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Seton Hall Students Discuss Big Economic Ideas on Campus and in Nebras
From campus discussions to a national conference, students engaged deeply with economic ideas, strengthening analysis and communication skills.
Key US science panels are being axed - and others are becoming less open - College of Arts and Sciences
A Nature analysis shows that the Trump administration has terminated more than 100 advisory committees to science agencies — and reduced the transparency and independence of those that remain. … “I would hope that in the future, in this administration … Read more
A PvE Analysis of Steeled Resolve: Taken Over
Steeled Resolve adds new Shadow Pokémon, but only Shadow Landorus truly stands out as a meaningful PvE raid pick.
Kirkwood to launch Business Analytics Technician program in fall 2026
Kirkwood Community College will introduce a new Business Analytics Technician program beginning in the fall 2026 semester, the college announced Wednesday, April 29. The online, two-year program prepares students for careers in data analysis and business intelligence. According to Lightcast labor market data, demand for business analytics technicians — classified as a subset of data […]
InvestigateTV+: ‘Junk science’ and harassing debt phone calls
We look at the discredited FBI bullet analysis; a method experts now call “junk science,” and the push to reopen convictions
Report: iPhone Memory Costs Set to Quadruple by 2027
Memory could account for as much as 45 percent of an iPhone's component costs by 2027, up from around 10 percent today, according to a JPMorgan analysis cited by the Financial Times ($). Apple buys memory for roughly 250 million iPhones a year and has historically been one of the largest customers in the category. But Apple has reportedly now gone from a position where it could set terms to one where it now has to compete with rivals for supply.
Analysis | Trump is a target of political violence, but he’s hardly its only cause
Social upheaval, deep polarization and social media are primary drivers of the phenomenon, which has touched Republicans and Democrats alike.
'Lifestyle analysis' found Moorhead business owner hid income while collecting SNAP
A Minnesota business owner is facing several felony charges after investigators say she filed false tax returns while fraudulently receiving SNAP benefits.
Analysis: Unstable people in unsettled times – America revisits the political violence of the '60s and '70s
How to implement AI-powered coronary plaque analysis software—and ensure you get paid
The use of AI to evaluate plaque buildup in CCTA images has been one of cardiology’s biggest ongoing trends. Implementing this software into existing workflows, however, can be a challenge. An upcoming webinar is focused on providing guidance to hospitals and cardiology practices hoping to learn more about this topic.
Airfare data: Ticket prices could jump by 14% if Spirit collapses
An analysis of air fares shows a reverse "Spirit effect," in which ticket prices would rise if the budget carrier folds.
A Special Session in Florida — split signals, different speeds
New data analysis and polling reveal a mixed mandate.
Scientists finally solve mystery of strange “golden orb” found 2 miles deep
A mysterious “golden orb” found more than two miles deep in the Gulf of Alaska left scientists baffled for over two years, sparking wild speculation about its origins. After an intensive investigation combining deep-sea expertise, microscopic analysis, and advanced DNA sequencing, researchers finally cracked the case. The strange object turned out not to be an egg, sponge, or anything alien, but the remains of tissue from a giant deep-sea anemone.
Assessing Six Flags Entertainment (FUN) Valuation After Quantum Accelerator Coaster And Park Upgrades Debut
Six Flags Entertainment (FUN) is back in focus after Six Flags New England previewed its new Quantum Accelerator coaster, along with refreshed dining and guest experience upgrades across the park. See our latest analysis for Six Flags Entertainment. At a share price of $18.28, Six Flags Entertainment has a 30 day share price return of 10.12% and an 18.01% share price return year to date. However, the 1 year total shareholder return of 49.36% and 3 year total shareholder return of 56.66%...
RJ to launch VegasBusiness, authoritative source of local business news
The Review-Journal on May 3 will launch VegasBusiness, a multiplatform brand that delivers analysis and insight to the business leaders of Southern Nevada.
2026 NFL Draft team grades: Live updates, report cards for all 32 teams
Every pick shifts the board: Live team grades update in real time with analysis on key moves
2026 NFL Draft grades, tracker: Live Round 7 analysis for every selection made in order
Josh Edwards grades the seventh round of the 2026 NFL Draft.
Scientists Reveal The Optimal Amount of Sleep to Lower Dementia Risk
A huge analysis uncovers the sweet spot.
2026 NFL Draft grades, tracker: Live Round 6 analysis for every selection made in order
Josh Edwards grades the sixth round of the 2026 NFL Draft.
2026 NFL Draft grades, tracker: Live Round 5 analysis for every selection made in order
Josh Edwards grades the fifth round of the 2026 NFL Draft.
Analysis: VAR frustration for Toffees
It isn't that long since Everton were in West Ham's position and fighting for Premier League survival - but now they are in the battle to secure European football next season and, particularly for that reason, this will have been a frustrating result. David Moyes' side have one of the best away records in the Premier League and it looked they would earn a point with Kiernan Dewsbury-Hall's late strike. Moments before Dewsbury-Hall equalised, the Toffees thought they had a penalty when the ball struck Mateus Fernandes' hand inside the box as he grappled with Thierno Barry.
2026 NFL Draft grades, tracker: Live Round 4 analysis for every selection made in order
Josh Edwards grades the fourth round of the 2026 NFL Draft.
PENN Entertainment (PENN) Near Breakeven Q1 Loss Tests Bullish Profitability Narratives
PENN Entertainment (PENN) opened Q1 2026 with revenue of US$1.8b and a basic EPS loss of US$0.02, alongside net income excluding extraordinary items of a US$2.3m loss. The company’s quarterly revenue moved from US$1.7b in Q1 2025 to US$1.8b in Q1 2026, while EPS shifted from a profit of US$0.73 to a small loss in the latest quarter, creating a mixed picture of topline scale against continued pressure on profitability and margins. See our full analysis for PENN Entertainment. With the headline...
2026 NFL Draft grades, tracker: Live Round 3 analysis for every selection made in order
Mike Renner grades the third round of the 2026 NFL Draft.
2026 NFL Draft grades, tracker: Live Round 2 analysis for every selection made in order
Mike Renner grades Round 2 of the 2026 NFL Draft
NFL draft picks tracker: Analysis for every 2026 second- and third-round selection
The 2026 NFL draft is fully underway. The Round 2 and 3 tracker offers instant analysis on all 68 picks made Friday night in Pittsburgh.
Bipartisan-cited science is powerful but rare
New analysis explores how policymakers engage with science
Civil-Military Relations under the Trump Administration (Part I) -- Politicians and Military Leaders | List of Articles | International Information Network Analysis
IINA provides ongoing analysis of international affairs both by region—such as North America, China, and Europe—and by such topics as human security, nontraditional security threats, and cyber security. The articles on this site, written by experts at the Sasakawa Peace Foundation and guest contributors, are carefully selected for their objectivity, accuracy, timeliness, and relevance for Japan.
Dallas Cowboys NFL Draft tracker: Picks, grades, analysis for every selection
Track every Cowboys pick in the 2026 NFL Draft with live grades, analysis and updates
NFL draft picks tracker: Analysis for every 2026 first-round selection
The 2026 NFL draft is finally here. The first-round tracker offers instant analysis on all 32 picks made Thursday night in Pittsburgh.
A Look At PENN Entertainment (PENN) Valuation After Recent Share Price Volatility
Assessing PENN Entertainment after recent performance PENN Entertainment (PENN) has drawn fresh attention after a mixed stretch in its share price, with a 1 day decline of about 4.5% contrasting with modest gains over the past month and past 3 months. See our latest analysis for PENN Entertainment. At a share price of $14.77, PENN Entertainment has seen pressure in the very short term, with a 1 day share price return of about a 4.5% decline and a 7 day share price return of a 7.8% decline...
Substantiation, Entity Indebtedness, and Business Expense Deductibility: An Analysis of the Simmons Case — Current Federal Tax Developments
Cathryn A. Simmons v. Commissioner, T.C. Memo. 2026-34 (April 22, 2026) In a recent memorandum decision, the United States Tax Court addressed recurring substantiation issues surrounding closely held entities, commingled funds, and rental real estate deductions. The taxpayer, Cathryn A. Simmons, p
Restrictions on obesity drug coverage force patients to pivot
Twelve million people lost coverage for Zepbound over the last year. The same number of people lost coverage for Wegovy, according to an analysis by GoodRx, a drug discount website.
A Look At Sphere Entertainment (SPHR) Valuation As Upgraded Earnings Outlook Lifts Momentum
Momentum shift puts Sphere Entertainment in focus Recent favorable revisions to earnings estimates and a strong momentum score have pushed Sphere Entertainment (SPHR) onto more investors’ radars, as the stock’s performance has differed from both the broader market and its media peers. See our latest analysis for Sphere Entertainment. Despite a 2.8% decline in the latest session and a 4.4% 7 day share price pullback, Sphere Entertainment’s 30 day share price return of 18.8% and very large 1...
Assessing Madison Square Garden Entertainment (MSGE) Valuation After New Impossible Foods Partnership
Madison Square Garden Entertainment (MSGE) is in focus after announcing a multiyear partnership with Impossible Foods. The deal introduces branded plant-based offerings, a dedicated Impossible Grille concession and expanded in-arena promotion across Knicks and Rangers home events. See our latest analysis for Madison Square Garden Entertainment. The stock is trading at $61.42 after a 9.37% 1 month share price return and 13.03% year to date share price return. The 1 year total shareholder...
DNA reveals a hidden pitviper species in China
A vivid green pitviper hiding in Sichuan’s misty mountains has been revealed as a completely new species. Scientists had overlooked it for decades, assuming it was a common snake—until DNA analysis proved otherwise. Named after Laozi, it features striking differences between males and females, including bold stripes and eye colors. The discovery highlights just how many unknown species may still be lurking in well-studied regions.
Analysis: Fans have turned on Rosenior
It marked radical new low point in a bleak run of five consecutive league defeats without a goal for Chelsea - their worst such sequence in more than a century and one that few supporters have witnessed in their lifetime. Given the club's success over the past 25 years, it is perhaps understandable that patience is thin for a head coach appointed just three months ago from Chelsea's partner club, Strasbourg. There were early signs that the night might not unfold as Rosenior had hoped.
Behavioral health data exchange challenges impede interoperability, says ONC
Technical barriers, workforce limitation, privacy concerns and cost may all contribute to lower rates of electronic exchange of health information by mental health and substance abuse treatment facilities, a new analysis shows.
Shaky political science: using "simulated" elections over real-world elections
[Dear DSOS readers – 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 early December, we examined over 40 studies focused on ranked choice voting. We found that 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 three articles in our series: the first one summarizing the overall results of our report, the second one analyzing 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, and a third article showing an admirable example of two political scientists holding two other political scientists accountable for their flawed, sloppy research]. In this fourth article in our “Shaky Political Science” series, we shine a spotlight on seven studies that were web-hosted and funded by New America’s Political Reform Program and its Electoral Reform Research Group (the ERRG is an ad hoc committee headed by New America’s Political Reform Program and joined by the American Enterprise Institute, the Unite America Institute and Stanford University’s Center on Democracy, Development, and the Rule of Law). This research consortium has been led by Lee Drutman, senior fellow with New America’s Political Reform Program. These seven studies are simply not credible from any objective standard about how political “science” is supposed to illuminate our understanding of either ranked choice voting or politics in general. The feature that six of these seven studies have in common is that they all used surveys – artificial, simulated elections -- to attempt to say something cogent or interesting about ranked choice voting (RCV) elections. None of them used real world data from actual RCV elections – either the 1000+ elections in the US or the many thousands of elections from places like Australia, Ireland and elsewhere where RCV has been used for 100 years. While a few of these studies conclude with some mixed positives about RCV, our analysis here is content neutral. The idea that, with a political reform like RCV, you can ask respondents in a mock, artificial election to vote with that method, with only the barest of explanation about how RCV works or its likely impacts (i.e. no spoiler candidates, majority winners, voters liberated to pick their favorite candidates, coalition-building), and then ask them their thoughts/reactions about voting in that system, with fake candidates and no real campaigning, no real exposure to an actual election or actual candidates, rests on some very puzzling assumptions. The findings of these seven studies actually are contradicted by the findings from many other studies based on real-world RCV elections. These New America studies also failed to list the real-world RCV studies in their own citations, instead including those studies that reinforced their conclusions. The seven studies featured in this article were chosen because they form a cohesive cohort which precisely illustrates one of the main points of our research paper, namely that using surveys, i.e. artificial elections, or mathematical/theoretical models, instead of real-world data, is in fact “shaky political science.” Below are summaries of our analysis of five of the seven New America studies. You can read our complete analysis of all seven studies at our paper, “Shaky political ‘science’ misses mark on ranked choice voting.” Choosing to “Vote As Usual” by Andre Blais, Carolina Plescia, and Semra Sevi. New America. (Blais et al., 2021). This study, web-hosted and funded by New America’s Political Reform Program and its Electoral Reform Research Group, used two surveys in which respondents completed ballots for simulated elections using plurality, approval, RCV and point (Score) voting. In both cases the authors provided the respondents with only minimal explanation of each method. For example, the entire explanation for RCV was “For this vote, rank the candidates from your first to your last choice (you do not need to rank them all). This is called the ranked vote.” That’s it. The study did not provide any context or explanation to survey respondents about why she/he might want to rank multiple candidates. Participants were not even told that ballots would be tabulated using an “instant” runoff, not to mention any description of RCVs ability to eliminate the spoiler effect or liberate voters to rank their favorite candidates without fear of helping the “greater evil” candidate to win. That’s like taking an iPhone back in time to 1970 and asking someone if they like it better than their rotary phone without explaining how it works. Their first survey targeted states that held 2020 Super Tuesday Democratic primaries and used the real candidates’ names in the survey; the second survey used fictitious candidates. In other words, they surveyed respondents who had only ever participated in plurality elections, had no history or background with using RCV or any of the other methods, had no clue about its likely impacts, and did not communicate how the alternative methods would be counted, and then asked them: “How satisfied are you with using each system?” Predictably, the winner was plurality elections, the system used for president, Congress, gubernatorial and state legislative elections – in other words, the method they have been using, year after year, all their voting lives. With so little explanation of RCV and its impacts, this study is simply not credible in discovering anything useful about real-world RCV elections. It merely shows that a basic voter education campaign is needed when adopting a new election system. Additionally, the result contradicts many other post-election surveys following real RCV elections, asking opinions from voters who had just participated in a RCV election, that showed a great deal of satisfaction with RCV (see details on that in Studies 22-25 in our paper, as well as the four studies cited in the review for Study 28). Share Other studies on “satisfaction” and “understanding” make similar mistakes, in terms of basing their surveys on inadequate explanation to respondents and lack of education about context. How could any survey ever hope to measure accurately, in essence simulate a real-world election, without actual campaigning candidates, the media writing about those candidates, organizations endorsing candidates and voters being inundated with crucial information? More than anything, what these “studies” based on surveys show is that if you ask voters about something they don’t know very much about, and fail to adequately educate them, their responses will unsurprisingly reflect their confusion. Equally puzzling is that New America’s Electoral Reform Research Group, headed by political scientist Lee Drutman, found this to be a credible enough study that they not only published it but highlighted it in Drutman’s own discussion of research related to ranked choice voting. This pattern was repeated in study after study featured by New America’s Electoral Reform Research Group. For example in Ranked-Choice Voting and Political Expression: Voter Guides Narrow the Gap between Informed and Uninformed Citizens by Cheryl Boudreau, Jonathan Colner, and Scott MacKenzie, the researchers based their analysis on a survey which found that respondents who were asked to vote in a simulated RCV election, with minimal explanation of RCV or how it works, displayed less evidence of being informed about how to use RCV effectively, with the least informed voters ranking fewer candidates. As pointed out under the study above, in a real election voters are informed by a wide variety of methods, including public education by the election administration, by interested political groups, the media, and the candidates themselves who benefit from voters being aware of how to vote in the new system. In Support for Ranked-Choice Voting across Race and Partisanship by Joseph Anthony, David C. Kimball, Jack Santucci and Jamil Scott, the researchers used respondents from different parties and races voting in simulated plurality and RCV elections, who indicated their satisfaction with each voting method. Instead of using real world election results, the authors fell back on the easy, armchair and less reliable academic research methodology of making up mock elections. As with the other studies, little explanation was given of how RCV works or what its implications might be (electing majority winners or eliminating spoilers, for example). Unsurprisingly, this study found that respondents were not very satisfied with RCV. However, when the authors added an explanation that RCV has a tendency to elect more women and people of color, they found that this greater explanation increased the preference for RCV. The more voters were familiar with it, and the more they understood potential positive impacts – surprise! -- the more they were open to switching away from the status quo. Of note, the results from this study are thoroughly contradicted by a number of other studies whose data was obtained from real RCV elections with real voters. Those studies show a great deal of satisfaction with RCV. More “fake election” research An interesting wrinkle on this “research by fake elections” approach, which only served to illustrate how unreliable such “research” can become, was taken in Ranked-Choice Voting, Runoff, and Democracy: Insights from Maine and Other U.S. States by Joseph Cerrone and Cynthia McClintock_,_ also web-hosted and funded by New America’s ERRG. It gets high marks for creativity, but an eye-roll for thinking this could possibly add anything meaningful to our understanding of real world RCV elections. This study tried to determine whether RCV, plurality or two-round runoff elections provided greater voter satisfaction and acceptance of election results. To determine that, the authors conducted a survey asking if voters were satisfied with a fictional newspaper report of an election, with three different versions given to respondents – plurality, runoff and RCV, with variations of Republican/Democrat winners and variations of “come-from-behind” winners,” i.e. candidates not initially in first place but who win the “runoff.” Again, a minimal explanation of RCV or how it works was given, and the survey showed that respondents had the greatest unfamiliarity with RCV than the other methods. The unsurprising result? Respondents were much more satisfied with “come-from-behind” victories in a traditional two-round runoff election than in RCV, even though RCV is also a runoff system but with a single round of counting. Interestingly, the dissatisfaction with RCV disappeared for those who were more familiar with RCV. In fact, among those respondents who were “very familiar” with RCV, they were equally satisfied with RCV, runoff and plurality. Surprise, surprise. Again, what this study revealed, more than anything, is not only the inadequacy of the explanation for RCV given by the authors of this study, but the failure of the research format itself, thinking that such an artificial mock election could somehow simulate what actually happens in the real world in a real RCV election. Those four studies reviewed above are fitting examples of inadequate and shaky political “science.” Other studies reviewed in our paper from the New America/Electoral Reform Research Group cohort which also used mock elections included: Ranked-Choice Voting is an Acquired Taste by Joseph Anthony and David C. Kimball. New America. (Anthony et al., 2021). Ranked-Choice Voting is No Refuge for Extreme Candidates by Melissa Baker. New America. (Baker, 2021). Also included in this New America cohort is Does Ranked-Choice Voting Reduce Racial Polarization? by Yuki Atsusaka and Theodore Landsman, which actually did use real-world election results data but applied an odd and unconventional methodology to the data which relied on shaky assumptions and non-real-world scenarios that were too divorced from reality. To determine levels of “racially polarized voting,” the researchers imagined “ethnic parties,” by which they mean political parties for each ethnic group, which was especially odd since the election data they were using came from nonpartisan RCV races. But then they made an even odder assumption, namely that since race and ethnic characteristics of studied voters were not available, the authors tried to infer that information based on who voters selected and the racial make-up of voters in each district. This amounted to little more than vague and ambiguous guesswork dressed up with a bunch of mathematical equations used to give it a veneer of scientific appearance. Indeed, it seemed to assume racial polarization in order to prove racial polarization. Based on this questionable methodology, the authors concluded that RCV doesn’t reduce racial polarization. But the premise of this study missed an obvious reality: since RCV incentivizes more candidates to run and can result in more diverse fields of candidates, one would expect more racially-polarized voting in voters’ top rankings, not less, because more voters would have someone on that ballot who represents their racial or ethnic identity and more freedom to vote for their real first choice. By encouraging more diverse candidates and eliminating the spoiler effect, RCV facilitates voting for a favorite candidate of your own race and then selecting a second choice with the best likelihood of winning. The real measure is what voters do with their additional rankings – do they consider other candidates and vote “for the best of the rest”? This study didn’t tell us anything useful about that. But readily available data shows this is common in real RCV elections, and candidates act on this knowledge by engaging with voters outside their racial group. So the authors of this study failed to consider or account for what actually happens in real-world elections, and their conclusions are tainted by this failure. New America has contributed a great deal over the past 2.5 decades to our understanding of many policy areas, including politics and political reform (full disclosure: Steven Hill, one of the authors of this article and of the “Shaky Political Science” research paper and series, is a former senior fellow and former director of New America’s political reform program, 2005-2010). So it was especially disappointing that New America funded and published such a large batch of dubious studies about ranked choice voting. The stated praiseworthy goal of its Electoral Reform Research Group was to inspire new academic research about ranked choice voting that would shed light and help the public better understand the impacts of RCV. Instead, the ERRG research did just the opposite. It produced dubious research that created more confusion and misinformation. In so doing, New America’s political reform program contributed to “shaky political science.” Steven Hill and Paul Haughey Share Upgrade to $5 subscription Thanks for reading DemocracySOS, a reader-supported digital portal for the pro-democracy movement. Subscribe for only $5 per month to receive full benefits and to support our work. Subscribe
Assessing PENN Entertainment (PENN) Valuation After Recent Share Price Momentum
Event context and recent performance PENN Entertainment (PENN) has been drawing attention after recent share price moves, with the stock closing at US$15.84 and showing positive returns over the past week, month, and past 3 months. Investors are weighing this against its 3 year and 5 year total return record. See our latest analysis for PENN Entertainment. The recent 30 day share price return of 15.87% and 90 day share price return of 15.37% contrast with a 3 year total shareholder return...
Trump, Pope Leo And A New Chapter in America’s Religious Politics
(ANALYSIS) American religion has rarely, if ever, seen anything quite like these past weeks. Start with President Donald Trump’s profane Easter Sunday message to Iran: “Open the [unprintable F-bomb] Strait, you crazy bastards, or you’ll be living in Hell - JUST WATCH! Praise be to Allah." The l
A Simpler Path to Super-Resolution: Scientists Reinvent Microscopy
A new imaging framework is pushing the boundaries of how scientists observe life at the microscopic scale.
How Employers Support Lower-Waged Workers' Access to Health Insurance Options
Health insurance makes up 8% of total employee compensation on average, and while most employees take up health insurance when it is offered, lower-wage workers are far less likely to be able to access coverage, according to an analysis of survey data and focus groups with more than 100 U.S. employers with over a quarter of a million employees.
Quarter of a million people could lose job by middle of 2027 as UK ‘flirts with recession’, analysis says
Twin reports from top accounting firms underline scale of economic threat as Iran war shatters business confidence
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Schematic illustration of overpotential deconvolution in anion exchange membrane water electrolysis using electrochemical impedance spectroscopy (EIS) and distribution of relaxation times (DRT) analysis.
New study reveals how maze-like magnetic patterns form and evolve in materials
Maze magnetic domains in soft magnetic materials strongly influence energy loss in electric motors, particularly at high temperatures. However, existing models struggle to explain their complex, temperature-dependent behavior. To address this gap, researchers developed an entropy-extended Ginzburg-Landau model combined with data-driven analysis to study these structures. The approach reveals how entropy and energy interactions drive magnetization reversal and increasing domain complexity, providing new insights into magnetic energy-loss mechanisms.
Health visitors call for limits on 'impossible' 1,000-family caseloads
BBC analysis shows the number of health visitors in England has almost halved in the last 10 years.
Analysis: Silk and steel win the day
Manchester City secured the victory that maintains their growing momentum and applied further pressure on Arsenal through the familiar route of a Erling Haaland winner. Rayan Cherki's goal was the result of a touch of genius and sleight of foot to bamboozle Arsenal's Gabriel and Piero Hincapie before sliding in a perfect finish. After Gianluigi Donnarumma's error swiftly gifted Arsenal a way back into the game, City had to dig deep to show reserves of resilience before Haaland was once more the match-winner.
Analysis: Senior players step up
Arne Slot's side had lost their four previous away games in all competitions and, although a draw would hardly have been a bad result, there is no understating how big this win was for Liverpool. The Egyptian scored in his first Merseyside derby in 2017 and has now scored in his last. Van Dijk's goal was the result of an Everton weakness identified by Liverpool set-piece analyst Lewis Mahoney that was targeted all game.
Analysis: Watkins stars to boost World Cup chances
Tammy Abraham's strike was just his third goal for Aston Villa since he rejoined the club from Besiktas in January. Villa need just six more points to ensure Champions League qualification, with Premier League games against Fulham, Tottenham, Burnley, Liverpool and Manchester City still to come. Abraham may have got the winner but the striker he replaced, Ollie Watkins, was Villa's star with two goals and an assist.
A Look At AMC Entertainment Holdings (AMC) Valuation After Recent Share Price Momentum
AMC Entertainment Holdings (AMC) has recently drawn fresh attention as the share price moved to US$1.86, with a one-month return of 89.7% and a three-month return of 15.5%. See our latest analysis for AMC Entertainment Holdings. While the recent 1 month share price return of 89.7% suggests strong short term momentum, the 1 year total shareholder return decline of 33.1% and 5 year total shareholder return decline of 96.6% highlight how volatile the ride has been for long term holders. If fast...
A Look At AMC Entertainment Holdings (AMC) Valuation After Record Easter Trading And Odeon Refinancing
AMC Entertainment Holdings (AMC) has drawn fresh attention after reporting record combined global admissions and food and beverage revenue over the five day Easter weekend, helped by the release of THE SUPER MARIO GALAXY MOVIE and strong attendance across its theatres. See our latest analysis for AMC Entertainment Holdings. The recent record Easter trading, together with refinancing at Odeon and fresh attention from B. Riley, has coincided with sharp short term share price momentum. This...
A Look At Flutter Entertainment (NYSE:FLUT) Valuation After Citi Downgrade And Buyback Delay Concerns
Why Citi’s downgrade has put Flutter Entertainment (NYSE:FLUT) under closer scrutiny Citi’s downgrade of Flutter Entertainment (NYSE:FLUT) to sell, tied to concerns about US growth, profit targets, and possible delays to buybacks, has pushed investors to reassess the stock’s risk profile. See our latest analysis for Flutter Entertainment. At a share price of $110.08, Flutter’s 7 day share price return of 7.52% and 1 day gain of 0.94% sit against a 90 day share price return decline of 41.59%...
LIVE SCORE UPDATES & ANALYSIS: Arkansas baseball vs. Georgia Game 3
Follow along as the Razorbacks play the Bulldogs in the rubber game.
700-year-old mummy from Bolivia contains earliest confirmed evidence of strep throat bacteria in the Americas
A DNA analysis of pathogens from a pre-Hispanic mummy revealed that the bacterium that causes scarlet fever and strep throat was present in the Americas prior to European colonization.
Detroit Lions NFL Draft Injury Report: Oklahoma WR Deion Burks
Deion Burks NFL Draft medical report. Full injury analysis heading into the 2026 NFL draft. How will it affect Detroit Lions draft strategy?
How Dylan Patel and SemiAnalysis Grabbed Sway in Silicon Valley
For Dylan Patel, founder of SemiAnalysis, an influential AI industry newsletter and research firm, Nvidia deserves the kind of dogged observation and study the tabloid press once devoted to Princess Diana. Hescrutinizesthe chip giant’s new products,documentsits delays andscoopsdetails about its ...
Location-Based Entertainment Market Analysis Report 2026: $14.35 Bn Opportunities, Trends, Competitive Landscape, Strategies, and Forecasts, 2020-2025, 2025-2030F, 2035F
The location-based entertainment market offers opportunities in themed venues, digital gaming experiences, immersive VR/AR attractions, and interactive content. Growth is driven by rising consumer spending, technological innovations, and increased global tourism, with Asia-Pacific poised for rapid expansion. Location-Based Entertainment Market Location-Based Entertainment Market Dublin, April 17, 2026 (GLOBE NEWSWIRE) -- The "Location-Based Entertainment Market Report 2026" has been added to Res
NSWCPD Applies AI and Machine Learning to Predictive Machinery Health
In a soundproof chamber at the Naval Surface Warfare Center, Philadelphia Division (NSWCPD), a steel-gray air compressor hums as engineers test an experimental machine learning model designed to detect early signs of failure through vibration analysis. The effort, part of NSWCPD’s growing portfolio of artificial intelligence (AI) and machine learning (ML) projects, shows early promise for potential future Navy use.
The return of power politics to the market: theory and practice of the geoeconomic zeitenwende
Descriptions, explanations, and recommendations regarding foreign policy as well as foreign trade policy increasingly refer to the concept of geoeconomics. In fact, the use of economic and technological measures in foreign policy practice is becoming more frequent and intensive, especially in those countries that have the necessary resources of power at their disposal, such as […]
Analysis | How Trump vs. Pope Leo could impact elections
The Washington Post’s essential guide to power and influence in D.C.
Roman Space Telescope Science Platform Will Open New Frontiers in Space Science
Preparations for NASA's soon-to-launch Nancy Grace Roman Space Telescope have already introduced historic changes to the field of astronomy. Starting in 2027, Roman will deliver an unprecedented volume of complex survey data that will be impractical to download to individual computers for analysis. Astronomers and engineers at the Space Telescope Science Institute (STScI), working in close collaboration with the mission’s partners at NASA and Caltech/IPAC, have met these new developments head
Can we trust the science shaping our lives?
Improved methods for social and behavioral sciences research could help enhance public trust in science, says a new study that investigated the robustness of data analysis to understand whether it reliably ...
Pragmata Nintendo Switch 2 tech analysis, including frame rate and resolution
Lots of technical details about Pragmata on Nintendo Switch 2, including frame rate, resolution, and more.
Scientists Opened Up A Martian Meteorite And Found Ink From A Violet Gel Pen Inside
While we will have to wait a long time for samples collected on Mars to be returned to Earth, we do have Martian rock sent to us the old-fashioned way – unfortunately, analysis reveals a few surprises that shouldn't be there.
Analysis | Trump tests loyalty of Christian supporters as erratic behavior escalates
The president maintains his hold on the Christian right, but his bluster, fight with the pope and portrayal of himself as a Jesus-like figure strain that bond.
Analysis of Alzheimer’s Drugs Stirs Debate About Their Effectiveness
The review said a certain class of drugs had little clinical benefit, but many Alzheimer’s experts criticized the analysis, saying it unfairly lumped failed drugs with two recently approved treatments.
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A few weeks after Donald Trump’s second presidential win, I took the train up from London (where I was living at the time) to Oxford to attend a conference on polls and forecasts of the 2024 election. Most of the attendees were pollsters or academics, but I also watched presentations from Aaru and Electric Twin, two companies that do what is interchangeably called synthetic sampling, silicon sampling, or synthetic audiences. Stripped of startup jargon, that means they use large language models (LLMs) to simulate responses to public opinion polls by having AI agents take on the role of survey respondents. I had already heard of Aaru thanks to some articles with eye-catching headlines like “No people, no problem: AI chatbots predict elections better than humans” in the months leading up to Election Day. The founders were making some big, some might even say far-fetched claims, such as: “within two years, we will simulate the entire globe — from the way crops are grown in Ukraine to how that impacts production of oil in Iraq, trade through the strait of Malacca, and elections for the mayor of Baltimore.” When Semafor asked Aaru’s cofounders — Cameron Fink and Ned Koh — about my boss, they said “we respect all those who came before us.” Nate (as he so often does) shared his thoughts on Twitter: Fink and Koh were relatively good-natured about this back-and-forth when we spoke at Oxford. They even offered to mail me one of the t-shirts featuring Nate’s quote they apparently had made. I never took them up on the offer, which I now somewhat regret. These synthetic sampling companies fell off my radar for a while, but they do still exist. In fact, Aaru recently received a $1 billion valuation. Is what they’re doing anywhere close to the most important frontier in AI development? Not by a longshot, especially when Anthropic just developed a model so adept at exploiting software vulnerabilities that it’s only being released to 40 companies. Still, silicon sampling is increasingly finding its way into public polling. Axios reported in March that “a majority of people trust their own doctors and nurses” based on findings from Aaru — without mentioning that the “people” in that sentence were actually LLMs. Around the same time, the Public Sentiment Institute “boosted” their online sample of 373 real survey respondents with 114 AI agents.1 (Spoiler alert: even the co-founder of Electric Twin doesn’t think that’s a particularly defensible approach.) Polling companies like Qualtrics and Ipsos are also developing synthetic data panels. So, what should we make of these … “polls”? Let’s get one thing out of the way: whatever they are, they’re not polls in the way that term is usually defined. Subscribe You can’t replace polls with AI On one hand, using LLMs to essentially make up fake survey respondents sort of sounds like the dumbest idea ever, one that will at best imperfectly replicate real polls while introducing all sorts of biases. On the other hand, with LLMs improving at a remarkable, perhaps even alarming rate, maybe that means I’m a dinosaur at the ripe old age of 24 because I still want to rely on polls that talk to actual people. I’m not going to argue that synthetic samples are completely useless. In fact, as I’ll return to later, there is evidence that some techniques can replicate topline survey results quickly and cheaply. But the marketing from certain companies can be slightly optimistic. “No traditional poll will exist by the time the next general election occurs,” said Fink in 2024. We’re just 206 days away from the midterms, and based on the fact that I still have to collect a bunch of polls every day, I’d say he should have run that prediction by a sample of AI agents before the interview.2 To see why synthetic samples can’t replace polls, here’s a quick primer on how they work. The simplest version of these models involves taking a LLM (like ChatGPT or Claude), giving it a demographic profile (e.g., a white, college-educated woman who lives in Utah and makes $70k a year), and then asking it to respond to a survey question. You repeat that process a few thousand times using different demographic profiles and end up with a sample of synthetic survey responses. The actual models used by private companies are more sophisticated than this, usually because they incorporate more hypothesized demographic characteristics for each agent and provide them with extra information. Aaru, for example, feeds agents a diet of news and information they’d be likely to consume, while Electric Twin incorporates their customers’ proprietary data about the audience they’re trying to replicate. The way Ben Warner, the co-founder of Electric Twin, explained it to me was “we have a large amount of data on […] for instance, 5,000 people. Can we make an accurate prediction of how they would respond to another question?” Still, it should be obvious why synthetic samples can’t replace polls. Polling is fundamentally a data collection process. We might use surveys to make predictions by feeding them into election forecasts, but the main purpose of a poll isn’t prediction, it’s gathering new data about what people think and how they feel. Silicon sampling, on the other hand, produces no new data. It’s simply a model: you input LLM training data, demographic prompts, and a bunch of other information, and it spits out a prediction for what a poll would say. We love models here, but models aren’t polls. That difference is an important philosophical sticking point for most pollsters I talk to. “I think politics should stay away from [synthetic sampling], because we’re trying to […] represent the voice of the people,” said Natalie Jackson, a vice president at GQR Insights. Democratic pollster John Hagner told me: “I think I’m just incredibly skeptical of this idea. I don’t think it’s research. At that point, you’re asking the machine to tell you what you already believe.” Hagner has seen some presentations of early synthetic sampling experiments, but so far, “if it’s being used in a campaign, people are keeping it incredibly quiet.”3 But Eli, I hear you saying, aren’t polls themselves increasingly governed by modeling decisions? Indeed they are: pollsters’ choices on which sampling method to use, how to define their likely voter models, and how to weight their samples can and do lead to dramatic differences in the results they publish. Aaru even referenced these limitations in the methodology statement included with that maternal mortality “poll” — although I’m using the term “methodology statement” loosely here, because it doesn’t really explain how the model works at all. We can ignore the (frankly preposterous) implication that synthetic sampling isn’t subject to a separate set of biases. The important point is that there’s still a meaningful difference between using weighting and other statistical techniques on actual polling data and using a model to predict what a poll would say. The latter is far closer to election forecasts or techniques like MRP — potentially useful models, but not a replacement for polls.4 To be fair, other synthetic sampling companies are perfectly happy with the distinction between polls and models. Warner compared polling and synthetic sampling to different tools in a toolbox. “The mistake I think we make is we think that these new tools should either work in exactly the same way or somehow replace these old tools,” he said. “Rather than thinking of it as, okay, so we’ve always had the hammer, we’ve always had the screwdriver, now we’ve got a saw. But don’t use a saw to try [to] do the job of a hammer.” A quick comment from Nate Eli didn’t ask me for a comment — rather rude of him, don’t you think? But since I’m editing this story, I figured I’d add a few quick thoughts rather than putting words in his mouth. Beyond the frequently misleading marketing, what bothers me about the AI “poll” hype is that as AI tools make statistical inference cheaper and/or better (note that these are not synonyms) that actually increases the comparative value of collecting original data. You might be able to train a model to make a reasonable estimate of what some hard-to-reach poll respondent would say — say, a young Black man who voted for Trump. (Such a person checks a number of boxes for a voter who is usually hard to reach in surveys.) Indeed, this is closely related to what models like the Silver Bulletin forecast already do. They essentially smooth out the kinks in noisy survey data by making inferences based on past voting patterns or national polls or surveys of other states. But you don’t actually know what these voters think unless you’re reaching them directly. If there’s a shift in opinion among this subgroup, you’re not going to detect it. So if I were running a campaign, I’d invest more in going the extra mile to find a representative sample of those voters. And then I’d hire some smart quants — or Claude? — to figure out the implications for campaign strategy based on proprietary data that my competitors didn’t have access to. -Nate Silver Are these models any good? If synthetic surveys are just a new type of model, the next obvious question is whether the models are at least accurate. The answer very much depends on who you ask. On one end of the spectrum, you have the maximalist argument that synthetic sampling is more accurate than actual polls. “It’s an incredibly challenging problem to go to someone and say ‘hey, we’re going to be more accurate at predicting human behavior than you, even when you talk to your customers directly’,” Koh recently told CNBC. In his view, synthetic sampling isn’t a saw to polling’s hammer, it’s “magic.” There’s certainly evidence that synthetic samples can replicate certain survey toplines. But if Aaru does have any examples of their approach outperforming the polls, they’re keeping those to themselves.5 Aaru’s 2024 election model, for example, had Kamala Harris leading in Michigan, Nevada, Pennsylvania, and Wisconsin on November 4th. And although they’ve since taken down their forecast page, they gave Harris a 50.5 percent chance of winning the race on November 2nd.6 After the election, Fink told Semafor he was happy enough with those results because they were “within margin of error,” a term that is completely meaningless when applied to a “sample” of AI agents. And of course, Aaru says their models have improved since 2024, so supposedly now they’d be more accurate than the polls? Still, their stronger argument is on cost: “We are significantly faster and cheaper than traditional polling, and still more accurate,” said Fink. The first two claims are undeniably true, but the third brings us to the opposite end of the spectrum. Both Jackson and Hagner are skeptical that these models are reliable for anything beyond replicating common survey toplines. “I just […] don’t think the machines are what we want when we’re looking for nuanced views. My example on this is people in Arizona and Nevada in 2024 who voted for Trump and voted for expanding abortion in their states on ballot initiatives,” said Jackson. Hagner identified another issue. Maybe the synthetic respondents, like sycophantic LLMs, are inhuman in one important way: they’re too nice. “The reports that have come through at the meetings that I’ve been at are that the early experiments on this, they cannot get respondents to be as racist or sexist or, frankly, as negative as human respondents,” he said. Academic research mostly agrees on this point. While there are some papers that show promising results when using LLMs to replicate polling data, most show that LLMs suffer from various quirks like producing too few “don’t know” responses and can seriously overpredict the favorability of politicians like Donald Trump and Kamala Harris. They also seem to struggle with too little variation between demographic subgroups, so the difference in predicted opinion between Democrats and Republicans, for example, is too small. When I asked Warner about these studies, his response to these papers was that just because academics can’t get synthetic sampling to work doesn’t mean that the technique doesn’t work in general. “Actually, the argument is, okay, yours does not [work]. That does not mean […] for this complex set of machinery, which uses a lot of investment, a lot of time, a lot of money, you can’t get it to work.” Cards on the table, I’m somewhat sympathetic to this argument because academics aren’t exactly great at making election forecasts. Usually, the people with skin in the game are the most accurate. Warner’s argument is that the approach Electric Twin takes — which includes, for example, making multiple predictions for each synthetic respondent using different models and prompts and subsequently averaging those to get a final prediction in a sort of ensemble forecast — produces better results than the simpler academic models. Warner shared a comparison between his method and the method from a recent academic paper with me, and Electric Twin was indeed able to get more accurate replication. But even still, he acknowledged that synthetic sampling “is not a crystal ball.” “If you asked me, do I think using other data sources will be more accurate than asking somebody who they will vote for, I would probably say no. But if you asked me ‘would your system be useful for our turnout modeling today?’ I would say yes.” For better or worse, it looks like the method is already getting more popular in the market research world. Most of the clients Aaru touts these days are businesses like EY and McDonald’s. And AI will probably begin to pop up in other parts of the political polling process. Pollsters are already using it to code open-ended survey responses, and some firms, like YouGov, are testing using LLMs to ask survey respondents questions. More worryingly, one danger to actual polls is that AI agents can be used to infiltrate online surveys. Most online polls use various checks to prevent that from happening, but there’s conflicting evidence on how effective those filters are and how prevalent AI agents currently are in online panels. If those agents ever become impossible to detect, it might spell the end of online polling, but the solution isn’t to replace all of your respondents with ChatGPT. Silver Bulletin is a reader-supported publication. To receive new posts and support our work, consider becoming a subscriber. Subscribe 1 That particular poll obviously doesn’t meet Silver Bulletin standards for aggregation. But we exclude all Public Sentiment Institute polls from our averages because we classify them as an amateur polling firm. 2 You could argue that Fink meant the next presidential election, but (a) I’m also confident we’ll still have real polls in 2028 and (b) in that case he should have asked an LLM to define “general election.” 3 Quick caveat: that’s reporting from a Democratic pollster. It’s possible that Republicans are more willing to use AI in political campaigns. 4 Indeed, Silver Bulletin does not include “polls” produced by MRP in our forecasts or averages, and we think it’s extremely misleading when their practitioners describe them in a way that suggests original data had been collected among a large number of states or Congressional districts. 5 A recent report from Aaru and EY did show two examples of a synthetic estimate being closer than a survey to a real-world benchmark — but I’d take those findings with a grain of salt because the report reads more like an ad and didn’t involve any sort of prediction being made ahead of time. 6 For comparison, our odds for Harris on the same day were 48.2 percent.
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