Latest news with #Trump-voting
Indianapolis Star
23-07-2025
- Health
- Indianapolis Star
An Indiana hospital cut medical services. A new DNC billboard blames President Trump
A new billboard on the southeast side of Columbus paid for by the Democratic National Committee blames President Donald Trump for recent medical service cuts at Columbus Regional Health and is part of a multi-state campaign to show Trump-voting communities what the party views as negative effects to rural health care in the 'One Big Beautiful Bill.' The Indiana billboard, which was installed July 22, is one of four billboards the DNC unveiled addressing hospitals that are closing or cutting medical services across the country. In addition to Indiana, the DNC launched billboards in Missouri, Oklahoma and Montana. A spokesperson told IndyStar the party paid 'four figures' for the Indiana sign. All four billboards are bright yellow with messages in bold black lettering specific to a health care provider in each state. 'Under Trump's watch, Columbus Regional Health is cutting medical services,' the Columbus billboard reads. It directs passersby to a page on the DNC website with state-by-state impacts of the president's tax and spending cuts bill that was signed into law on July 4. Democrats and advocacy groups have decried the large cuts to Medicaid included in the bill through work requirements and an eventual decrease in the cap on provider taxes from 6% to 3.5%. Indiana relies on those taxes, paid by hospitals, to fund its Medicaid expansion program known as the Healthy Indiana Plan. Columbus Regional Health on June 30, prior to the bill's passage, announced it would close its inpatient rehabilitation unit and outpatient orthopedics and sports medicine services, which the organization said was due to no longer being able to 'cost-effectively provide inpatient rehab services.' The June announcement said some of the cost concerns are due to rising supply costs, 'legislative scrutiny' and state and federal funding cuts. In a statement to IndyStar on July 22, Columbus Regional Health said it was unaware of the DNC billboard and did not provide permission to be referenced. 'Recently, Columbus Regional Health made the announcement of service line and practice closings related to increasing financial constraints and burdens our health system is currently facing," the statement reads. 'These difficult decisions were made under consideration of the many challenges and risks facing not just CRH – but many hospitals, health systems, and medical providers statewide and nationally – in order to remain financially viable.' A $50 billion fund to support rural hospitals was added to the Trump's "One Big Beautiful Bill" toward the end of negotiations between lawmakers to appease senators who were concerned about the size of the proposed Medicaid cuts. But some health policy groups say it's likely not enough to help ease the impact of federal funding losses from the changes to Medicaid in the bill. Indiana could receive some amount of money from $25 billion of the rural health fund dedicated to states that submit applications with the Center for Medicare and Medicaid Services. The CMS Administrator is expected to have flexibility to distribute the other $25 billion. Taxes to Medicaid: 4 ways Trump's 'Big Beautiful Bill' could impact Hoosiers A June letter to Republican leaders from four Senate Democrats argued that Trump's tax and spending cuts bill would put 12 rural Indiana hospitals "uniquely at risk" of closure or cutting services. But the letter, based on data from the Sheps Center for Health Services Research at the University of North Carolina, was sent out before the rural fund was added to the bill. An analysis from the Kaiser Family Foundation, though, found that the rural health fund only offsets about one third of the federal Medicaid funding rural areas around the country are expected to lose under the bill. Scott Tittle, the president of the Indiana Hospital Association, said in a statement to IndyStar that he is also concerned the rural fund will not be enough to cover expected losses for hospitals in Indiana and that the fund itself is temporary. 'There is no additional assistance following the end of the OBBBA's five-year period,' Tittle said in the statement. In a news release about the billboards, DNC chair Ken Martin said Trump 'put the last nail in the coffin for rural hospitals' and that Trump's voters 'will suffer the most.' Nearly 63% of voters in Bartholomew County, where Columbus is located, voted for Trump in the 2024 presidential election. "After blowing a lethal hole in rural hospital funding, Republicans are about to find out that their flimsy funding band-aid won't be enough to protect them from voters' righteous anger,' Martin said. 'These new DNC billboards plainly state exactly what is happening to rural hospitals under Donald Trump's watch.' Contact IndyStar state government and politics reporter Brittany Carloni at
National Observer
09-07-2025
- Politics
- National Observer
Trump allies fume Canadian smoke is ruining summer – and offer misinfo as the solution
Smoke from Canadian wildfires that have forced about a quarter of a million Canadians to evacuate since 2023 are preventing Americans in Trump-voting districts from "spend[ing] time outdoors recreating, enjoying time with family, and creating new memories," six Republican House representatives complained in an official letter. On Monday, the group sent a letter to Kirsten Hillman, Canada's ambassador to the US. They write that smoke from Canadian fires is impacting their constituents' summer plans and ask the Canadian federal government to better manage its forests — and do more to prevent arson. Signatories include Tom Emmer, the GOP's third-highest ranking member, alongside staunch Trump allies Tom Tiffany, Brad Finstad, Glenn Grothman, Michelle Firshbach and Pete Stauber. Emmer, Tiffany, Stauber and Finstad have received at least $408,068 in campaign donations from fossil fuel-linked groups since 2020. "This is not the first year Canadian wildfire smoke has been an issue. In 2023, Canada had its worst year for wildfires on record, last year's fire season was considered one of the worst, and this year seems to be a continuation of previous years," the group wrote. "While we know a key driver of this issue has been a lack of active forest management, we've also seen things like arson as another way multiple large wildfires have ignited in Canada. … Canada has been a friendly neighbor of the United States and the states we represent, so given the significance of this issue, we urge you to relay this message to your government, in particular Natural Resources Canada and the Canadian Forest Service." Taryn Elliott, a spokesperson for the Canadian embassy in Washington, confirmed the embassy has received the letter and shared it with relevant Canadian agencies. Smoke from Canadian wildfires preventing Americans in Trump-voting districts from "spend[ing] time outdoors recreating, enjoying time with family, and creating new memories," six GOP representatives have complained to Canada's US ambassador. Lightning, not arson, behind most fires Contrary to the American group's claims, the cause of Canada's fires is more complicated. While arson and bad forest management practices do cause wildfires, lightning is responsible for most of the country's infernos and burns the most area, according to the Canadian National Fire Database. Climate change is exacerbating the problem, largely because it makes fire-prone days more common by drying out landscapes. Only about four per cent of wildfires in BC over the past decade may have been caused by arson, Forrest Tower, the BC Wildfire Service's director of communications, wrote in an email. Moreover, over the past 100 years, fire suppression has blocked a natural cycle of fire essential to maintain forest health and prevent the massive, devastating fires that have hit BC and other parts of Canada in recent years. To address this problem, the agency has started to let fires that don't harm people or infrastructure burn to restore ecosystem health, and is increasing its use of preventative measures like prescribed burns, he wrote. That hasn't stopped conservative politicians and conspiracy theorists on both sides of the border from hammering on the misleading idea that arson or bad forest management are behind the country's wildfires. In 2023 and 2024, Alberta Premier Danielle Smith placed the blame for devastating fires in her province on arsonists, going so far as to bring in outside arson investigators. By December of that year, the province's Ministry of Forestry and Parks concluded that 0.01 per cent of the total land burned in the province that year was linked to arson. Last year, researchers found that right-wing influencers and websites – including many that attacked pandemic-era public health measures and climate action – leveraged 2023's record-breaking wildfires to spread climate disinformation. The posts became more numerous in June of that year, as smoke from fires in Quebec and Ontario enveloped major American cities like New York. These posts became "more conspiratorial," the report notes, alleging that "eco-terrorists, left extremists and governments set the fires to advance a climate agenda," they found. Lori Daniels, head of the University of British Columbia's Centre for Wildfire Coexistence, wrote in an email that "it is disappointing to see political leaders … lay blame without understanding the complexity of wildfire impacts nor taking any responsibility." The letter fails to acknowledge that thousands of Canadians have been evacuated because of the fires or lost their lives , including two people killed this spring in Lac du Bonnet, Manitoba. It also ignores "climate change and anthropogenic global warming caused by fossil fuels" to instead focus on "conspiracies and misinformation." A charter signed at the end of the G7 conference in Kananaskis, Alta., last month also failed to mention climate change even once — despite its leading role exacerbating wildfire risk — in a move observers attributed to obstruction by President Trump. Nor are Americans the only people to suffer from another country's smoke: fires in Alaska, Washington, Oregon and California have smothered Canadian cities in recent years, with Vancouver and the Okanagan particularly hard hit. "This has certainly been an interesting take given that smoke regularly comes up from Washington [and] Oregon into Canada. Borders don't mean much to wildfire! As recently as yesterday we sent BCWS airtankers to assist with the
Yahoo
19-05-2025
- Politics
- Yahoo
Polling Was Quietly Still Bad in 2024
Pollsters seemed to finally get it right in 2024. After years of bad misses, they said the presidential election would be close, and it was. In fact, the industry did not solve its problems last year. In 2016, pollsters famously underestimated Donald Trump by about 3.2 points on average. In 2024, after eight years of introspection, they underestimated Trump by … 2.9 points. Many of the most accurate pollsters last year were partisan Republican outfits; many of the least accurate were rigorous university polls run by political scientists. Polls can't be perfect; after all, they come with a margin of error. But they should not be missing in the same direction over and over. And chances are the problem extends beyond election polling to opinion surveys more generally. When Trump dismisses his low approval ratings as 'fake polls,' he might just have a point. For years, the media have been covering the travails of the polling industry, always with the premise that next time might be different. That premise is getting harder and harder to accept. Polling used to be simple. You picked up the phone and dialed random digits. People answered their landline and answered your survey. Then, you published the results. In 2000, nearly every national pollster used this methodology, known as random-digit dialing, and their average error was about two points. In subsequent elections, they got even closer, and the error, small as it was, shifted from overestimating Bush in 2000 to underestimating him in 2004—a good sign that the error was random. Then came the Great Polling Miss of 2016. National polls actually came pretty close to predicting the final popular-vote total, but at the state level, particularly in swing states, they missed badly, feeding into the narrative that Hillary Clinton's win was inevitable. The 2016 miss was widely blamed on education polarization. College graduates preferred Clinton and were more likely to respond to polls. So, going forward, most pollsters began adjusting, or 'weighting,' their results to counteract the underrepresentation of non-college-educated voters. In 2018, the polls nailed the midterms, and pollsters rejoiced. That reaction turned out to be premature. The 2020 election went even worse for the polling industry than 2016 had. On average, pollsters had underestimated Trump again, this time by four points. Joe Biden won, but by a much slimmer margin than had been predicted. This sent pollsters searching for a solution yet again. If weighting by education didn't work, then there must be something specific about Trump voters—even Trump voters with a college degree—that made them less likely to answer a poll. So, many pollsters figured, the best way to solve this would be weighting by whether the respondent had previously voted for Trump, or identified as a Republican. This was a controversial move in polling circles. The proportion of the electorate that is Democratic or Republican, or Trump-voting, changes from election to election; that's why polls exist in the first place. Could such elaborate modeling turn polls into something more like predictions than surveys? [Gilad Edelman: The asterisk on Kamala Harris's poll numbers] 'This is where some of the art and science get a little mixed up,' Michael Bailey, a Georgetown professor who studies polling, told me. If you weight a sample to be 30 percent Republican, 30 percent Democrat, and 40 percent independent—because that's roughly how people self-identify when asked—you are making an assumption about how the three groups will behave, not merely matching a poll to population demographics such as age, gender, and education. These assumptions vary from pollster to pollster, often reflecting their unconscious biases. And for most pollsters, these biases seem to point in the same direction: underestimating Trump and overestimating his opponent. 'Most pollsters, like most other people in the expert class, are probably not huge fans of Trump,' the election-forecasting expert Nate Silver told me. This personal dislike may not seem to matter much—after all, this should be a science—but every decision about weighting is a judgment call. Will suburban women show up to vote in 2024? Will young men? What about people who voted for Trump in 2020? All three of these respondent groups have a different weight in an adjusted sample, and the weight that a pollster chooses reflects what the pollster, not the respondents, thinks about the election. Some pollsters might even adjust their weights after the fact if they see a result they find hard to believe. The problem is that sometimes, things that are hard to believe happen, such as Latino voters moving 16 points to the right. This dynamic might explain a curious exception to the trend last year. Overall, most polls missed yet again: The average error was a three-point underestimate of Trump, the same as 2016. But Republican-aligned pollsters did better. In fact, according to Silver's model (others have similar results), four of the five most accurate pollsters in 2024, and seven of the top 10, were right-leaning firms—not because their methods were different, but because their biases were. The most basic problem in 2024 was the same as in 2016: nonresponse bias, the name for the error that is introduced by the fact that people who take polls are different from those who don't. A pollster can weight their way out of this problem if the difference between those who respond and those who don't is an observable demographic characteristic, such as age and gender. If the difference is not easily observable, and it's correlated with how people vote, then the problem becomes extremely difficult to surmount. Take the fact that Trump voters tend to be, on average, less trusting of institutions and less engaged with politics. Even if you perfectly sample the right proportion of men, the right proportions of each age group and education level, and even the right proportion of past Trump voters, you will still pick up the most engaged and trusting voters within each of those groups—who else would spend 10 minutes filling out a poll?—and such people were less likely to vote for Trump in 2024. So after all that weighting and modeling, you still wind up with an underestimate of Trump. (This probably explains why pollsters did quite well in 2018 and 2022: disengaged voters tend to turn out less during midterm elections.) This problem almost certainly afflicts presidential-approval polls too, though there's no election to test their accuracy against. Low-trust voters who don't answer polls don't suddenly transform into reliable respondents once the election's over. According to Nate Silver's Silver Bulletin poll aggregator, Trump's approval is currently six percentage points underwater. But if those approval polls are plagued by the same nonresponse bias as election surveys were last year—which could well be the case—then he's at only negative 3 percent. That might not seem like a big difference, but it would make Trump's approval rate historically pedestrian, in line with where Gerald Ford was at roughly this point in his presidency, rather than historically low. Jason Barabas, a Dartmouth College political scientist, knows something about nonresponse bias. Last year, he directed the new Dartmouth Poll, described by the college as 'an initiative aimed at establishing best practices for polling in New Hampshire.' Barabas and his students mailed out more than 100,000 postcards across New Hampshire, each with a unique code to complete a poll online. This method is not cheap, but it delivers randomness, like old-school random-digit dialing. The Dartmouth Poll also applied all the latest statistical techniques. It was weighted on gender, age, education, partisanship, county, and congressional district, and then fed through a turnout model based on even more of the respondent's biographical details. The methodology was set beforehand, in keeping with scientific best practices, so that Barabas and his research assistant couldn't mess with the weights after the fact to get a result that fit with their expectations. They also experimented with ways to increase response rates: Some respondents were motivated by the chance to win $250, some were sent reminders to respond, and some received a version of the poll that was framed in terms of 'issues' rather than the upcoming election. In the end, none of it mattered. Dartmouth's polling was a disaster. Its final survey showed Kamala Harris up by 28 points in New Hampshire. That was wrong by an order of magnitude; she would win the state by 2.8 points the next day. A six-figure budget, sophisticated methodology, the integrity necessary to preregister their methodology, and the bravery necessary to still release their outlier poll—all that, only to produce what appears to have been the most inaccurate poll of the entire 2024 cycle, and one of the worst results in American polling history. [David A. Graham: The polls are sending Trump a message] Barabas isn't totally sure what happened. But he and his students do have one theory: their poll's name. Trust in higher education is polarized on political lines. Under this theory, Trump-voting New Hampshirites saw a postcard from Dartmouth, an Ivy League school with a mostly liberal faculty and student body, and didn't respond—whereas anti-Trump voters in the state leaped at the opportunity to answer mail from their favorite institution. The Dartmouth Poll is an extreme example, but the same thing is happening basically everywhere: People who take surveys are people who have more trust in institutions, and people who have more trust in institutions are less likely to vote for Trump. Once a pollster wraps their head around this point, their options become slim. They could pay poll respondents in order to reach people who wouldn't otherwise be inclined to answer. The New York Times tried this in collaboration with the polling firm Ipsos, paying up to $25 to each respondent. They found that they reached more moderate voters who usually don't answer the phone and who were more likely to vote for Trump, but said the differences were 'relatively small.' Or pollsters can get more creative with their weights. Jesse Stinebring, a co-founder of the Democratic polling firm Blue Rose Research, told me that his company asks whether respondents 'believe that sometimes a child needs a good hard spanking'—a belief disproportionately held by the type of American who doesn't respond to surveys—and uses the answer alongside the usual weights. Bailey, the Georgetown professor, has an even more out-there proposal. Say you run a poll with a 5 percent response rate that shows Harris winning by four points, and a second poll with a 35 percent response rate that shows her winning by one point. In that situation, Bailey says, you can infer that every 10 points of response rate increases Trump's margin by one percentage point. So if the election has a 65 percent turnout rate, that should mean a two-point Trump victory. It's 'a new way of thinking,' Bailey admitted, in a bit of an understatement. But can you blame him? To be clear, political polls can be valuable even if they underestimate Republicans by a few points. For example, Biden likely would have stayed in the 2024 race if polls hadn't shown him losing to Trump by an insurmountable margin—one that was, in retrospect, almost certainly understated. The problem is that people expect the most from polls when elections are close, but that is when polls are the least reliable, given the inevitability of error. And if the act of answering a survey, or engaging in politics at all, correlates so strongly with one side, then pollsters can only do so much. The legendary Iowa pollster Ann Selzer has long hated the idea of baking your own assumptions into a poll, which is why she used weights for only a few variables, all demographic. For decades, this stubborn refusal to guess in advance earned her both accurate poll results and the adoration of those who study polling: In 2016, a 538 article called her 'The Best Pollster in Politics.' Selzer's final poll of 2024 showed Harris leading Iowa by three percentage points. Three days later, Trump would win the state by 13 points, a stunning 16-point miss. A few weeks after the election, Selzer released an investigation into what might have gone wrong. 'To cut to the chase,' she concluded, 'I found nothing to illuminate the miss.' The same day the analysis was published, she retired from election polling. Article originally published at The Atlantic
Atlantic
19-05-2025
- Politics
- Atlantic
Polling Was Quietly Still Bad in 2024
Pollsters seemed to finally get it right in 2024. After years of bad misses, they said the presidential election would be close, and it was. In fact, the industry did not solve its problems last year. In 2016, pollsters famously underestimated Donald Trump by about 3.2 points on average. In 2024, after eight years of introspection, they underestimated Trump by … 2.9 points. Many of the most accurate pollsters last year were partisan Republican outfits; many of the least accurate were rigorous university polls run by political scientists. Polls can't be perfect; after all, they come with a margin of error. But they should not be missing in the same direction over and over. And chances are the problem extends beyond election polling to opinion surveys more generally. When Trump dismisses his low approval ratings as ' fake polls,' he might just have a point. For years, the media have been covering the travails of the polling industry, always with the premise that next time might be different. That premise is getting harder and harder to accept. Polling used to be simple. You picked up the phone and dialed random digits. People answered their landline and answered your survey. Then, you published the results. In 2000, nearly every national pollster used this methodology, known as random-digit dialing, and their average error was about two points. In subsequent elections, they got even closer, and the error, small as it was, shifted from overestimating Bush in 2000 to underestimating him in 2004—a good sign that the error was random. Then came the Great Polling Miss of 2016. National polls actually came pretty close to predicting the final popular-vote total, but at the state level, particularly in swing states, they missed badly, feeding into the narrative that Hillary Clinton's win was inevitable. The 2016 miss was widely blamed on education polarization. College graduates preferred Clinton and were more likely to respond to polls. So, going forward, most pollsters began adjusting, or ' weighting,' their results to counteract the underrepresentation of non-college-educated voters. In 2018, the polls nailed the midterms, and pollsters rejoiced. That reaction turned out to be premature. The 2020 election went even worse for the polling industry than 2016 had. On average, pollsters had underestimated Trump again, this time by four points. Joe Biden won, but by a much slimmer margin than had been predicted. This sent pollsters searching for a solution yet again. If weighting by education didn't work, then there must be something specific about Trump voters—even Trump voters with a college degree—that made them less likely to answer a poll. So, many pollsters figured, the best way to solve this would be weighting by whether the respondent had previously voted for Trump, or identified as a Republican. This was a controversial move in polling circles. The proportion of the electorate that is Democratic or Republican, or Trump-voting, changes from election to election; that's why polls exist in the first place. Could such elaborate modeling turn polls into something more like predictions than surveys? Gilad Edelman: The asterisk on Kamala Harris's poll numbers 'This is where some of the art and science get a little mixed up,' Michael Bailey, a Georgetown professor who studies polling, told me. If you weight a sample to be 30 percent Republican, 30 percent Democrat, and 40 percent independent—because that's roughly how people self-identify when asked—you are making an assumption about how the three groups will behave, not merely matching a poll to population demographics such as age, gender, and education. These assumptions vary from pollster to pollster, often reflecting their unconscious biases. And for most pollsters, these biases seem to point in the same direction: underestimating Trump and overestimating his opponent. 'Most pollsters, like most other people in the expert class, are probably not huge fans of Trump,' the election-forecasting expert Nate Silver told me. This personal dislike may not seem to matter much—after all, this should be a science—but every decision about weighting is a judgment call. Will suburban women show up to vote in 2024? Will young men? What about people who voted for Trump in 2020? All three of these respondent groups have a different weight in an adjusted sample, and the weight that a pollster chooses reflects what the pollster, not the respondents, thinks about the election. Some pollsters might even adjust their weights after the fact if they see a result they find hard to believe. The problem is that sometimes, things that are hard to believe happen, such as Latino voters moving 16 points to the right. This dynamic might explain a curious exception to the trend last year. Overall, most polls missed yet again: The average error was a three-point underestimate of Trump, the same as 2016. But Republican-aligned pollsters did better. In fact, according to Silver's model (others have similar results), four of the five most accurate pollsters in 2024, and seven of the top 10, were right-leaning firms—not because their methods were different, but because their biases were. The most basic problem in 2024 was the same as in 2016: nonresponse bias, the name for the error that is introduced by the fact that people who take polls are different from those who don't. A pollster can weight their way out of this problem if the difference between those who respond and those who don't is an observable demographic characteristic, such as age and gender. If the difference is not easily observable, and it's correlated with how people vote, then the problem becomes extremely difficult to surmount. Take the fact that Trump voters tend to be, on average, less trusting of institutions and less engaged with politics. Even if you perfectly sample the right proportion of men, the right proportions of each age group and education level, and even the right proportion of past Trump voters, you will still pick up the most engaged and trusting voters within each of those groups—who else would spend 10 minutes filling out a poll?—and such people were less likely to vote for Trump in 2024. So after all that weighting and modeling, you still wind up with an underestimate of Trump. (This probably explains why pollsters did quite well in 2018 and 2022: disengaged voters tend to turn out less during midterm elections.) This problem almost certainly afflicts presidential-approval polls too, though there's no election to test their accuracy against. Low-trust voters who don't answer polls don't suddenly transform into reliable respondents once the election's over. According to Nate Silver's Silver Bulletin poll aggregator, Trump's approval is currently six percentage points underwater. But if those approval polls are plagued by the same nonresponse bias as election surveys were last year—which could well be the case—then he's at only negative 3 percent. That might not seem like a big difference, but it would make Trump's approval rate historically pedestrian, in line with where Gerald Ford was at roughly this point in his presidency, rather than historically low. Jason Barabas, a Dartmouth College political scientist, knows something about nonresponse bias. Last year, he directed the new Dartmouth Poll, described by the college as 'an initiative aimed at establishing best practices for polling in New Hampshire.' Barabas and his students mailed out more than 100,000 postcards across New Hampshire, each with a unique code to complete a poll online. This method is not cheap, but it delivers randomness, like old-school random-digit dialing. The Dartmouth Poll also applied all the latest statistical techniques. It was weighted on gender, age, education, partisanship, county, and congressional district, and then fed through a turnout model based on even more of the respondent's biographical details. The methodology was set beforehand, in keeping with scientific best practices, so that Barabas and his research assistant couldn't mess with the weights after the fact to get a result that fit with their expectations. They also experimented with ways to increase response rates: Some respondents were motivated by the chance to win $250, some were sent reminders to respond, and some received a version of the poll that was framed in terms of 'issues' rather than the upcoming election. In the end, none of it mattered. Dartmouth's polling was a disaster. Its final survey showed Kamala Harris up by 28 points in New Hampshire. That was wrong by an order of magnitude; she would win the state by 2.8 points the next day. A six-figure budget, sophisticated methodology, the integrity necessary to preregister their methodology, and the bravery necessary to still release their outlier poll—all that, only to produce what appears to have been the most inaccurate poll of the entire 2024 cycle, and one of the worst results in American polling history. David A. Graham: The polls are sending Trump a message Barabas isn't totally sure what happened. But he and his students do have one theory: their poll's name. Trust in higher education is polarized on political lines. Under this theory, Trump-voting New Hampshirites saw a postcard from Dartmouth, an Ivy League school with a mostly liberal faculty and student body, and didn't respond—whereas anti-Trump voters in the state leaped at the opportunity to answer mail from their favorite institution. The Dartmouth Poll is an extreme example, but the same thing is happening basically everywhere: People who take surveys are people who have more trust in institutions, and people who have more trust in institutions are less likely to vote for Trump. Once a pollster wraps their head around this point, their options become slim. They could pay poll respondents in order to reach people who wouldn't otherwise be inclined to answer. The New York Times tried this in collaboration with the polling firm Ipsos, paying up to $25 to each respondent. They found that they reached more moderate voters who usually don't answer the phone and who were more likely to vote for Trump, but said the differences were 'relatively small.' Or pollsters can get more creative with their weights. Jesse Stinebring, a co-founder of the Democratic polling firm Blue Rose Research, told me that his company asks whether respondents 'believe that sometimes a child needs a good hard spanking'—a belief disproportionately held by the type of American who doesn't respond to surveys—and uses the answer alongside the usual weights. Bailey, the Georgetown professor, has an even more out-there proposal. Say you run a poll with a 5 percent response rate that shows Harris winning by four points, and a second poll with a 35 percent response rate that shows her winning by one point. In that situation, Bailey says, you can infer that every 10 points of response rate increases Trump's margin by one percentage point. So if the election has a 65 percent turnout rate, that should mean a two-point Trump victory. It's 'a new way of thinking,' Bailey admitted, in a bit of an understatement. But can you blame him? To be clear, political polls can be valuable even if they underestimate Republicans by a few points. For example, Biden likely would have stayed in the 2024 race if polls hadn't shown him losing to Trump by an insurmountable margin—one that was, in retrospect, almost certainly understated. The problem is that people expect the most from polls when elections are close, but that is when polls are the least reliable, given the inevitability of error. And if the act of answering a survey, or engaging in politics at all, correlates so strongly with one side, then pollsters can only do so much. The legendary Iowa pollster Ann Selzer has long hated the idea of baking your own assumptions into a poll, which is why she used weights for only a few variables, all demographic. For decades, this stubborn refusal to guess in advance earned her both accurate poll results and the adoration of those who study polling: In 2016, a 538 article called her 'The Best Pollster in Politics.' Selzer's final poll of 2024 showed Harris leading Iowa by three percentage points. Three days later, Trump would win the state by 13 points, a stunning 16-point miss. A few weeks after the election, Selzer released an investigation into what might have gone wrong. 'To cut to the chase,' she concluded, 'I found nothing to illuminate the miss.' The same day the analysis was published, she retired from election polling.
Yahoo
29-04-2025
- Business
- Yahoo
At 100 days, economic anxieties come alive in Michigan: ‘I wish the message was clearer'
President Donald Trump is taking a self-described victory lap on Tuesday as he returns to one of the biggest battleground states for the first time since taking office, basking in the glow of 100 days back in the White House. For Pashko Ujkaj, who can feel the economic pressures at his Dodge Park Coney Island diner, it's far too early to measure the success – or bemoan the failure – of Trump's second term. 'I think it's too early to give him a grade,' Ujkaj said. 'If he puts this economy back on track and wins these tariffs to our advantage, I think people will feel more comfortable. If he doesn't, it's not going to be good. It's not going to be good.' The economic headwinds and their accompanying hardships weigh heavy on the minds of voters who supported Trump – and those who did not – as his presidency hits 100 days. It's an arbitrary, yet inescapable, milestone for early assessments of his whirlwind return to power. In 2016, Ujkaj voted for Trump. Four years later, he did not. When asked whom he supported in 2024, he paused for an uncomfortably long moment as customers sat within earshot, before replying: 'Let's just say you're putting me on the spot.' Like many business owners, he would rather listen to opinions than offer his own, considering he is as likely to serve breakfast to Trump-voting Republicans as he is lunch to Democrats who backed Kamala Harris at his Macomb County diner north of Detroit. But after absorbing the last few months of those conversations, he is certain of one thing: The economy and a promise of lowering costs, which helped propel Trump to the White House, now stand as one of the president's biggest challenges. 'I think the fair thing to give him a grade – if you want to really give him a true grade – is by the end of the year,' Ujkaj said. By then, he added, 'I want to see this economy better.' For all the carefully watched national economic indicators, including a University of Michigan survey this month that showed consumer sentiment fell to 52% from 57% in March, Ujkaj has also noticed a telling metric inside his diner. 'Instead of coming out three or four times a week, people might only come out one or two times,' Ujkaj said in an interview Monday before the lunch crowd arrived. 'We have a lot of seniors. They're on fixed incomes. And when you see those prices skyrocket, they feel it the most, right?' In Michigan, where one in five jobs are linked in some way to the auto industry, fallout from the Trump administration's tariff policy comes up in one conversation after another. The on-again, off-again duties – on neighboring Canada, Mexico and beyond – have roiled markets and frustrated John Walus, a three-time Trump voter, Army veteran and retired autoworker. 'I just wish the message was clearer on where he's going with the tariffs,' Walus said. 'I think that would settle a lot of the turmoil right now, especially with the stock market. There's been a lot of uncertainty right now regarding that.' As he paused for a moment to talk Monday afternoon while walking in downtown Mt. Clemens, Walus added: 'How is he going to get from here to there? I think he needs to do a better job of explaining how that's going to be done.' As the president was set to make his way to Michigan on Tuesday for an evening rally at Macomb Community College in Warren, the White House signaled another modification on auto-related tariffs, responding to fears from the nation's biggest automakers about economic consequences. The president is poised to sign an executive order Tuesday that will lay out a three-year plan that breaks down different phases of the auto tariffs – a decision that came after Trump fielded calls from multiple automaker CEOs, White House officials familiar with the conversation told CNN. Chris Vitale, a retired Michigan auto worker who was in the Rose Garden on April 2 as Trump announced the sweeping tariffs in an event the White House hailed as 'Liberation Day,' said he applauded the president's approach to tariffs to revive American manufacturing. 'I know how our industry has been disadvantaged, for the last 60 years,' Vitale said. 'The tariffs, in effect, got people's attention and brought them to the negotiating table, which is probably the goal all along.' Vitale spent three decades at Chrysler, which is now Stellantis, before retiring at the end of last year. He is among the many rank-and-file auto workers and retirees who have spoken out in favor of Trump's tariffs, one of many things he says he supports about Trump's second term. 'For the first time in four years, I don't have a feeling of dread,' Vitale said. 'It's like that weight, that dread, of what new regulation, what new law, what experimental vaccine, what mandate is going to get imposed next.' Before administration officials previewed their latest tariff pause on Tuesday, the whiplash and uncertainty has become a growing point of frustration to Michael Taylor, the mayor of Sterling Heights, a Republican who supported Trump in 2016 but has since twice voted against him. 'The tariffs are on, then they're off, then they're changed,' Taylor said in an interview. 'Business owners, they really struggle when they don't have a certain landscape ahead of them. These tariffs have created chaos in that regard.' The promise of reviving American manufacturing by imposing steep tariffs is overstated, he said, and far more complicated than the Trump administration has indicated or explained. 'He's not just misleading. He's lying,' Taylor argued about a tariff strategy Trump has long believed in, with visions of factories suddenly roaring back to life. 'It's frustrating because he has a lot of supporters who believe him even though he knows he's not telling the truth.' 'Small businesses are the backbone of America,' Gibson said. 'How can that be if tariffs are brought into play? Then, little people, businesses like mine, are going to struggle and may not even exist because we cannot afford to pay those kind of prices and absorb it into our little business.' Naszreen Gibson, who owns The Rendezvous with Tea, said she is bracing for the impact of Trump administration's tariffs on tea imports from Sri Lanka, China and other countries around the world. She said she did not vote for Trump, but many of her customers did. Her sales are down from a year ago, she said, which she attributes to economic anxiety and belt-tightening before a possible recession. 'Every time someone talks about the tariffs, the stock market goes crazy,' Gibson said. 'It goes up and down, people have their retirement funds there, their 401(k)s and so on.' The president's visit to Michigan on Tuesday marks a rare moment of taking his economic agenda on the road for the first campaign-style rally of his second term. While he has flown to his homes in Florida or New Jersey most weekends since returning to office, the term-limited Trump has logged virtually no travel during the week. It's a far different pattern than during his first term, when he delivered speeches in several battleground states during his first 100 days. For a president who campaigned on lowering costs for Americans and ushering in what he promised would be a new 'Golden Age,' the economic concerns reverberating through conversations with voters across Macomb County are a potential warning for his administration at this stage. The signs of unease are palpable, even for optimistic business owners like Ujkaj at Dodge Park Coney Island. 'Right now, I don't think it's where he wants it to be,' Ujkaj said of the president's performance after 100 days in office. 'Do I think it's going to get better? Yes. I do think he wants his legacy to be known for something great.'
