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Are Leeds absolutely safe? What history tells us
Officially, there is still work for Leeds to do to seal their Premier League status for another season. After dispatching Burnley with ease on Friday, the Whites are nine points and four places above 18th-placed Tottenham, who occupy the third and final relegation spot. It is worth pointing out that four of the teams directly below Leeds - Newcastle, Nottingham Forest, West Ham and Spurs - all have a game in hand on Daniel Farke's side.
Player status report, presented by Orlando Health: Orlando City SC at Inter Miami CF
Here is the Player Status Report, presented by Orlando Health, for Saturday's away match at Inter Miami CF
Crues retain Premiership status with shootout win over Annagh
Crusaders secured their Irish Premiership status for next season after a dramatic penalty shootout victory which sealed the play-off victory over Annagh United.
Business Lookahead: Eyeing oil, US jobs, and European earnings
STORY: From high oil prices and the conflict in the Middle East to U.S. jobs data and corporate earnings, here’s what you need to watch in business and finance in the week ahead.:: Crude and currencyOil prices briefly topped $120 a barrel this week to hit their highest level since 2022 as the war with Iran enters a third month.While the U.S. and Iran face pressure to end a conflict that has shut the Strait of Hormuz, the world watches anxiously as the biggest-ever disruption to energy supplies unfolds.For each week the Strait is closed, keeping oil elevated, the greater the economic risks via higher inflation or weak growth or, for some, both. Oil importer Japan just intervened to prop up a yen that has been weakened by the conflict.A new month is now underway and some traders will be mindful of that old adage, "Sell in May and go away.":: Jobs gyrationsAs the U.S. economy grapples with fallout from the Middle East war, Wall Street's radar turns to Friday's April monthly payrolls report.The U.S. economy likely created 73,000 new jobs, economists polled by Reuters forecast. In March, payrolls increased by 178,000, the most since December 2024, but that followed a sharp decline in February.The U.S. employment data comes amid signs of hawkishness at the Federal Reserve, as Donald Trump pick Kevin Warsh prepares to take over as chair with the U.S. president keen on rate cuts.:: Starmer’s statusThursday's local elections in Britain, usually a non-event for investors, could move markets in a big way, with opinion polls pointing to a heavy defeat for Prime Minister Keir Starmer's Labour Party.A heavy defeat could spark more widespread demands for his dismissal among his own lawmakers and stoke expectations of a successor more willing to run looser budgets. That would bring more bad news for British bonds.::European earningsIt's a big week for European earnings with Shell and Commerzbank among those reporting.On aggregate, profits are expected to grow 3.2% in Q1, according to LSEG I/B/E/S. Under the surface, it's a little bit more complicated. Growth is expected to be driven by just three sectors: financials, tech and energy. The latter is seen as the biggest beneficiary of the Iran war due to higher oil and gas prices.But if the war, and energy surge, persist, the overall outlook for Europe's earnings could turn.
Player Availability Report: #SKCvSEA
Player Availability Report is SportingKC.com’s look at the latest status updates around the team ahead of upcoming matches and is presented by Saint Luke’s. All details listed are from the league’s official Player Status Report that is submitted the day prior to the match. Sporting Kansas City returns home this
Commitment to Physical Fitness Leads Alumna to College of Public Health
Jennifer Wessel J.D., MPH, works to improve health outcomes, and her love for health and wellness paved the way for her to become a public health professional. “We tackle a multitude of issues to have a broader lens on ways to improve Arkansas’ health status. Therefore, I’m learning something new…
Sony clarifies recent PlayStation DRM update
PlayStation fans and gaming preservations have been alarmed since late last week that a new 30-day timer attached attached to newly-purchased digital games for PlayStation 4 and 5 might render those games unplayable if the system they’re on is offline for longer than a month. But a rep from Sony told Game File today that new system will require only a single online check before it functions as a perpetual license for the digitally purchased game. That is consistent with a newer theory that emerged by gamers testing the 30-day timer over the last two days. “Players can continue to access and play their purchased games as usual,” a rep for PlayStation told me over email. “A one-time online check is required after purchase to confirm the game’s license, after which no further check-ins are needed.” The rep’s explanation squares with the current understanding among players about what’s happening. A multi-day mystery A post last Friday by YouTuber Lance MacDonald spread awareness over the 30-day timer. Quickly, players began stress-testing the system, removing a battery within their PlayStations and checking what would happen if their systems were offline past the timer window. They noticed that setting a PS4 or PS5 to be the “primary” console—a common Sony-authorized method to retain rights to a digital game—wasn’t overriding the 30-day limit. On Tuesday came the breakthrough: A gamer called Andshrew on the Resetera forums posted the results of some tasting. They found that digital games purchased on PS4/PS5 after some time in mid-April would get a 30-day timer that could then be removed and replaced with a perpetual license that would allow the game to be played offline. The transition to the perpetual license occurred some number of days after the digital game was purchased and the system was connected to the internet. They believed that a PlayStation’s online check-in would trigger the license change no sooner than 15 days after the user had purchased the game. This synced with the theory that Sony’s new system is related to the 14-day window that PlayStation users have to request a refund for digitally purchased games. The new timer/check-in system could be a way to defeat some exploit in that refund system, some users theorized. Game File is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber. Subscribe In a follow-up, I asked the Sony rep if the 15-day timeline is accurate or if the perpetual license can be activated sooner after purchase. If they share more, I’ll update this post. Sony has not said why they’ve introduced the timer and whether it is designed to stop people from exploiting the refund system. But their explanation suggests that this new DRM method should not result in long-term loss of access to digitally purchased games, just because a PlayStation is offline for a month or Sony’s servers are down. Xbox flashback For many some gamers, the initial reporting of the 30-day timer conjured memories of Microsoft’s disastrous May 2013 announcement of the Xbox One, which was going to require an internet-connected check-in once a day, lest your games become unplayable.1 After widespread backlash, Microsoft abandoned that plan, ahead of the Xbox One’s launch. 1 Fun fact: That 24-hour check-in detail was my scoop from an interview I had that day with then-Xbox exec Phil Harrison. I was EiC of Kotaku at the time and rushing from one Xbox One preview appointment on Microsoft’s campus to another. I phoned the news in to reporter Jason Schreier, who wrote it up for the site.
Supreme Court leans in favor of Trump's bid to end protections for Syrian, Haitian migrants
Trump's lawyers say Congress gave the Department of Homeland Security, not judges, the power to end Temporary Protective Status granted earlier.
Georgia ranks 48th for Hispanic health care, driven by high uninsured rates
40% are uninsured, and immigration status locks many out of safety net programs.
Windows K2 status tracker: Keeping tabs on every Windows 11 commitment Microsoft has made in 2026
Microsoft has promised to fix Windows 11's biggest flaws, but actions speak louder than words. So, let's track its progress.
Supreme Court hears arguments over temporary protected status for Haitian and Syrian migrants
The court’s decision could affect hundreds of thousands of people who benefit from Temporary Protected Status.
Broncos Fans Worried About Bo Nix's Status For 2026 Season
We're still several months away from the start of the 2026 season, but Denver Broncos fans are already panicking about Bo Nix's status for Week 1. Nix finished his second season in Denver with 3,931 passing yards, 25 touchdowns and 11 interceptions. Although he was inconsistent at times, he saved ...
Australia becomes the 30th country to eliminate trachoma as a public health problem
The World Health Organization (WHO) has validated Australia for eliminating trachoma as a public health problem, marking a significant milestone in the health of indigenous peoples and in global efforts to combat neglected tropical diseases (NTDs). Trachoma, the world’s leading infectious cause of blindness, no longer represents a public health problem in the country.Australia is among a growing number of countries that have successfully eliminated trachoma, contributing to global progress towards the targets set out in the WHO road map for NTDs 2021–2030.Trachoma is caused by the bacterium Chlamydia trachomatis and spreads through close contact with infected individuals, contaminated surfaces, and flies that carry eye and nose discharge. Repeated infections can lead to scarring of the eyelids, turning eyelashes inward, and ultimately causing blindness if untreated.“WHO congratulates Australia on this important achievement,” said Dr Tedros Adhanom Ghebreyesus, WHO Director-General. “This success reflects sustained commitment, strong partnerships, and a focus on reaching populations most affected by health inequities. It brings us closer to a world free from the suffering caused by trachoma.”Australia’s journey to eliminationAustralia’s achievement reflects decades of targeted public health action, particularly in remote Aboriginal and Torres Strait Islander communities, where trachoma persisted despite its earlier disappearance from the rest of the country.National efforts intensified with the establishment of the National Trachoma Management Programme in 2006, which implemented the WHO-recommended SAFE strategy: surgery for trichiasis, antibiotics to treat infection, promotion of facial cleanliness, and environmental improvement. Regular screening of all communities classified as at-risk of trachoma by teams of qualified health workers formed an important part of the Programme. Interventions were delivered through coordinated partnerships between federal and state governments, Aboriginal community-controlled health services, and local communities.Over time, sustained screening, treatment, and prevention activities, including improvements in housing, water, sanitation and hygiene, led to a steady decline in trachoma prevalence. Australia’s approach included adaptations to reflect its context, such as targeted treatment based on community-level data rather than mass drug administration, and strong integration with environmental health programmes.“Elimination of trachoma is a win for the eye health of communities across Australia, particularly those whose lives have been impacted by a disease that is entirely preventable,” said Mark Butler, Minister for Health and Ageing, Australia. “This major milestone is thanks to Aboriginal and Torres Strait Islander leadership, community commitment and sustained investment over many decades.“The lessons from this work will inform how we approach other preventable health conditions in remote and regional Australia. Aboriginal Community Controlled Health Organisations and local health workers have been central to this success, delivering culturally safe care and community-led solutions.”“This recognition from the World Health Organization reflects decades of work led by Aboriginal Community Controlled Health Organisations, alongside local health workers in remote First Nations communities,” said Malarndirri McCarthy, Minister for Indigenous Australians. “Their work has been critical to eliminating trachoma as a public health problem in Australia.”Advancing global efforts against neglected tropical diseases (NTDs)Trachoma is one of 21 diseases and disease groups that are regarded by WHO as NTDs. Together, NTDs affect more than 1 billion people worldwide, primarily in underserved populations with limited access to essential services such as clean water, sanitation, and health care.Australia’s elimination of trachoma as a public health problem highlights the importance of sustained political commitment and cross-sectoral collaboration in addressing the underlying determinants of health. It also underscores the feasibility of eliminating trachoma even in geographically challenging settings.In addition to trachoma, Australia has several endemic NTDs, including Buruli ulcer, leprosy and scabies. Validation of elimination of trachoma as a public health problem marks the first time that WHO has confirmed the elimination of an NTD in Australia, which becomes the 63rd country globally and 16th in the Western Pacific Region to have eliminated at least one NTD.“Tackling neglected tropical diseases in the Western Pacific Region has long been a challenge for countries across the socioeconomic spectrum, given the complexities in reaching the most vulnerable communities, including in remote areas,” said Dr Saia Ma’u Piukala, WHO Regional Director for the Western Pacific. “As a doctor from Tonga, I’ve experienced these challenges for myself. But I also know that with strategic commitment underpinned by optimal resources and partnerships in health, success is possible as other countries in our region have also demonstrated. I commend Australia on eliminating trachoma as a public health problem and urge all involved to remain vigilant to ensure this status is maintained.”WHO continues to support countries working to eliminate trachoma and other NTDs, ensuring that progress reaches those most in need and that gains are sustained through strong surveillance, appropriately integrated into national health systems, and mainstreamed within the wider health sector and beyond.Editor’s notesNeglected tropical diseases and trachoma elimination effortsNeglected tropical diseases are associated with devastating health, social and economic consequences. Their burden is mainly felt among impoverished communities in tropical areas.Public health targets for the control, elimination and eradication of these conditions were set in the road map for neglected tropical diseases 2021–2030 (https://www.who.int/publications/i/item/9789240010352).In 1996, WHO launched the WHO Alliance for the Global Elimination of Trachoma by 2020 (GET2020), creating a network of governments, non-governmental organizations and academic institutions dedicated to the fight against trachoma. WHO continues to support endemic countries to accelerate progress towards the global target of eliminating trachoma as a public health problem worldwide; 2030 is the new target date.Elimination of trachoma as a public health problem is defined as: (i) a prevalence of trachomatous trichiasis (TT) “unknown to the health system” of < 0.2% in ≥15-year-olds; and (ii) a prevalence of trachomatous inflammation—follicular (TF) in children aged 1–9 years of < 5%, in each formerly endemic district, plus (iii) the existence of a system to identify and manage incident cases of TT.Other countries validated by WHO as having eliminated trachoma as a public health problem are: Algeria, Benin, Burundi, Cambodia, China, Egypt, Fiji, Gambia, Ghana, India, Iraq, Islamic Republic of Iran, Lao People’s Democratic Republic, Libya, Malawi, Mali, Mauritania, Mexico, Morocco, Myanmar, Nepal, Oman, Pakistan, Papua New Guinea, Saudi Arabia, Senegal, Togo, Vanuatu and Viet Nam.
UAE Employment and Social Reforms 2026: Modernization or Business as Usual?
A flurry of employment law reforms in the United Arab Emirates—a business-friendly area that remains firmly rooted in traditional values and national identity—in recent years has caught the attention of multinational employers and expatriates alike, but do these changes represent a genuine shift toward Western-style liberalization, or are they pragmatic adjustments designed to maintain competitiveness while preserving the status quo? Below are some of the key developments and what they mean for employers operating in the region.
EUDA Health Holdings Limited Receives Nasdaq MVLS Notice with 180-Day Compliance Period to Regain Listing Status
EUDA Health Holdings received a Nasdaq notice for not meeting market value requirements, with a compliance period until October 2026.Quiver AI SummaryEUDA Health Holdings Limited received a notice from Nasdaq on April 23, 2026, indicating that it failed to maintain a Minimum Market Value of Listed Securities of $35 million for 32 consecutive business days, violating Nasdaq Listing Rule 5550(b)(2). The notice does not immediately affect the compan
Correspondents’ dinner lacked highest security level despite presence of top officials
The White House Correspondents’ Dinner, which was attended by the President and many Cabinet members, was not given top security status that would have unlocked the full weight of federal security resources.
Post-Pelosi, status quo out, candidate says
Former boss Alexandra Ocasio-Cortez hasn't endorsed.
Should Flutter’s Shift to U.S.-Style Governance and Blank-Check Preferred Shares Require Action From Flutter Entertainment (FLUT) Investors?
At its 2026 Annual General Meeting on May 29, held in the past relative to today, Flutter Entertainment plc approved amendments to its Memorandum and Articles of Association to align governance with common U.S. public company practices, including plurality voting in contested director elections, flexible board size, and the ability to issue blank-check preferred shares. An important implication is Flutter’s move to formalize its status as a U.S. domestic issuer under the Securities Exchange...
14 Products Apple Is Saying Goodbye To In 2026
Apple trimmed its lineup again in 2026, cutting older iPhones, AirTags, and Macs. See what changed, support status, and what buyers should keep in mind.
Player status report, presented by Orlando Health: Orlando City SC at D.C. United
Here is the Player Status Report, presented by Orlando Health, for Saturday's away match at D.C. United
Rediscovered after 100 years: scientists reveal status of the critically endangered Osmanthus pubipedicellatus
Integrative morphological and molecular evidence confirms the rediscovery of a long-lost Osmanthus species, revealing its declining population and urgent conservation needs.
Player Availability Report: #CHIvSKC
Player Availability Report is SportingKC.com’s look at the latest status updates around the team ahead of upcoming matches and is presented by Saint Luke’s. All details listed are from the league’s official Player Status Report that is submitted the day prior to the match. Sporting Kansas City concludes the club’s
CBS Sports weighs in on Paul McNeil Jrs status Real chance of staying at NC State
Paul McNeil Jr. remains in the transfer portal at the end of another week, with NC State men's basketball and the fan base both waiting on an official announcement. CBS Sports college basketball analyst Isaac Trotter weighed in with the latest.
Marijuana's reclassification raises new questions for the cannabis industry
Medical marijuana is moving from Schedule I status, reserved for the most dangerous drugs like heroin and LSD, to Schedule III, like testosterone and steroids, which are less strictly regulated.
Status symbols men are obsessed with in 2026
Status symbols for men in 2026 are all about looking sharp and evoking quiet luxury. Leather bags and tailored designer suits are just two examples.
Wembanyama's status uncertain for Spurs vs. Blazers in Game 3
Wembanyama's status uncertain for Spurs vs. Blazers in Game 3
Measles exposure alert for Ellensburg school as Kittitas County hits outbreak status
Health officials in central Washington are responding to potential measles exposures at Valley View Elementary School in Ellensburg as the county enters outbrea
Victor Wembanyama cleared in concussion protocol to travel for Spurs' Game 3 against Trail Blazers; playing status uncertain
Republicans pressure Ron DeSantis to redistrict in Florida after Virginia Democrats’ win
Senior Republicans in Washington are ramping up the pressure on Florida Gov. Ron DeSantis to lead a redrawing of his state’s US House map after Virginia Democrats triumphed in potentially flipping four seats in their favor. A special session to consider redistricting in Florida is slated to start Tuesday, but no map has been publicly released. A DeSantis spokesperson did not respond to a CNN inquiry about its status. Key Republicans involved in redistricting say they’ve been kept largely in the dark on DeSantis’ plans. There’s no coordination on the state level because of strict state rules around partisan gerrymandering, and no maps have been officially circulated within Florida’s congressional delegation either.
The Symbolic Politics of Status in the MAGA Movement -
The Symbolic Politics of Status in the MAGA Movement By Biko Koenig, Franklin & Marshall College and Tali Mendelberg, Princeton University Drawing on ethnographic fieldwork among Make America Great Again (MAGA) activists during the 2020 [...]
Gamers sue Nintendo over tariff refunds, saying consumers should get the money back
Two gamers have filed a class action lawsuit against Nintendo, alleging that the company will be unjustly enriching itself with any refund it secures from the U.S. government over widespread tariffs last year that, among other things, hiked the prices of Nintendo hardware and accessories. “Unless restrained by this Court, Nintendo stands to recover the same tariff payments twice—once from consumers through higher prices and again from the federal government through tariff refunds, including interest paid by the government on those funds,” the suit states. Nintendo sued the U.S. government to secure a tariff refund in March, after the Supreme Court struck down the tariffs a month prior, saying they were illegally implemented by President Donald Trump.. The gamers who have sued, California-based Gregory Hoffert and Washington-based Prashant Sharan, both say they purchased Nintendo goods that had increased in price due to tariffs, according to the complaint. They filed their suit in the Western District court of Nintendo of America’s home state of Washington and are seeking class action status to represent all people in the U.S. who purchased price-hiked Nintendo goods between February 1, 2025 and February 24, 2026. They allege that Nintendo’s recovery of any tariff refunds would constitute unjust enrichment and violate Washington state consumer protection law. Similar class action lawsuits pressing companies to pass on tariff refunds have been previously filed against FedEx, UPS and eyeglass importer EssilorLuxottica. The tariffs were announced in early April, and by mid-month, Nintendo had announced $5 price increases for controllers for the then-forthcoming Switch 2. In August, it raised the price of the original Switch. In their suit, the gamers cite comments from Nintendo executives connecting the tariffs to price increases. In May 2025, a month after the tariffs were imposed, Nintendo CEO Shuntaro Furukawa told investors “Our basic policy is that for any country or region, if tariffs are imposed, we recognize them as a part of the cost and incorporate them into the price.” Nintendo’s March lawsuit, along with tariff-recovery suits from hundreds of other companies was immediately put on hold pending the implementation of a refund system. The U.S. government announced the beginning of the refund process earlier this week. Companies could receive as much as $160 billion, per CNBC. In March 2026, after Nintendo filed its lawsuit to recover the cost of the tariffs, I asked the company if they planned to pass their refund on to customers who’d paid increased prices. The company’s response acknowledged the existence of the lawsuit but avoided answering that question: “We can confirm that we filed a request. We have nothing else to share on this topic.” Even a promise to consumers may not have spared Nintendo this week’s lawsuit. FedEx previously promised to pass its tariff refunds on to consumers. They’ve been sued over them anyway.
Player status report, presented by Orlando Health: Orlando City SC vs Charlotte FC
Here is the Player Status Report, presented by Orlando Health, for Wednesday's home match vs Charlotte FC
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
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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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Gemma 4 and what makes an open model succeed
Having written a lot of model release blog posts, there’s something much harder about reviewing open models when they drop relative to closed models, especially in 2026. In recent years, there were so few open models, so when Llama 3 was released most people were still doing research on Llama 2 and super happy to get an update. When Qwen 3 was released, the Llama 4 fiasco had just gone down, and a whole research community was emerging to study RL on Qwen 2.5 — it was a no brainer to upgrade. Today, when an open model releases, it’s competing with Qwen 3.5, Kimi K2.5, GLM 5, MiniMax M2.5, GPT-OSS, Arcee Large, Nemotron 3, Olmo 3, and others. The space is populated, but still feels full of hidden opportunity. The potential of open models feels like a dark matter, a potential we know is huge, but few clear recipes and examples for how to unlock it are out there. 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Of course, we can’t test some things like search abilities without some tool, but being able to measure exactly the pace of progress of the model alone is a welcome simplification to a systematically opaque AI space. Share The list of factors I’d use to assess a new open-weight model I’m considering investing in includes: Model performance (and size) — how this model performs on benchmarks I care about and how it compares to other models of a similar size. Country of origin — some businesses care deeply about provenance, and if a model was built in China or not. Model license — if a model needs legal approval for use, uptake will be slower at mid-sized and large companies. Tooling at release — many models release with half-broken, or at least substantially slower, implementations in popular software like vLLM, Transformers, SGLANG, etc due to pushing the envelope of architectures or tools. Model fine-tunability — how easy or hard it is to modify the given model to your use-case when you actually try and use it. The core problem is that some of these are immediately available at release, e.g. general performance, license, origin, etc. but others such as tooling take day(s) to week(s) to stabilize, and others are open research questions — with no group systematically monitoring fine-tunability. In the early era of open models, the days of Llama 2 or 3 and Qwen pre v3.5, the architectures were fairly simple and the models tended to work out of the box. Some of this was due to the extremely hard work of the Llama, Qwen, Mistral, etc. developer teams. Some is due to the new models being genuinely harder to work with. When it comes to something like Qwen 3.5 or Nemotron 3, with hybrid models (either gated delta net or mamba layers), the tooling is very rough at release. Things you would expect to “just work” often don’t. I’ve been following this area closely since we released Olmo Hybrid with a similar architecture, and Qwen 3.5 is just starting to work well in the various open-source tools that need to all play nice together for RL research. That’s 1.5 months after the release date! This is just to start really investing more into understanding the behavior of the models. Of course, others started working on these models sooner by investing more engineering resources or relying on partially closed software. The fully open and distributed ecosystem takes a long time to get going on some new models. All of this is lead-in for the most important question for open models — how easy is it to adapt to specific use-cases? This is a different problem for different model sizes. Large MoE open-weight models may be used by entities like Cursor who need complex capabilities in their domain, e.g. Composer 2 trained on Kimi K2.5. Other applications can be built on much smaller models, such as Chroma’s Context-1 model for agentic search, built on GPT-OSS 20B. The question of “which models are fine-tunable” is largely background knowledge known by engineers across the industry. There should be a thriving research area here to support the open ecosystem model. The first step is to understand characteristics of different base and post-trained models to understand what they look like. The second step is to tune pretraining recipes for open models so they’re more flexible. Interconnects AI is a reader-supported publication. Consider becoming a subscriber. Subscribe For The ATOM Project and other Interconnects endeavors, we’ve put in substantial effort to measuring adoption trends in the open ecosystem. Everything takes a long time to unfold after a model is first publicly available — and adaptability is why. What we know for sure now, when Qwen has been going from strength to strength with its releases, is that technical staff across the industry has gotten comfortable working with Qwen models. Countless research methods and datasets were made to work with Qwen. It’ll take patience for any other model family to get to this point — a patience I’m not sure many open model builders have. This takes us to Gemma 4, Google’s latest open models. Gemma 3 was released more than a year ago, in March of 2025, and is a bit underrated. Gemma 4 comes in 4 sizes for now, with a bigger, MoE model of over 100B total parameters rumored but not released yet. The models we have today come in sizes of ~5B dense, 8B dense, 26B total 4B active MoE, and 31B dense. I’m most excited that they’re finally adopting a standard Apache 2.0 open source license. This’ll massively boost adoption. The standard of better licenses for strong open-weight LLMs was set by mostly Chinese open model labs in the last 1-2 years, and now U.S. companies are following suit. I will personally be so happy if the horrible Llama licenses and Gemma terms of service were an ~18-month transient dynamic of the industry being nervous about releasing strong open models. The Gemma 4 scores look very solid, the small models have incredible benchmark scores (especially in general domains like LMArena) and the 31B model rivals the recent Qwen 3.5 27B, which is the leading member of that class. The ~30B size range is an important one, as it’s accessible both to researchers and to enterprises looking to deploy the model in real use-cases. Where the 7B model scale is the default for tinkering and research, a 30B model is the default for seeing if an open model can unlock substantial value in your specific workflow — a good mix of intelligence, low price, tractability for downstream training, etc. This takes us back to the above adoption criteria I mentioned for open models and the bigger question — do I think Gemma 4 will be an overwhelming success? Previous Gemma models have been plagued by tooling issues and poorer performance when being finetuned. Gemma 4’s success is going to be entirely determined by ease of use, to a point where a 5-10% swing on benchmarks wouldn’t matter at all. It’s strong enough, small enough, with the right license, and from the U.S., so many companies are going to slot it in. I’m cautiously optimistic that Gemma 4 is going to work better here. Winds are shifting for open models built in America. We saw GPT-OSS go through a bumpy launch to become an overwhelming success. There’s a collective energy around the likes of Reflection, Arcee, Nemotron, Gemma, Olmo, and peers that show substantial demand for building new stacks around open models. There’s capital to be spent on AI stacks across the economy by those who want more ownership of everything, including the model. After launching The ATOM Project 240 days ago, the conversation is shifting into the next stage. Summer of 2025 was a crisis moment where the U.S. AI scene realized it can’t wait and figure out open models after building AGI. The two markets will capture different areas and proceed in parallel. Now that more companies in the U.S. are releasing strong models, we need to improve the ecosystem so that these models are easy to use, understand, and build value around. It’s the hard work to build another inflection point in these adoption plots I’ve been updating consistently, but that’s the work to be done. Join me in it. More data coming soon! Here’s a sneak peek:
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