always wants a taste It’s painfully clear that what Katsios is trying to do here is turn the whole of government science research and funding into the sort of “move fast and break things” paradigm that is the hallmark of big tech. That method works to line the pockets of tech executives, but it isn’t science. There’s a reason the government funds different kinds of research than private tech companies do. What Katsios either fails to understand or deliberately ignores is that the federal government is the main funder of basic research precisely because it can take a long time for it to bear fruit and is not intended to be profitable as such. “Basic” here does not mean rudimentary or simple, but rather research that is designed to advance scientific knowledge instead of achieving a specific outcome or product. Big tech companies don’t widely fund that sort of research, because it doesn’t make them money. Industry dollars account for only about 20 percent of basic research funding, while the government contributes around 60 percent. Big tech companies and startups do, however, rely on and benefit from that basic research. A 2019 study found that 35 percent of all patents obtained by venture-backed startups from 1976 to 2016 cited federally supported research. Basic research funded by the NIH contributed to every single drug the FDA approved from 2010 to 2016. [ ](https://www.publicnotice.co/p/trump-saudi-nuclear-deal) [ The Saudi nuclear farce and governance by whim and meme ](https://www.publicnotice.co/p/trump-saudi-nuclear-deal) Noah Berlatsky · Jul 27 [ Read full story ](https://www.publicnotice.co/p/trump-saudi-nuclear-deal) Unlike inventing the next ChatGPT, actual science is slow and iterative. Government funding of research that, on its face, would not appear to lead to any big new invention is actually what underpins those big new inventions. If the government hadn’t funded research into desert lizard venom, we wouldn’t know about semaglutide, and we wouldn’t have Ozempic. If research scientists hadn’t studied how bees optimize nectar foraging within a colony, we wouldn’t have the algorithm that assigns internet traffic across computer servers. The report assiduously ignores that a symbiotic, profitable relationship between the federal government, universities, and private companies already exists. Each federal research dollar generates about $1.50 to $3.00 in long-term economic benefits. The $36 billion the government awarded in NIH research funding in fiscal year 2025 generated $94 billion in new economic activity. Trump’s proposed new golden age is intended to strip those billions from universities, resulting in the dismantling of departments and the shuttering of labs. But Katsios has a plan for that: Universities should just become trade schools to churn out no-show STEM degrees! “Require universities and community colleges to embed practical technical training and externships into STEM curricula. Let hands-on experience and industry credentials count toward degrees.” It’s quite the feat to, on the one hand, strip schools of funding for scientific research while simultaneously demanding to control what is taught and, oh, also, colleges need to give degrees to employees at big tech companies just for being employees at big tech companies. The new golden age would also exacerbate the brain drain Trump’s policies have already caused. Nature found that in the first quarter of 2025, US scientists submitted 32 percent more job applications abroad than in 2024. A March 2025 poll by Nature of roughly 1,600 scientists found that over 1,200 said they were considering leaving the country. Europe is investing $565 million to make it a “magnet for researchers” and provide funding for scientists who relocate. The new golden age is also about embedding Trump’s xenophobia into the fabric of American science. The report complains of an “over-reliance on foreign students” that “creates a security challenge our institutions are ill-equipped to address” and that a “reliance on foreign talent sidelines American students.” This is, to put it mildly, nonsense. International students pay far higher tuition and often receive no financial aid. Their tuition dollars are what make it possible for American students to get financial aid. In the 2023-2024 school year alone, international students contributed $43.8 billion to the US economy and supported over 378,000 jobs. Those 1.1 million international students accounted for only six percent of the total number of students in higher education that year, but were such an economic engine that for every three international students, one job was created or supported. It’s impossible not to wonder whether part of Trump’s loathing for universities and their leading role in scientific research is that there is no way for him to corrupt the process and make money off it in the same way he can by giving millions and billions to Silicon Valley types who, in turn, give him millions in cash. There’s no way for his children to invest in universities that the government then gives no-bid contracts to, fattening the family’s bottom line, which is pretty much the Trump sons’ current venture capital practice. Trump and Katsios’s view of science is narrow, cramped, and wrong. We’re not in a crisis, we’re not a failed state. We’ve been a science superpower for decades, and the only thing that threatens that is Donald Trump. Tech bros are already living high off the hog in this administration. They don’t need any more of our tax dollars. Hopefully this new golden age never comes to pass. Thanks for reading Public Notice. This post is public so feel free to share it. Share We’ll be back with more tomorrow. If you appreciate today’s PN, please do your part to keep us free by signing up for a paid subscription. 🚀 Subscribe to PN 🚀 Thanks for reading, and for your support.
After Hobbes vs Rousseau: Politics must move beyond human nature
Since the great debate between Hobbes and Rousseau, our political theory has been organised around a single question: is human nature essentially good or essentially corrupt? Graham Harman, the philosopher behind object-oriented ontology, argues that this is simply the wrong question to be asking. The real forces governing our collective fate - climate change, artificial intelligence, geography, and pandemics - are non-human; therefore, questions about human nature are not the central ones. Instead, Harman proposes a politics reorganised around our relationship to non-human objects and environments, in which quasi-government institutions incentivise and deter actions with the aim of extending the survival of the human race. “It is easier to imagine the end of the world than the end of capitalism.” This has become one of the most popular phrases among twenty-first-century intellectuals. Often misattributed to Fredric Jameson, it has been warmly embraced by such influential authors as Slavoj Žižek and the tragically departed Mark Fisher, and has fueled the notion that the major problem with the political Left is that it simply needs to become more speculative and creative. Naturally, this is never a bad idea in any human pursuit. But what if the political distinction between Left, Right, and Center itself results from a failure of imagination? SUGGESTED READING Hobbes vs Rousseau: are we inherently evil? By Robin Douglass This particular division has been with us only since the summer of 1789. During the simmering prelude to the French Revolution, it referred originally to the physical position in the National Assembly of radical figures on one side and loyal monarchists on the other. These positions are linked with two entirely different camps of modern political theory. On the Left we find a series of authors ranging from the moderate (Locke) to the supercharged (Rousseau) to the truly radical (Marx), all of them contending that exploitation of the many by the few justifies revolutionary overthrow of the existing order. On the Right they are countered by the likes of Machiavelli, Hobbes, and Schmitt, a group of thinkers convinced that corrupt human nature can be tamed only by force. In the words of the Nazi supporter Schmitt: “One could test all theories of nature and state and political ideas according to their anthropology and classify these as to whether they consciously or unconsciously presuppose [humans] to be by nature evil or by nature good.” This is the division we continue to face today, even in the daily retail politics of Western democracies.___Our species has regularly proven itself capable of both the noblest gestures and the most scathing cruelties, making it hard to define us as essentially either emancipatory or brutal in our aims.___The most refreshing feature of David Graeber and David Wengrow’s 2021 book The Dawn of Everything: A New History of Humanity was their awareness that the forced choice between Rousseau and Hobbes (as they put it) is no longer sufficient. Our species has regularly proven itself capable of both the noblest gestures and the most scathing cruelties, making it hard to define us as essentially either emancipatory or brutal in our aims. Far from being stationed “beyond good and evil,” we seem to be fully entangled with both. We are not naturally good or evil, Graeber and Wengrow contend, but naturally experimental and imaginative. They rest their case on the archaeological record, which seems to bear witness to numerous episodes of seasonally shifting governments and festivals, which vacillate in the same society (even in the same year) between the egalitarian and the dictatorial. Such praise of political experiment makes a good fit with the generally anarchist position defended by these authors. Yet it is also what I find most disappointing in their position. Although they are right that the forced choice between Hobbes and Rousseau falls short of what our new situation requires, the authors simply replace it with praise for the human being as a political tinkerer and performer. In other words, they give us just another theory of human nature, one that would not have been out of place in the sixteenth or seventeenth century. What other options might we have?___The time is ripe for a retheorization of politics on the basis of something other than human nature… We are not just alienated and limited by objects, but also empowered and unleashed by them___One fresh approach would be to treat politics within a broader framework than human nature, given that the polis does not exist in a vacuum filled exclusively with people. When Bruno Latour went to observe the baboons of Kenya with the San Diego anthropologist Shirley Strum, they jointly concluded that these primates were more socially interdependent than our own species. Each baboon is so reliant on the dynamics of the group that they find themselves locked into constant surveillance of their potentially dangerous peers. The group structure turns out to be inherently volatile. Humans, by contrast, are able to stabilize their societies to a large degree through the mediation of inanimate objects. Although one’s position in society may seem to fluctuate over time, considerable stability is produced through such items as apartment keys, wedding rings, and identification cards, all of them serving to secure us a place distinct from that of our fellows. The Italian philosopher Maurizio Ferraris has written at length about the crucial role of documents in establishing social relations, making him a hero among notaries in his country. Proper names and license plates cement our position amidst other humans, as do symbolic achievements such as graduation from a top university or distinguished wartime service with its various medals and ribbons. None of this is found among baboons, despite their closeness to us on the evolutionary tree: after all, we did share a common ancestor just 25 to 30 million years ago. SUGGESTED VIEWING The goodness paradox With Richard Wrangham The time is ripe for a retheorization of politics on the basis of something other than human nature, whether understood in the manner of the Left or of the Right. We are not just alienated and limited by objects, but also empowered and unleashed by them. But initially, it is true, we face non-human things primarily in the form of constraints. It would be difficult, perhaps impossible, to form a human civilization underwater, deep underground, atop Mount Everest, or in outer space. Human dependence on the non-social background takes on subtler form in discussions of political geography, especially unloved on the more idealistic Left. Consider the luckless position of Poland during World War II, sandwiched between Hitler on one side and Stalin on the other. By contrast, note the good fortune of the United States in not having a military peer positioned on any land border. Anglo-American geopolitics, since the writings of the American naval commander Alfred Thayer Mahan and the British geographer Sir Halford Mackinder, has been wedded to the notion that one or more liberal offshore naval powers should prevent any authoritarian “heartland” regime from gaining effective control of Eurasia. That remains the case whether the opponent is the impatient Napoleon, the swashbuckling German Kaiser, the villainous Hitler, the murderous Stalin, or the industrial juggernaut Chinese. In their current Foreign Affairs article “Heartland vs. Rimland,” Michael Beckley and Hal Brands analyze the current and coming state of the world on the basis of these same rather durable principles. In recent years a similar outlook has been embraced, in inverted form, by the Putin-loving Russian philosopher Aleksandr Dugin, an icon of the Rightist intellectual underworld. For Dugin, the Anglo-Saxons are an evil force bent on destroying the spiritually superior people of the land: much like Athens in its failed war with Sparta, or Carthage in its eventual collapse against Rome. But the shared notion on both sides is that any strategy that fails to take geography into account is likely to end up as a defeated form of excessive optimism.___When dealing with environmental degradation, then, we are doing business with forces that promise dire effects on our species as a whole.___More striking for us today than geography is the non-human object called climate, which threatens rimland and heartland equally. Even if we contend that humans are one hundred percent responsible for triggering the climate crisis, it remains non-human in the sense of being an independent force beyond our effective control. In a major work published just before his death in 2002, The Structure of Evolutionary Theory, the American paleontologist Stephen Jay Gould noted the tendency of evolutionary theorists to focus too closely on the fate of individuals in view of their successful or failed adaptation to circumstances. With climate change, however, we confront a force that goes well beyond the scope of any individual life. Whereas Richard Dawkins extended evolutionary questions downward from individuals to the sub-individual gene, Gould pushed it upward, speaking of entire species or clades as impacted by environmental change. The asteroid that struck the Yucatán 66 million years ago is only the most famous example of this sort. In the wake of that catastrophe, large animals needing abundant supplies of food were at a fatal disadvantage by contrast with the smaller birds and mammals of the planet. When dealing with environmental degradation, then, we are doing business with forces that promise dire effects on our species as a whole. The effect is to shift our attention away from individual beings towards the survival of the group.In the United States in particular, the COVID-19 pandemic sparked considerable backlash among those who asserted a nearly absolute degree of individual freedom. In California I encountered those who demanded that their businesses be allowed to reopen, that it was enough to cover their mouths but not their noses, or that they should have the right to enter any public area despite refusing vaccination. Yet public health is probably the clearest argument against libertarianism, which often merely asserts the autonomy of individuals against any claims of the commons. In normal times the individual is worth defending; under conditions that threaten the survival of part or all of our species, compulsion may be our only resort, as with perfectly reasonable blackouts and rations in wartime. To rebuild human society under the constraints of climate change will be one of the great challenges of the century to come, as will our improvised grappling with artificial intelligence. Such phenomena pose existential risks for humanity, and leave far less room for tolerance of individual brattiness. Cases are mounting of devastating wildfires caused by arson. Recently it was reported that there is even a website where one can bet on the location of coming wildfires, raising the specter of deliberate blazes set to collect on wagers. The death penalty has steadily lost support in a world where many stress the infinite value of human life. But if we focus instead on entire ecosystems, those who purposely burn the forests may begin to look worse than serial murderers.___The politics of the future may be splintered by disagreement over such topics as how to manage our environing background and how to permit or restrict the entry of new objects into the political sphere.___So far I have spoken of force, authority, and punishment: measures sure to have greater appeal to those who identify with what we know as the Right. But other implications of the post-anthropocentric world are likely to have different backers. If non-human objects are seen as structuring political space, it stands to reason that they can no longer be introduced solely by the pace of technical breakthrough. Fields ranging from cybernetics to energy will demand increased politicization once they are reconceived not just as products of individual human investment, but as renovations of collective political geography. This need not involve world government, with its inherent risk of tyranny, but may involve quasi-governmental enforcers of prestige along the lines of a less corrupt FIFA or International Olympic Committee, punishing deviant states not with violence but with less tangible incentives.Politics will never lose its historic links with conflict and faction. But rather than factions aligned by differing theories of human nature, the politics of the future may be splintered by disagreement over such topics as how to manage our environing background and how to permit or restrict the entry of new objects into the political sphere. This will prove just as incommensurable with the modern Left/Right spectrum as a globe is with a two-dimensional map.
Israel's decades-old US support risks losing Democrats
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The Science Behind the AI Panic Is Shakier Than You Think
A column by Sascha Lobo Is AI making us dumb? So asked DER SPIEGEL on its cover a while ago. After a few weeks of recovery and a therapeutic intervention with the help of my AI, I feel able to respond. That’s a bit unfair, of course; the article itself is more nuanced than the loud cover, the image of a schoolkid with dull prompt questions, or the subtitle: “AI is conquering the schools, and educators fear a disaster.” The short answer to “Is AI making us dumb?” is: no. The long answer is more interesting, and even carries a preliminary glimmer of the spectacular. Unfortunately, it requires a detour into the sphere of artificial intelligence, into the mogul-field terrain of technology assessment, the attention economy, and the destructive virus of cultural pessimism. Along with narrowing the scope to AI’s effects on education and work rather than on intelligence. Because the honest version of the question would be: Does AI help us learn and work, or not? Generative AI, which set off the still-ongoing hype with ChatGPT, has only existed in relevant distribution since late 2022, early 2023. For a technology-driven transformation of people and society, that is extremely short. For that reason alone, research is still in its infancy. And technology assessment is not a fast discipline anyway. Prominent voices from Elizabeth Eisenstein to RAND to Tom Wheeler say we still cannot conclusively judge the consequences of the printing press. Its invention is a mere 580 years back, and some scholars would rather not circulate assessments that might have to be retracted in two or three hundred years. We’re Going Through Growing Pains A phenomenon that already caused upheaval in social media research makes serious assessment of AI’s consequences even harder: the “moving target” problem of LLM-ology, as the linguist Sean Trott called it in 2025. AI develops so quickly and so unpredictably that researchers often end up studying snapshots of the past. There are concepts, from morphological analysis to anticipatory governance, for keeping research, planning, and regulation halfway meaningful anyway. But even with those, universally valid statements are rare. DER SPIEGEL - The German View is a reader-supported publication. To receive new posts and support our work, consider becoming a free or paid subscriber. Subscribe We should therefore treat findings about the interplay between humans and AI as far more procedural and situational. Unfortunately, this challenge comes at the worst possible time. We are going through growing pains: AI’s everyday impact has grown very large very fast, and with it the longing for guidance. Annoyingly, the body of solid knowledge has not exploded along with it. Experts cannot be moved to broad consensus on even banal statements about AI. Sascha Lobo, born in 1975, is an author and strategy consultant focusing on the internet and digital technologies. Together with Jule Lobo, he explores the debates of the day in the podcast “Feel the News – Was Deutschland bewegt” (”What Moves Germany”). Nvidia CEO Jensen Huang says software developers are dying out. Bill Gates considers coders one of only three professions that will survive the AI tsunami. Top tech economists find virtually irrefutable arguments both for and against an AI bubble. The same naturally applies to the structurally youth-hostile debate over whether AI is good or bad for young people. The gap between the demand for insight and the supply of solid knowledge creates an orientation vacuum. This vacuum of AI cluelessness is filled, as the attention economy described by Georg Franck in 1998 would have it, with half-knowledge (funnily enough, often AI-generated), marketing, and self-marketing. After all, infinite money is at stake, along with academia’s best current shot at global fame. But this iridescent froth of interpretation operates more by the algorithmic principles of the digital public sphere than by seriously earned insight. That is why dramatized, fear-feeding claims about AI are so promising. It tempts parts of academia into distorted drivel, and parts of the media then sensationalize the published drivel once more. Was the Research Aimed at a Desired Result? How badly this can influence academia and public perception is demonstrated by one of the most-discussed studies on AI’s effects: “Your Brain on ChatGPT.” The MIT study by Nataliya Kosmyna also gets plenty of space in the SPIEGEL cover story. What was measured and interpreted: lower brain activity in people who write with AI assistance, compared to people who only google or write without any tools. As is common with preprints, the study has not yet been peer-reviewed, and it contains substantial weaknesses that experts have sharply criticized. The first round had 54 participants in three groups, the second only 18, who reportedly also came from MIT’s own orbit. There was no preregistration (committing in advance to what you want to find out with which data). In their analysis, Stanković et al. even discovered an opposite effect that the study does not further explain. Some measurement data has not (yet) been published. And the EEG analysis method used is considered too imprecise to support such far-reaching conclusions. The biggest criticism, though, is the suspicion of an activism-driven study. In an interview with Time, lead author Kosmyna said she published the study immediately, rather than after full peer review, because she feared politicians might otherwise decide to put ChatGPT in kindergartens. She considers that absolutely harmful. It is legitimate to hold such a view. It just seems unscientific to approach a study with it, and then to design the setup so that the chance of a fitting desired result remains as high as possible. Ideologies Collide It is not easy to separate genuine AI insights from studies that trivialize and weaken well-founded AI criticism. The same goes for the opposing, AI-enthusiastic narratives, because the pro-AI side works against it with billions in resources. Ideologies collide, fed by egos, PR strategies, moral posturing, and once-in-a-lifetime opportunities. Doomsday marketing makes the search even harder: AI companies can profit from warnings about the dangers of AI, whether through the notoriety of apocalypse narratives or because, in some target groups, danger translates into power. Some seemingly negative findings are therefore quite welcome in the AI industry. If you try to get at the findings presumably less influenced by interest groups, the picture in education seems relatively clear: AI can improve educational outcomes when the right AI is used the right way, namely pedagogically. Simply dumping an AI chatbot into a classroom, by contrast, accomplishes little. Huge surprise. But something else is also obvious: whether they are allowed to or not, kids use AI for school, which is why the controlled integration of AI tools into education is, in the medium term, entirely without alternative. In the world of work, the landscape of findings is more complex and requires more differentiation. A series of serious studies points to an AI effect that suits neither the alarmists, regulation fetishists, and AI opponents, nor the trillion-dollar corporations with their armada of paid scientists, PR professionals, and ecosystems: working with AI helps the inexperienced (at least for now) considerably more than it helps the pros, in certain fields of work, and provided they know how to use it correctly. Missing Domain Knowledge Among the experienced, the professionals, and the high flyers, by contrast, despite frequent time savings, partially negative effects and new problems are emerging. Take the jagged frontier problem: AI solves task A brilliantly and fails completely at task B, even though both look similar even to professionals. Or the verification-cost problem, in which AI’s greater productivity gets eaten up by the enormous effort of checking its output. Or the illusion of competence, because AI makes new domains seem easily penetrable, until you painfully discover that deep domain knowledge is missing. Taken as a whole, the effects of working with AI do lean positive. But the promise that AI works as a turbocharger for everyone and boosts practically everything simply refuses to materialize. The AI magic the world has been feeling since ChatGPT arrived in late 2022 has so far barely shown up in most companies’ numbers. The consulting firm McKinsey has coined a term for this, the “gen AI paradox,” and believes that work processes and corporate structures would have to be rebuilt quite fundamentally to realize AI’s benefits at scale. Reuters just reported that only 3.3 percent of Microsoft’s customers have subscribed to the AI package Copilot. That may be down to the product; in other areas we continue to see soaring successes and new AI triumphs. But after the first quarter of 2026, disillusionment is the word for all too many AI projects at traditional companies: because the promised revolution of AI agents has so far failed to arrive or been postponed, and because of the leveling effect that many of the studies cited here suggest. Against Inequality The societal effects, on the other hand, appear rather encouraging. Many previous technologies operated on the Matthew principle, named for the Gospel verse about giving to those who already have: they tended to reward the more competent and more privileged. AI, however, seems more often to have an equalizing effect once a threshold of access and education is crossed. Some anecdotal insights point in this direction, for example, how an unemployed man in Leipzig successfully defended himself in court in 2025 against fraud accusations from Germany’s federal employment agency — without a lawyer, armed only with ChatGPT. The AI made mistakes and cited invented court rulings, but in the end the man walked away unpunished. And a key capability of artificial intelligence is its capacity to learn: set up correctly and fed with data, it can keep getting better. It is a question of time, or more precisely of AI innovations and training data, until even free AI chatbots write better legal briefs than law graduates with perfect exam scores. Whether that will make anyone dumb is something the world’s press will surely inform us of in due time. Subscribe Leave a comment
Battle to replace late House Dem goes to overtime after daughter failed to clinch seat
Marcye Scott and Everton Blair advance to an Aug. 25 runoff election in Georgia's 13th congressional district to fill the late David Scott's seat.
See which Livonia restaurants failed health checks
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Behind Closed Doors, Trump Huddles With Netanyahu and Zelensky
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Did League Cup come too early for Saints?
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What England's local councils tell us about fragmenting politics
Even the most ardent advocate for local democracy would concede that council chambers are not always the most exciting places. Subscribe Whether it’s planning meetings, motions or resolutions, you’d be forgiven for switching off. Unless it’s lockdown and we’re talking about standing orders, of course. Remember Jackie Weaver, who infamously “had no authority here” at a chaotic parish council Zoom call in 2021? Yet, as a general rule since then, council meetings rarely make the headlines beyond local papers and news websites. Reform’s success After Reform’s stunning success at the local elections in May though, the leader of the party’s group on Kirklees Council suddenly found she’d gone viral online for admitting that she didn’t actually understand council procedures. “I don’t understand the constitution”, Councillor Sarah Wood, pictured above, told the council chamber. “I have not had sufficient time to read that as yet. I don’t understand what standing orders are, what they’re made up of, nor do I understand what an amendment is.” Share Channel 4 News Councillor Wood later defended her comments to the BBC, and said that “new councillors and not just us, are coming from jobs”. She claimed that the sharing of the clip mocking her online was an example of “Reform-bashing”. She added: “Yes, we need to know procedures. Yes we need to do the homework. And we have addressed that now and we have put that right.” So, with standing orders getting another moment in the spotlight, not to mention the fracturing and fragmentation from May’s results, we set out to find out how new councillors are doing across England in this new political landscape. New political landscape Where better to start then than Kirklees, in West Yorkshire. Reform is the largest party, the council is under no overall control and has chosen a new leader - Sarah Wood - after two failed attempts to elect one. It is difficult to secure interviews with new Reform councillors, but John Hardie, pictured below, told us it’s been a “whirlwind” since being elected in May. He represents the Dalton ward and told us the party’s lack of political experience hasn’t been a hindrance. “We’ve come with lots of experience, lots of business experience and life experience, and it’s been good, actually, too. And to mix with other councillors who have been in the political world, and we can learn from each other.” Indeed, more parties are now having a say than ever before. In Manchester, the Green Party followed up their victory in the parliamentary by-election in Gorton and Denton by gaining 17 seats on the city council. That makes them the official opposition to Labour, who have long dominated Manchester City Council. [ ](https://channel4news.substack.com/p/how-landmark-green-by-election-win) [ How landmark Green by-election win could change British politics ](https://channel4news.substack.com/p/how-landmark-green-by-election-win) Krishnan Guru-Murthy · Feb 27 [ Read full story ](https://channel4news.substack.com/p/how-landmark-green-by-election-win) Thirza Amina Asanga-Rae, pictured below, is one of those new councillors, representing Moss Side. We asked her how being the official opposition can make a difference. She said: “I think even the fact that we’ve made history in what we’ve done, it’s been a 50-year stronghold of Labour in Manchester, and now that we’ve broken that and chipped in that, there’s real hope that we can not only run the council in the future, but currently hold them to account. So, I think that’s powerful. It’s just going to help shape and build what I call the green wave.” The reality, though, is that several newly elected councillors across the country have already left their roles through resignations, suspensions or defections. ‘It’s a slog’ Asanga-Rae adds: “It’s a job, it’s a slog. Obviously, we’re going through hard times. Austerity is real. We’re talking about food, child poverty, furniture poverty. The list is endless, and I think people who come into a councillor role need to be willing to help, really roll the sleeves up and get involved and help, and I think a lot of the career politicians, who think it’s the ‘la-di-da’ position, get in and realise I’m not going to do this work and bounce.” Share Although Manchester still has a clear majority, many councils, including Kirklees, are now under no overall control. That is perhaps the strongest sign of the political fragmentation we are seeing. Burnley is another example of this. Reform is now the largest party, yet they’re not part of the power-sharing coalition on this council - the Liberal Democrats and a local group of independents. Zulkernehn Hayat, pictured below, is part of The Independent Group. He represents Queensgate ward and told us all councils can benefit from having more independent councillors. ‘This is where I was brought up’ He said: “This is my home. This is Burnley. This is where I was brought up. Why do I need to get approval from somebody in a head office down south somewhere, you know? “This is my biggest argument. If okay, my neighbour comes to me with an issue, I can then take that straight to the council, because I don’t need to get approval from anywhere else. And this is the benefit of being independent.” So, while voters will always inevitably want quick results, perhaps spare a thought for the newly-elected councillors who are still navigating local government - one standing order at a time. 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Kevin Seifert Drops Clear Message on Vikings' 2026 Season
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Orlando Magic Shockingly Drop in Latest Power Rankings
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With His Latest Threats, Trump Signals to Iran That He Is Willing to Escalate
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Apple's $634M payment to Masimo now set in stone after Judge tosses appeal
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Sigcho-Lopez, Macías Failed to Qualify for 4th District Congressional Race: Elections Board
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Missouri health facility failed to protect kids from sexual abuse, lawsuit says
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Freedom, trust and the future of science: Nobel laureates reflect on the ideas shaping tomorrow
Behind every scientific discovery are years, sometimes decades, of fundamental research, failed experiments, uncertain funding, international collaboration and the freedom to pursue questions without knowing where they might lead. The Nobel laureates recently gathered at the 75th Lindau Nobel Laureate Meeting in Germany argued that scientific breakthroughs depend on far more than brilliant ideas alone. Those conversations unfolded against the backdrop of Russia’s full-scale war against Ukraine, ongoing conflicts in the Middle East and growing geopolitical competition. The question running through the discussions was therefore broader than science itself: what conditions make discovery possible? ‘Europe is a space of freedom’
Warren’s latest ‘kiss of death’ endorsement sparks mockery over disastrous political picks
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WVU Health leadership failed to address painkiller thefts as opioids devastated West Virginia
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Shaky political "science": breakdown of the peer review process
[This article is the latest in our “Shaky Political Science” series. In our 38 page report, “Shaky political ‘science’ misses mark on ranked choice voting,” released in December 2025, we examined over 40 studies focused on ranked choice voting (RCV). Many of these studies suffered from puzzling research methodologies, poorly constructed surveys, unrealistic simulated elections, cherry picked data and faulty analyses that often were contradicted by results from real-world elections (a link to our full paper is here). Here are links to the first four articles in our series: the first one summarizing the overall results of our report; the second one analyzed a study co-authored by University of Minnesota academic Larry Jacobs, which was one of the most error-prone of all the research we reviewed in our report; a third article showing an admirable example of two political scientists holding two other political scientists accountable for their flawed, sloppy research; and a fourth article that analyzed seven studies sponsored by New America’s political reform program that deployed flawed methodology based on “simulated” elections instead of real-world elections, which when combined with some basic misunderstandings of RCV, produced odd and misleading results]. In this fifth article in our “Shaky Political Science” series, we examine two flawed studies on the impact of RCV on voter turnout authored by San Francisco State University professor Jason McDaniel. McDaniel’s research in these two papers stands out for its puzzling methodology, inadequate and cherry-picked data, and faulty analyses that not only misunderstands ranked choice voting but reflects a basic misunderstanding of politics in general. The first of the McDaniel studies actually passed through a peer review process and then was subsequently published by the Journal of Urban Affairs, despite its obvious errors. It is perplexing that a jury of peer political scientists did not catch the errors and send it back to McDaniel for a rewrite or outright rejection. This calls into question the credibility of the peer review process itself. The peer review process is supposed to represent the intellectual pinnacle of the profession – a way for academics to certify the quality of each other’s work, and to act as a check against sloppy research. In the case of the McDaniel study, the peer review process failed. Yet his flawed study has been cited dozens of times by other political scientists in their own flawed works — an unvirtuous circle of academic research. Here is the first Jason McDaniel study that we analyzed: “Writing the Rules to Rank the Candidates: Examining the Impact of Instant-Runoff Voting on Racial Group Turnout in San Francisco Mayoral Elections,” by Jason McDaniel, 2016, Journal of Urban Affairs. This study covered San Francisco’s use of ranked choice voting (RCV) in mayoral elections, purporting to show that RCV reduces voter turnout overall, increases voter errors, and has a negative impact on “marginal populations,” i.e. racial minorities, mainly as the result of the alleged complexity of RCV asking voters to rank candidates and having to be familiar with multiple candidates and related dynamics. McDaniel reached these conclusions by examining five San Francisco mayoral elections taking place in odd years (i.e. where there are no federal or state races on the ballot) from 1995 to 2011, comparing three earlier non-RCV races (in 1995, 1999 and 2003) with the later two RCV races (in 2007 and 2011). Only two RCV races were studied, and as McDaniel acknowledged, only the contest in 2011 was “competitive” (that contest in 2007 was the first mayoral election using RCV, and incumbent mayor Gavin Newsom won easily in the first round of counting, earning 74% of first choices and far ahead of the second place candidate who had just 6.3% of first choices). Yet even the allegedly competitive contest in 2011was won by an incumbent with a landslide margin of nearly 20 points. No other elections were studied by McDaniel, even though San Francisco elects 17 other offices besides mayor with RCV, including the 11 seats on the Board of Supervisors (the name for the city council) in even years, and six other citywide offices in odd years. Previous academic research has found that competitive elections can stimulate greater voter involvement and higher turnout. For unexplained reasons, this study ignored at least 34 other RCV races between the years 2004 to 2011, many of which were very competitive and had high voter turnout. Instead, McDaniel’s analysis based its conclusions on data from only a single, marginally-competitive mayor’s race using RCV. These 2007 and 2011 mayoral elections were the only two RCV elections that McDaniel used as the sole basis for his small data set to determine the impact of RCV on voter turnout. Despite having no meaningful data to inform his study, McDaniel nonetheless concluded that RCV lowered turnout when compared to the previous three mayoral non-RCV elections using two-round runoffs. Then, using the same inadequate database of San Francisco elections, McDaniel also found that “Instant-runoff voting is associated with a significant decline in Black voter turnout and White voter turnout…On average, Black voter turnout decreases by 18 points and White voter turnout decreases by 16 points …” But how could he credibly arrive at that conclusion when his study was based on voter turnout in two RCV contests that were not even remotely competitive? Beyond that, McDaniel tacitly admits that the key determining factor driving Black voter turnout was not RCV vs non-RCV elections, but the presence of a viable Black candidate. McDaniel wrote, “Black voter turnout was about 17 percentage points higher for the two elections that featured an African American candidate compared to the three elections that did not” — but one of those three elections did not use RCV. The same dynamic was present for White voter turnout, in which higher turnout was not correlated with RCV vs non-RCV elections, but the presence of a viable White candidate. Beyond that, McDaniel’s voter turnout results, whether correlated with the race of the candidates or RCV vs non-RCV elections, showed no clear patterns. In his Figure 1, he shows low Asian voter turnout in the non-RCV elections in 1999 and 2003 when there was no viable Asian candidate running, but in the 2007 mayoral election using RCV, there is still no viable Asian candidate, yet Asian turnout increases dramatically. For Latinos, voter turnout is virtually the same in 1999 (no viable Latino candidate, non-RCV elections), 2003 (leading Latino candidate, non-RCV elections), 2007 (no viable Latino candidate, RCV elections) and 2011 (leading Latino candidate, RCV elections). Meanwhile White voter turnout increased dramatically from a low in the 2007 mayoral election, in which the leading candidate was a white incumbent, to the 2011 election in which there were no leading white candidates that finished any higher than sixth place with 5.6% of the vote. Clearly other factors were determining voter turnout than either the race of the candidates or RCV vs non-RCV elections. Despite these inconsistent findings, McDaniel boldly marches forth to render conclusions about the impact of RCV on different groups of racial voters, even though his conclusions are not remotely supported by his data. This looks like the worst kind of “data cherry picking” to cover up a puzzling conclusion based on a poor data set involving only two RCV elections, neither of which were remotely competitive. McDaniel’s cherry picking didn’t stop there. In calculating voter turnout for the three non-RCV mayoral elections in 1995, 1999 and 2003, he failed to mention that in each of these years there was a two-round runoff election, with a first round election in November in which no candidate garnered a winning majority of the vote, followed by the decisive runoff in December. So there were two non-RCV elections in each election year. But McDaniel only decided to include one of the two elections in his data set, apparently the December runoff in each year (which had higher turnout in two out of the three mayor’s races, and lower turnout in the third). So he ignored the November 1995 election, the November 1999 election when turnout was only 45 percent, and the November 2003 election when turnout was only 45.7 percent. This is flawed methodology based on blatant cherry picking, since McDaniel simply omitted three elections worth of data that did not fit within his frame. His study should never have made it through a peer review process, and it is an embarrassment to political science that not only was it approved for publication, but it has been uncritically cited by dozens of other political scientists. Share A “study” without wider context or credible data Lacking a data set that included even a single competitive RCV mayoral race, McDaniel declared that RCV lowered voter turnout in 2011, when turnout was 42.5 percent. But he also ignored -- or did not realize -- that voter turnout in mayoral elections during 2011 had sharply declined in all big cities, including far more steeply in nearby Los Angeles and other cities. In fact, San Francisco’s election in 2011 had the second highest turnout of any mayoral election in the nation’s 22 largest cities from 2008-2011. Was 2011 just a particularly low turnout year all across the country, perhaps because the country was still reeling from the aftermath of the housing market collapse in 2008-2010? McDaniel ignored this factor and did not search for alternative explanations beyond his flawed thesis. Furthermore, while McDaniel suggested that RCV leads to more “overvotes” – which is an invalidated ballot in which a voter, in either a non-RCV or RCV race, makes a mistake and selects two candidates for a single choice – he failed to address that in the June 2012 US Senate primary contest, which used the typical “one-choice” plurality method and did not use RCV, there was more than five times as many overvotes in San Francisco and Oakland than in the RCV mayoral elections in those cities. Additionally, turnout had been significantly higher and more representative in RCV elections for the San Francisco Board of Supervisors races -- that McDaniel didn’t even bother to study -- as compared to previous “delayed two-round runoffs” for those offices, often higher by as much as 40% in the RCV races. Perhaps the most surprising irony was that an earlier study co-authored by McDaniel (Overvoting and the Equality of Voice under Instant-Runoff Voting in San Francisco by Francis Neely and Jason McDaniel, 2015, California Journal of Politics and Policy) found that overvotes are often more common in lower-income precincts, but that the pattern of overvoting is similar in both RCV and non-RCV contests. Wrote Neely and McDaniel: “[Overvote] errors appear to be a function of complexity in general and not IRV per se…. the pattern of overvoting is similar in both IRV and non-IRV contests…Even among votes cast in a top-of-the-ticket race like U.S. Senate, overvoting occurs in an uneven fashion” (IRV, or ‘instant runoff voting,’ is another name for ranked choice voting in single-winner contests). So McDaniel not only contradicted his own conclusion in his earlier study with Neely, but the earlier study had been an important corrective for one of the most frequently made mistakes made by anti-RCV political scientists – a continual failure to provide crucial context by pairing a comparative analysis of real world RCV elections with an analysis of real world plurality or other electoral methods. Unfortunately McDaniel’s earlier study does not get cited much by other researchers, and McDaniel did not even cite it in his own flawed study analyzed above. Incredibly, McDaniel cherrypicked McDaniel, even as his flawed study has been cited dozens of times. Despite being a textbook example of poor political “science,” featuring both inadequate as well as cherrypicked data, the shelf life of McDaniel’s study has been extended endlessly by other political scientists and media outlets who have cited it uncritically. Equally troubling, the Journal of Urban Affairs put this paper through its peer review process and published it despite its numerous flaws. McDaniel gets it wrong, Part II Not content with producing one shoddy, confused paper, McDaniel produced another one a few years later, here is the link: Electoral Rules and Voter Turnout in Mayoral Elections: An Analysis of Ranked-Choice Voting by Jason McDaniel. San Francisco State Univ. (McDaniel, 2019). In this paper, McDaniel extended his previous flawed research focused on San Francisco, about voter turnout and voter impact, to multiple RCV cities through the 2018 elections. In his data set he included San Francisco, Minneapolis, St Paul, Oakland, Berkeley, San Leandro and Santa Fe. He then compared their turnout in mayoral elections to non-RCV cities, and to mayoral elections in those cities held before first RCV usage, and concluded “a significant decrease in voter turnout of approximately 3–5 percentage points in RCV cities after the implementation of RCV.” But he replicated many of the same mistakes as his first study presented above. While in this study McDaniel attempted to distinguish between various factors, such as odd year vs. even year elections, competitive races vs. noncompetitive, contests with open seats and other factors, the analysis is superficial and inadequate. He attempts to incorporate so many often-conflicting variables that his conclusions are once again unsupported by the actual data, and ultimately unconvincing (this second study never underwent a peer review process). For example, McDaniel declared that for RCV cities “in elections that are more competitive than average (margin of victory less than 20%), there is no significant RCV effect on voter turnout.” Yet McDaniel is a professor in a city, San Francisco, in which the 2018 special election using RCV to fill a mayoral vacancy was exceedingly close, decided by a margin of only one percentage point, and resulted in the second highest turnout in San Francisco history for a mayoral election. Illustrating the complexity involved in assessing the critical factors in turnout, that special election was held on the same election day as federal and state offices, which tends to boost turnout. Yet more voters participated in that RCV mayoral election than voted on the same day in the non-RCV primary for governor in which former San Francisco mayor Gavin Newsom was running. Even more puzzling, in this study McDaniel inaccurately cited his own previous study from 2015 with Neely. McDaniel wrote, “Neely and McDaniel (2015) examine individual ballot image files within a natural experiment, and find higher rates of ballot errors in RCV elections compared to non-RCV elections” (emphasis added). However, we quoted from that 2015 study several paragraphs above, and in actual fact Neely and McDaniel actually concluded the opposite -- that the pattern of overvoting – which is the most common form of ballot error – is similar in both RCV and non-RCV contests. McDaniel also ignored the fact that in Bay Area RCV elections held in even years – at the same time as federal and state elections, when turnout is highest -- the “undervote” (that is, the dropoff in ballots cast for governor or mayor) has declined, which contradicts his thesis that the act of ranking ballots in RCV elections is too complex and presents a barrier for certain demographics of voters. To his credit, McDaniel actually acknowledged another contradiction in his own paper, which found a negative RCV turnout effect in some odd-year elections but not others, admitting that “may present a challenge to the theory that increased complexity [from RCV] will have a marginal negative effect on voter turnout.” But he tried to wallpaper over that contradiction by blaming it on an unlikely source -- bad election administration. McDaniels wrote, “This would suggest that the negative impact of RCV on voter participation may be alleviated by high quality election administration,” without presenting any data or even anecdotes to support such an unfounded theory. While competent election administration of any election, whether RCV or non-RCV, is crucially important, there is no credible research that supports the far-fetched notion that the quality of election administration has much of an impact on voter turnout in US elections, whether using RCV or otherwise. Upgrade to a $5 subscription The unvirtuous circle of academic research It is puzzling how McDaniel’s first study could have survived the peer review process for the Journal of Urban Affairs. The mistakes in McDaniel’s first study above should have been obvious to anyone with a basic understanding of ranked choice voting as well as elections in general, and elections in San Francisco specifically. It undermines faith in the credibility of the peer review process to think that a jury of peer political scientists did not catch the egregious errors and reject McDaniel’s sloppy research and paper. And it remains a black mark on political science that this thoroughly discredited study has been cited dozens of times by other researchers. Indeed, in our research paper it became apparent that many political scientists cite each other’s flawed research to pad their list of citations and to legitimize their own flawed research, creating an unvirtuous circle of political science. More broadly, McDaniel’s voter turnout studies, like other studies evaluating RCV’s impact on turnout, lacked a recognition that no credible opinion or research can claim that RCV increases voter turnout merely because so many voters are excited to vote for their favorite candidates instead of “lesser evil” candidates without worrying about spoilers. Instead, with respect to turnout, the advantage of RCV has always been that, in most places where it has been used, it has eliminated a pre-November primary or post-November runoff, which usually saw about half the turnout of the November general election. This is especially true during even years when there are state and federal elections on the ballot which substantially drive turnout more than local contests. Any study that does not adequately account for this non-November primary/runoff vs November general election dynamic, or odd year vs even year election factors, is simply not credible. Both of McDaniel’s studies largely failed on those grounds. Steven Hill and Paul Haughey Share Upgrade to a $5 subscription Thanks for reading DemocracySOS…your digital portal for the pro-democracy movement. Subscribe for only $5 per month to receive full benefits and to support our work. Subscribe
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In 2020, I wrote an article about collaboration and collaborators. The title was History Will Judge the Complicit, and it started with the story of two famous East Germans, Markus Wolf and Wolfgang Leonhard, who both landed in East Berlin just after the end of the war. Although they came from very similar backgrounds, the former stuck with the regime, eventually becoming its spy boss; the latter, horrified by the brutal reality of Soviet-style communism, escaped. By way of juxtaposition, I also wrote about Lyndsey Graham and Mitt Romney. These two men also made very different decisions when confronted by Donald Trump’s assault on the ideals that they had both grown up believing: A glance at their biographies would not have led many to predict what happened next. On paper, Graham would have seemed, in 2016, like the man with deeper ties to the military, to the rule of law, and to an old-fashioned idea of American patriotism and American responsibility in the world. Romney, by contrast, with his shifts between the center and the right, with his multiple careers in business and politics, would have seemed less deeply attached to those same old-fashioned patriotic ideals. Most of us register soldiers as loyal patriots, and management consultants as self-interested. We assume people from small towns in South Carolina are more likely to resist political pressure than people who have lived in many places. Intuitively, we think that loyalty to a particular place implies loyalty to a set of values. But in this case the clichés were wrong. It was Graham who made excuses for Trump’s abuse of power. It was Graham—a JAG Corps lawyer—who downplayed the evidence that the president had attempted to manipulate foreign courts and blackmail a foreign leader into launching a phony investigation into a political rival. It was Graham who abandoned his own stated support for bipartisanship and instead pushed for a hyperpartisan Senate Judiciary Committee investigation into former Vice President Joe Biden’s son. It was Graham who played golf with Trump, who made excuses for him on television, who supported the president even as he slowly destroyed the American alliances—with Europeans, with the Kurds—that Graham had defended all his life. By contrast, it was Romney who, in February, became the only Republican senator to break ranks with his colleagues, voting to impeach the president. “Corrupting an election to keep oneself in office,” he said, is “perhaps the most abusive and destructive violation of one’s oath of office that I can imagine.” In the wake of Graham’s unexpected death on Saturday, I wrote about him again. He was, in many ways, the quintessential politician of Trump’s Washington, a man who shifted 180 degrees. Graham had been a fervent American patriot, proud reserve officer and military lawyer; he became one of the most important defenders of a president who believes soldiers are “suckers and losers” and shows no respect for law of any kind. As his politics changed, his language grew coarser and his behavior grew worse: He urged Israel to “level the place” in Gaza, and insulted the Danish prime minister in Munich, prompting a colleague, Senator Elissa Slotkin, to issue an apology. Here’s an excerpt from the article, which you can read in The Atlantic (gift link here) Like his close friend John McCain, Graham believed that America should stand at the center of a broad democratic alliance. The few times I met him were in that context, at the Munich Security Conference or at other European-American gatherings, which he once attended with great regularity. He also took seriously the practice of American democracy at home. In a 2014 conversation with The Atlantic, he described himself as a pragmatic politician who eschewed populist slogans. “I know Washington is broken, but what’s broken about it is everybody yelling and nobody trying to fix it,” he said. “I’m trying.” When Donald Trump first appeared in U.S. politics, Graham recognized him immediately for what he was: the spokesman for an alien ideology, one radically different from the idealistic patriotism that Graham had practiced and preached since childhood. Trump privately mocked the military that Graham loved as nothing but “suckers and losers.” He put falsehoods, cynicism, and personal greed at the center of his politics, while expressing disdain for transparency, accountability, and democracy itself. In 2015, Graham described Trump as a “race-baiting, xenophobic, religious bigot” who should “go to hell.” Also as a “nutjob.” When Trump won, Graham understood, as did so many others, that he would have to make some important choices. For a while, he went silent. In the spring of 2016, I saw him at one of those conferences in Europe. He seemed too depressed to speak. But then, like many other Republicans—and, more important, like many other people who have lived under political occupation or experienced radical regime change—he made the decision to abandon his previous ideals, to bury the patriotism that was once so important to him, and to become, instead, a loud, opportunistic collaborator. As I wrote in 2020, it’s very hard to look in to anyone’s heart and to understand their motivations from the outside. But it does seem that Graham had a deep need to be relevant, to be in the game, to be a player, at any cost. And that, rather than any particular achievement, is what he will be remembered for. Continuing to monitor conflicts of interest, ostentatious emoluments, outright corruption and policy changes that will facilitate outright corruption. (Read my original article, Kleptocracy Inc and check out the SNF Agora Institute chart) June 27 Trump diverted funds from more than 900 projects nationwide—including safety upgrades at national parks—to finance beautification projects around Washington, including $700,000 used to fix a White House walkway. June 28 After a years-long Department of Justice investigation into Abbott Laboratories over its management of a baby formula facility where potentially deadly bacteria turned up enough evidence to criminally charge the firm, top department officials instead opted for a financial penalty—illustrating the department’s move away from strict corporate enforcement under the Trump administration. June 29 Defense Secretary Pete Hegseth stacked the Defense Policy Board—which is charged with providing independent national security recommendations to the Office of the Secretary of Defense—with Trump allies, including tech billionaire Marc Andreessen, who has invested in defense contractors like OpenAI and SpaceX, after purging the panel last year. Trump purchased between $1 million and $5 million worth of stock in Axon—which makes about 90% of US tasers—two weeks before ICE solicited bids for a $220 million taser contract. The White House unveiled limited-edition US passports for America’s 250th birthday, featuring a portrait of Trump overlaid on the Declaration of Independence. June 30 Trump made around $1.2 billion from his various crypto companies last year, including more than $500 million from World Liberty Financial and $600 million from sales of his meme coin. Trump is considering issuing 250 pardons to commemorate America’s 250th birthday. These are expected to be largely doled out through the Office of the Pardon Attorney’s informal network of intermediaries. White-collar defense attorneys say they can typically win pardons for clients for $2 million. Last year, Trump administration officials awarded a no-bid contract worth up to $500 million to Clark Construction for the White House ballroom—negotiations in which the president was directly involved. July 1 The Amazon MGM Studios documentary about Melania Trump earned the First Lady more than $10 million. Trump made hundreds of individual stock purchases worth as much as $12.8 million the day before his announcement pausing “Liberation Day” tariffs for 90 days sent the S&P 500 soaring nearly 10%—one of the largest single-day gains ever. Mar-a-Lago and Trump National Doral saw record surges in revenue during Trump’s first year in office, earning $77.5 million and $121.9 million respectively, compared to average annual revenues of $25 million and $75 million during Trump’s first term. Entities across the Persian Gulf paid more than $300 million to Trump’s businesses last year, including $263 million from the sale of half his stake in World Liberty Financial to a firm backed by Sheikh Tahnoon bin Zayed Al Nahyan, a top UAE royal and brother of the country’s president. Kash Patel failed to properly disclose his stock purchase of a Department of Justice contractor, MicroStrategy, worth up to $250,000 last year, despite laws requiring disclosure within 45 days of the trade. July 2 Trump has been directing administration officials to steer more government contracts—so far worth more than $2.4 billion—to Jeff Bezos’s Blue Origin aerospace firm, after Amazon gave $1 million to Trump’s inaugural fund, donated to the White House ballroom project, and reached a $40 million deal to license a Melania Trump documentary. Alongside the billions he made from cryptocurrency last year, Trump earned millions of dollars from real estate licensing fees, including $21 million from organizations in the UAE and $9.2 million in Saudi Arabia, along with smaller sums from merchandise sales, including $4.7 million from Trump Watches and $35,920 from 45 Guitar, a guitar brand endorsed by the president. House Democrats accused consultants tied to the Trump administration of financial fraud, alleging they gave prospective donors to America250—the bipartisan committee created by Congress to celebrate the nation’s semiquincentennial—the banking and routing numbers for Freedom 250, the White House’s fund for events like the UFC cage fight. Democrats also allege that Freedom 250’s CEO traveled to the World Economic Forum in Davos to solicit donations from foreign government officials and business leaders. The Trump administration’s proposed rollback of gun regulations would lift the prohibition on mailing handguns to individuals, a significant win for GrabAGun—the direct-to-consumer firearm retailer on whose board Donald Trump Jr. sits and in which he holds a 1.1% ownership stake. GrabAGun currently must rely on a middleman to transfer firearms to customers. Trump’s financial disclosure revealed that he made more than 21,000 securities trades during his first year back in office, growing his investment account to at least $858 million across stakes in around 1,600 companies, compared to the 13 total trades Joe Biden made during his entire presidency. July 4 Nearly 1 million people who bought the president’s meme coin—Trump Coin—collectively lost $3.8 billion on the token, while he walked away with $636 million. July 6 Shares of Dell closed up 4.4% after Trump recommended people buy the firm’s computers during a speech announcing the launch of Trump investment accounts for children, boosting the more than $1 million worth of shares the president owns in the company. July 9 Federal Reserve Chair Kevin Warsh named crypto investor and Trump ally Marc Andreessen to a task force aimed at modernizing the Federal Reserve, including rethinking its approach to inflation—a key factor keeping interest rates elevated. Palm Beach International Airport has officially changed its name to Trump International Airport—a move that will require Florida to pay royalties to the president’s family for licensing his name. I was there a few months ago, during a trip to Barcelona. The sculptures were a revelation, I’d never seen so many together before. Each one has its own personality. Enjoy the good weather, if you are lucky enough to have it. History Will Judge the Complicit The Quintessential Politician Autocracy Inc Open Letters, from Anne Applebaum is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber. Subscribe
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Qatari club Al-Sadd have failed in their attempts to sign Olympique de Marseille defender Nayef Aguerd (30), as per a report from Foot Mercato.Marseille need to sell players this summer. Whilst the L...
Richard Hughes has the perfect midfield signing for Liverpool
Liverpool's midfield is one of their main areas that needs to be revamped. Alexis Mac Allister and Ryan Gravenberch both failed to meet expectations last term with their inability to run one of their ...
LeBron James’ Lakers rift stemmed from failed Russell Westbrook saga
LeBron James’ tenure with the Lakers is over after he informed the NBA franchise he’d spent the past eight seasons with that he’ll sign elsewhere in free agency. While both...
Top ‘Suicide Squad’ Developers Say the Flop Made Them Not Want to Make Games Anymore
The director and top designer of Rocksteady’s failed game open up about their experiences
See why Shaggy's, Zea Rotisserie, 5 others failed June health inspections
Seven restaurants in Rankin and Madison counties received failing health inspection grades in June 2026.
Dems join Republicans to crush Tlaib's war powers resolution in lopsided House vote
Rep. Rashida Tlaib's resolution to bar U.S. military hostilities in Lebanon failed overwhelmingly as Republicans questioned why the measure was needed.
US bill requiring paid games to be playable after they shut down has failed to pass a Senate vote
Stop Killing Games says it will try again with “the funding to do this properly”…
This Gainesville restaurant failed its health inspection with a 68. Here’s why
A Gainesville nuevo latino restaurant received a failing grade on its health inspection.
The World Cup is a stress test for our public health system. We failed it even before kickoff.
Soccer matches across North America are attracting people from around the world who are crowding stadiums and public transit, places where infectious diseases can be easily and widely spread.
UK Political Angst Turned Foreigners Into Gilt Sellers in May
Foreign investors, long an anchor for the UK government bond market, turned net sellers of gilts in May as climbing yields failed to offset concern about the country’s political turbulence.
Rural Fosston moves forward in its quest to relinquish control of local hospital from Essentia Health
A northwestern Minnesota community is seeking to regain local control of its hospital, arguing Essentia Health has failed to meet local health care needs. A recent court ruling allows Fosston to take its case to arbitration.
We almost had a smartphone in the 90s. Why did it fail?
In the early 90’s, a company called General Magic began working on a portable device that would allow people to check email, make phone calls, even play games. It was basically a smartphone. But it never caught on.On today’s show, a theory about why this device failed. General Magic had generous investors, world-class talent and creative freedom. But is it possible what they needed was constraints?Support:Planet Money+Read: Our book: Planet Money: A Guide to the Economic Forces That Shape Your Life Our weekly longform Planet Money newsletterOur weekly Indicator round-up newsletterFollow: InstagramTikTokYouTubeFacebookThis episode was hosted by Erika Beras and Emma Peaslee. It was produced by Emma Peaslee with help from Sam Yellowhorse Kesler and James Sneed. It was edited by Marianne McCune and fact-checked by Charlotte Isidore. It was engineered by Jimmy Keeley with help from Cena Loffredo. Alex Goldmark is Planet Money’s executive producer.
Bayer wins in US court, but at what cost to public health?
A landmark US Supreme Court ruling protects Bayer from thousands of lawsuits linked to its Roundup weedkiller. Plaintiffs alleged the German agrochemical giant failed to warn users about potential cancer risks.
NBA fans troll Victor Wembanyama after MVP chants in France
Victor Wembanyama is back in France after leading the San Antonio Spurs to the NBA Finals. While his team failed to win the championship, he still received a lot of love from his countrymen. The 7-foot-4 center entered a club…
California’s Billionaire Tax Kicks Off a Democratic Civil War
The divisive proposal heads to the ballot after attempts to reach a compromise deal failed.
Making Our Own Luck
We are cross-posting a piece that former NIH official Kris Willis wrote for Macroscience. Kris is now the President and Founder of the Woodley Park Institute, for which I’m a board member. Picking winners or hedging bets? Federal science agencies have long wrestled with the question of how to ensure their billions of dollars of grants and contracts result in maximum benefits for Americans. On the surface, it might seem that a goal-oriented, interventionist style of management would be the best policy: prioritize our most pressing problems and distribute funding accordingly.This top-down strategy creates a unique hazard, though: bad choices can send resources in the wrong direction, resulting in slow progress that impedes the delivery of tangible benefits to citizens. Moreover, if decision makers pursue an applied advance when the underlying scientific principles remain poorly understood, they risk costly failures and a loss of support for the research enterprise at large. Examples include Nixon’s 1971 War on Cancer, undertaken on the premise that a cure could be achieved in less than a decade, the drive to build an operational commercial fusion plant by the mid-1990s, and the National Plan to Address Alzheimer’s Disease, which failed to produce the effective treatments and prevention strategies promised by 2025. The contrasting laissez-faire approach is to hedge your bets. If the path to an advance is impossible to predict, then the wisest choice might be to distribute funding to as widely as possible. The main risk of this strategy is that spreading funding thinly may limit the resources available to the most promising research, resulting in the same negative outcomes as the interventionist approach: limited support for the most promising topics, slow progress, and delayed returns. In reality, at science agencies like the National Science Foundation and National Institutes of Health, program managers navigate between these two extremes, setting some funds aside to target high-priority areas and using the rest to cover the widest possible range of meritorious proposals. This middle path seems like the most rational way to proceed, but it still requires making choices. How much should be set aside for high priority topics? What should those topics be? How should we define merit? Expert opinion can provide a helpful guide, but leading experts can have remarkably different opinions about what matters and what should be prioritized. Moreover, experts and administrators alike can be risk averse, giving an edge to high-profile, well-established concepts. What’s really needed is a data-driven framework to help guide decision-making, one that doesn’t simply repackage prestige or incumbency. Recognizing breakthroughs years in advance Many breakthroughs fail to attract funding or recognition at the earliest stages of development. Katalin Karikó, for example, spent years struggling to win grants for work on mRNA that would eventually win her and Drew Weissman a Nobel Prize. Similar stories can be told about Jim Allison’s groundbreaking studies leading to the development of cancer immunotherapy, Stan Pruisner’s demonstration that prions can self-replicate without DNA, or Robin Warren and Barry Marshall’s proof that Helicobacter pylori, not stress, causes ulcers. Yet at some point, the scientific community recognizes and responds to transformative breakthroughs like these. How does that change happen? And what if science funders could identify the areas that are on the cusp of a breakthrough? Those questions led my collaborators and me to study how scientists responded to past breakthroughs. Based on patterns in that data, we developed a means of predicting future breakthroughs, using biomedicine as a proof of concept. It’s worth taking a moment to describe how our approach works. Briefly, our prediction process begins by grouping the 18 million or so peer-reviewed papers in PubMed, the authoritative database of biomedical research, into roughly 50,000 unique topics. A small subset of these topics are so widely acclaimed as breakthroughs that they have been recognized with a major prize like a Nobel or a Lasker Award. We theorized that studying the development of these outliers over time, especially before they gained acclaim, was the key to identifying future instances of them. After defining topics, we chose 21 representative breakthroughs and asked what they looked like before they won prestigious prizes. To answer that question, we re-ran our topic-mapping algorithm repeatedly, winding back the clock one year each time, stringing together the years to follow the progress of each field as it grew and advanced. We found that in each case, the years leading up to a discovery followed a pattern: a burst of papers on a new, rapidly evolving topic, many of which quickly became influential. These characteristics—the percent of papers that are new, the percentage of papers that are brought in from other topics, and the influence of each individual paper—can all be measured separately for any given topic. Together, they act as a predictive signal that is detectable an average of five years before a transformative discovery is made, and up to thirty years before the discovery receives a major prize. Scanning the current research landscape for topics that display this signal allows us to predict what work will likely produce a future breakthrough. Each year we analyzed includes four or five signals, a number that appears to have remained constant across a twenty year time frame. In their classic work on the sociology of science, Bruno Latour and Steve Woolgar established that the desire to participate in a major discovery is an important motivator for scientists as they consider whether they should take up (or abandon) a research problem. Although further work is needed, the simplest explanation for our results is that this behavior is widespread enough to detect at scale. A foundational advance, or something like it, draws the attention of scientists and causes them to change the direction of their research. They vote with their feet, staking their own reputation and careers by publishing on and citing the new idea. That upswell of interest is the foundation of our breakthrough signal. What kind of research does our model identify as a breakthrough? After building a model based on the patterns in our 21 preselected breakthroughs, we tested it by identifying all early signals of discovery from 1994 through 1997. Of the 18 signals we found in that time period, 17 can be traced forward in time to a breakthrough. Examples include super-resolution fluorescence microscopy (see the image above), the directed evolution of proteins and enzymes (Chemistry Nobel, 2018), and sequencing the human genome (National Medal of Science, 2008). The discovery of the role of leptin signaling in obesity is a particularly interesting case study. Around 1950, scientists noticed the existence of a type of lab mouse that suffered from a unique inherited form of obesity. When given the freedom to choose their own diet, these mice ate more than normal and preferred food that was high in fat. Researchers had few clues as to why the animals overate; early experiments pointed to the existence of a soluble ob factor found circulating in the bloodstream that regulated appetite, but its identity was unknown. In 1994, Jeffrey Friedman and colleagues identified and sequenced the ob gene, noting that the protein it encoded appeared to fit the profile of a circulating factor. A year later, a trio of high-profile publications demonstrated that ob was a hormone that regulated body weight and fat deposition by regulating appetite. One of these was co-authored by Friedman, who christened it leptin from the ancient Greek word for thin. Using our model, the data from 1996 make it clear this advance would become a breakthrough. Scientists had flocked to study the biology of the new hormone, generating the flurry of new papers and citations required to produce a signal. One of these demonstrated that serum leptin concentrations reflected the amount of adipose tissue in the human body, providing clinical validation of the earlier mouse studies. Before the identification of leptin, scientists were unable to point to a specific molecule that controlled appetite and adiposity, so that it was impossible to rule out non-physiological causes of obesity; its characterization fundamentally changed our concept of weight gain. In 2010, Friedman and fellow pioneer Douglas Coleman were awarded a Lasker for the discovery. Our work also identifies breakthroughs in clinical practice and behavioral and social sciences, even though these areas are less likely to draw the attention of major prize committees. One example that falls into this category is the introduction of endovascular aneurysm repair, a minimally invasive surgical procedure for the treatment of abdominal aortic aneurysm, a leading cause of death among Americans over the age of 65. Relative to the previous standard of care, it reduces in-hospital mortality by almost four-fold. In 2017, Timothy Chuter received the American College of Surgeons’ prestigious Jacobsen Innovation award for his multiple refinements to the technique. Another under-recognized breakthrough identified by our model is the development of standardized survey instruments to assess the quality of life for HIV+ patients. The antiretroviral cocktails introduced in the mid-1990s reduced AIDS mortality, but treatment came with serious side effects. The new evaluations showed that patients whose disease progressed had worse physical functioning than Americans with other chronic diseases, while those who were asymptomatic maintained a health-related quality of life on par with the overall US population. This evidence made it possible for patients and activists to argue that even in the absence of a total cure, and in spite of the side effects, alleviation of symptoms was a worthwhile priority for clinicians. My colleagues and I have failed to identify any significant recognition for the physicians and health policy experts who pioneered this advance, although in 2016, researchers called for the World Health Organization to set targets for good health-related quality of life as part of its framework to end the AIDS pandemic. From forecasting to funding How should science funders use our predictions? Any serious discussion of what we should do with this new capability needs to begin with an understanding of its limitations. We can’t (and shouldn’t) invest all of our resources in the small number of topics predicted to produce breakthroughs. Innovative new fields are born from existing ones; they rarely arise de novo. If funders don’t maintain a diverse portfolio, the breakthroughs of tomorrow will have no antecedents. Think of this as eating the seed corn, or killing the goose that lays the golden egg. There are also multiple goals of funding beyond basic scientific discovery, including translating discoveries into clinical practice, developing new technologies, supporting economic development, and training new scientists. The investments needed to accomplish these goals are likely different from those required to support emerging breakthroughs. Finally, we must be aware that we may not capture every instance of a breakthrough. The concept is fuzzy, and not every significant discovery is recognized with a major award. Further, breakthroughs are rare, meaning that our dataset is, by necessity, small. This makes formal estimates of accuracy challenging. Although our overall success rate appears to be high, any one signal may turn out to be a false positive. We found one apparent example: the development of the third generation COX-2 inhibitors, Vioxx and Celebrex, which were much celebrated in the early 2000s as effective but non-addictive pain relievers, meets all the algorithmic criteria of a breakthrough. Five years after it received FDA approval, researchers demonstrated that Vioxx was associated with serious cardiovascular complications, and the manufacturer voluntarily pulled the drug from the market. Celebrex remains available, although like other NSAIDs, it carries an FDA warning for increased cardiovascular risk. Decision makers who were overly focused on the breakthrough potential of this research might have wasted substantial resources nurturing an area that ultimately proved to be a failure—but so would those who relied on expert opinion at the time. That said, the potential benefits of funding the next mRNA vaccine or cancer immunotherapy years earlier than we might have are large. When we can’t assume the outcome of an action, it’s worth conducting an experiment. Can targeted support for areas that are poised to produce a breakthrough increase the return on scientific investment without cannibalizing future advances? With the necessary administrative infrastructure in place, conducting this experiment would be straightforward. First, identify all the breakthrough signals between 2018 and 2023, select half at random, and commit to a decade of investment. For biomedicine, a six year window should yield about 30 topics with the potential to produce a breakthrough. Providing strong support to half of these might be accomplished for $300 million a year. That’s roughly half of the recent annual budget of the NIH Common Fund or around 20% of the fiscal year 2025 budget for ARPA-H. After five years, then again at ten, compare to see which group — the one that was actively managed, or the control — produced more breakthroughs, and on what timescale. Although we used biomedicine as an example, the same experiment could just as well be run for physics, materials science, or any other discipline. Any attempt to undertake such an experiment should keep three points top of mind. First, we can predict the topic of future breakthroughs, but the people and vision for how to move the work forward are still important. In practice, this means success requires active program managers with the expertise to develop the science and the authority to do so, including by recruiting investigators. Second, we would be wise to learn from the failures of past attempts to fund transformative research. High among these are funding modestly repackaged work, confusing the genuinely novel with the merely unfamiliar, and relying too much on incumbent investigators. All of these risks can be mitigated by thoroughly and intelligently integrating high quality data into portfolio management. Finally, we need to have patience. Even with strong funding support, producing a breakthrough takes time. If supporting breakthroughs is the best way to nurture the birth of new fields, we also need to accurately describe and properly manage the other two stages, so that we invest wisely throughout the productive lifetime of ideas and divest once they reach the point of diminishing returns. We would benefit from more study of all of these phases, especially the transition from one to another. More research could answer questions like: When does a breakthrough become an established field? How do the availability of funding, the size and characteristics of the available workforce, and the accumulation of evidence that disagrees with prevailing models affect a field’s decline? Exactly how do old ideas give birth to new ones, and can we speed up the process? The more we understand about the dynamics of scientific progress, the better we can maximize the odds that our curiosity leads to results. I’d call that finding a way to make our own luck.
When WA's behavioral health system failed her son, Blaine mom declared herself an unfit parent
A mother's experience with 'cycle of insufficient care' for troubled children in Washington
Politics: What Donald Trump’s Defense Policy Means For Black Service Members
Black Americans serving in the U.S. military have long lived with a great contradiction. The country they’re fighting to protect is the same one that’s failed to serve and protect them.Despite this, Black Americans continue to enlist. There are over 350,000 Black active duty and select reserve members and more than 2.4 million Black veterans. That’s according to the Institute for Veterans and Military Families at Syracuse University.This year, Defense secretary Pete Hegseth has blocked or delayed the promotions of more than a dozen Black and female senior officers. He’s also dismissed several high-ranking Black and female officers, according to The Atlantic. This comes amid the second Trump administration’s aggressive rollback of programs and policies connected to diversity, equity and inclusion.Black military members have always battled discrimination. But for some, this is a step too far in the wrong direction. So, what does their future hold? And what does it mean for the U.S. military?Find more of our programs online. Listen to 1A sponsor-free by signing up for 1A+ at plus.npr.org/the1a.
Lexington-Fayette Health Department shuts down mall restaurant
The health department closed down a restaurant in the Fayette Mall after repeated failed inspections according to the Lexington Herald-Leader.
While Mainers still reeling from health insurance hikes, insurers propose more
Kennebunkport resident Kristin Fuhrmann-Simmons saw her family’s health insurance costs increase ten-fold after Congress last year failed to extend pandemic-era tax credits for plans purchased on the marketplace. Next year, she’s facing another potential 20% increase, this time due to a proposed hike by her insurance provider. “I didn’t know that the cost of care […]
Here's Why Boston Celtics Failed to Complete Trade For Giannis
The Celtics made a strong offer for the two-time MVP, but he was ultimately dealt to the Miami Heat.
Romania’s Political Turmoil Deepens After PM Hopeful Loses Vote
Romania’s prime minister nominee failed to win parliamentary approval for his proposed cabinet, prolonging a political deadlock that risks stalling key reforms for crucial European Union recovery funding.