In a pre-election essay, I contrasted the prognostications of poll-influenced prediction models with the wisdom of the betting crowd. I suspected that bettors—many of whom believed their candidate would win—were overly influenced by the false consensus effect (the presumption that most others see the world as we do). But score this round for the wisdom of the betting crowd, which better anticipated the election closeness, including Trump’s Florida victory. That’s a contrast with Britain’s Brexit vote, where polls indicated a toss-up (a half percent edge for “Remain”) while the betting markets wrongly estimated a 90+ percent Remain chance. The U.S. polls had a rougher-than-usual year, with the final Biden margin likely near 4.5 percent rather than the predicted 8 percent. The pollsters also struggled in key states. On election eve, the average poll gave Trump a 0.8 percent edge in Ohio; he won by 8 percent. In Florida, the polls gave Biden a 2.5 percent edge; he lost by about 3 percent. In Wisconsin, the polls favored Biden by 8.4 percent; he won by less than a percent. With so few people now responding to pollster calls and texts, precision is increasing a challenge (even with pollster adjusting results to match the voting demographics). But lest we dismiss the polls and sophisticated forecasters, let’s grant them three points. First, they got many of the specifics right. FiveThirtyEight, for example, correctly anticipated 48 of the 50 presumed state outcomes. Some of its correct predictions even surprised its creator: Second, polls, as Silver has said , could be worse and they would still greatly exceed conventional seat-of-the-pants wisdom. In a University of Michigan national survey in September, 4 in 5 Republicans incorrectly anticipated a Trump victory. Third, although the models missed on some details, credit them with the big picture. “Biden’s Favored in Our Final Presidential Forecast, but It’s a Fine Line Between a Landslide and a Nail-Biter,” headlined FiveThirtyEight in its final election forecast. And Biden did win. As I write, though, the betting markets —mindful of fraud allegations and legal challenges—still give Donald Trump a 12 percent chance of victory. But this, says Silver , “ is basically a market saying there's a 12% chance that the sky isn't blue.” Consider, say the media analysts who have called the election: How would widespread voter fraud account for Donald Trump’s doing much better than predicted by the historically reliable polls (and for down ballot Republicans doing better yet)? And how could that be so across America in countless local municipalities, including those with Republican-elected officials? Take my community—Holland, Michigan, a historically Republican town where Betsy DeVos grew up and has a home just a bike ride from my own. With a changing demography that now closely mirrors the nation, our last three presidential elections have been razor close, with Donald Trump narrowly edging Hillary Clinton in 2016 . . . but with Biden defeating Trump by 11 percent. Likewise, our surrounding county—one of the nation’s most reliably Republican counties—voted Trump by 30.2 percent in 2016 but only 21.5 percent in 2020. Neighboring Kent County, also leans Republican and is the home of Republican-turned-Libertarian Congressman Justin Amash, gave Biden 50,000 more votes than Clinton received four years ago. Is it conceivable that the Republican-friendly voting officials in countless such places across the U.S. consistently committed Biden-supporting fraud? All in all, it was not the best of years for pollsters and modelers, though it was a worse year for John and Joan Q. Public’s expectations of their candidate’s triumphant success. Winston Churchill once called democracy “the worst form of Government except for all those other forms.” To borrow his sentiment, polls and models are the worst forms of prediction, except for all the other forms. (For David Myers’ other essays on psychological science and everyday life, visit TalkPsych.com .) ... View more

To many observers, the election was a clash of two Americas—a war between two increasingly partisan identities, each of which is incredulous at what the other supports. As the Pew Research Center documents , the gulf between them is enormous. For example, 74 percent of Biden supporters told the Pew Research Center that “it is a lot more difficult” to be a Black person in this country than to be a White person, a view shared by a mere 9% of Trump supporters. Likewise, 68 percent of Biden supporters said climate change was important to their vote—as was the case for but 11 percent of Trump supporters (who scored this last among 12 issues of possible concern). Many Republicans, having believed Donald Trump would win, are aghast at the defeat of their pro-life, law-and-order supporting, free-enterprise-buttressing, patriotic values-embracing leader. Democrats had hoped the massive turnout heralded a massive blue wave repudiation of Trump’s bigotry, divisiveness, and climate unfriendly actions. Thus, many are stunned that all this barely moved the needle—from a 2016 electoral vote margin of 2.1 percent to about 5 percent—despite improved Democratic party demographics, increased fund-raising, and a better-liked candidate. In Why We’re Polarized , journalist Ezra Klein draws on social science research to document how Americans now view politics through the lens of their strongly held partisan identities—who “we” are versus who “they” are. Klein describes how our political tribal identities engage what we psychologists call “motivated reasoning.” Whatever our party and its leaders do—even when it clashes with what we formerly believed—we rationalize. Even morality and religion have become subservient to politics. In the latest issue of Science , an interdisciplinary team of 15 scholars, led by social psychologist Eli Finkel, further describe today’s “political sectarianism” and the rise of out-party hate. They document the growing contempt that today’s partisans feel for the other party, which greatly exceeds the love they have for their own. Recall, too, the power of the availability heuristic—our tendency to estimate the commonality of events based on their mental availability. Whatever information pops readily into mind—often vivid images—can hijack our thinking. Thus, potent memes (“defund the police”) and scenes (rampaging protesters) can define those we associate with them, even if the meme represents no political party and the scene represents an infinitesimal proportion of otherwise peaceful demonstrators. In the post-Trump era to come, both parties will be debating and massaging their brand identities in hopes of drawing more people in while retaining their base. Partisans on both sides could, methinks, benefit from a reading of Peter Wehner’s prescient The Death of Politics: How to Heal Our Frayed Republic After Trump —a guidebook to seeking a more perfect union (a book acclaimed, remarkably, by both Democratic strategist David Axelrod and Republican strategist Karl Rove). (For David Myers’ other essays on psychological science and everyday life, visit TalkPsych.com .) ... View more

I see you. My psychic powers enable me, from a great distance, to peer into your heart and to sense your unease. Regardless of your political leanings, you understand the upcoming U.S. election to be momentous, world-changing, the most important of your lifetime. Part of you is hopeful, but a larger part of you is feeling tense. Anxious. Fearing a future that would follow the outcome you dread. Hungering for indications of the likely outcome, you read the latest commentary and devour the latest polls. You may even glean insight from the betting markets (here and here) , which offer “the wisdom of the crowd.” They are akin to stock markets, in which people place bets on future stock values, with the current market value—the midpoint between those expecting a stock to rise and those expecting it to fall—representing the distillation of all available information and insight. As stock market booms and busts remind us, the crowd sometimes displays an irrational exuberance or despair. Yet, as Princeton economist Burton Malkiel has repeatedly demonstrated , no individual stock picker (or mutual fund) has had the smarts to consistently outguess the efficient marketplace. You may also, if you are a political geek, have welcomed clues to the election outcome from prediction models ( here and here ) that combine historical information, demographics, and poll results to forecast the result. But this year, the betting and prediction markets differ sharply. The betting markets see a 34 percent chance of a Trump victory, while the prediction models see but a 5 to 10 percent chance. So who should we believe? Skeptics scoff that the poll-influenced prediction models erred in 2016. FiveThirtyEight’s final election forecast gave Donald Trump only a 28 percent chance of winning. So, was it wrong? Consider a simple prediction model that predicted a baseball player’s chance of a hit based on the player’s batting average. If a .280 hitter came to the plate and got a hit, would we discount our model? Of course not, because we understand the model’s prediction that sometimes (28% of the time, in this case), the less likely outcome will happen. (If it never does, the model errs.) But why do the current betting markets diverge from the prediction models? FiveThirtyEight modeler Nate Silver has an idea: The Dunning-Kruger effect, as psychology students know, is the repeated finding that incompetence tends not to recognize itself. As one person explained to those unfamiliar with Silver’s allusion: Others noted that the presidential betting markets, unlike the stock markets, are drawing on limited (once every four years) information—with people betting only small amounts on their hunches, and without the sophisticated appraisal that informs stock investing. And what are their hunches? Surely, these are informed by the false consensus effect—our tendency to overestimate the extent to which others share our views. Thus, in the University of Michigan’s July Survey of Consumers, 83 percent of Democrats and 84 percent of Republicans predicted that voters would elect their party’s presidential candidate. Ergo, bettors are surely, to some extent, drawing on their own preferences, which—thanks to the false consensus effect—inform their predictions. What we are, we see in others. So, if I were a betting person, I would wager based on the prediction models. Usually, there is wisdom to the crowd. But sometimes . . . we shall soon see . . . the crowd is led astray by the whispers of its own inner voices. ----- P.S. At 10:30 a.m. on election day, the Economist model projects a 78 percent chance of a Biden Florida victory, FiveThirtyEight.com projects a Biden Florida victory with a 2.5 percent vote margin, and electionbettingodds.com betting market average estimates a 62% chance of a Trump Florida victory. Who's right--the models or the bettors? Stay tuned! P.S.S. on November 4: Mea culpa. I was wrong. Although the models--like weather forecasts estimating the percent change of rain--allow for unlikely possibilities, the wisdom of the betting crowd won this round--both in Florida and in foreseeing a closer-than-expected election. (For David Myers’ other essays on psychological science and everyday life, visit TalkPsych.com .)   ... View more

At a May 26 Rose Garden press conference, President Trump asked a face-masked reporter: “Can you take it off, because I cannot hear you.” On this matter, I can empathize with our president. At a recent dental appointment, I could understand but half my hygienist’s and dentist’s spoken words. Despite being a person with hearing loss, I normally hear them both with ease, thanks to our proximity. But when muffled by their masks and face shields, their words became indistinct. One speech researcher explains that the thicker fabrics of many home-made masks are especially likely to “significantly block the airstream, diminishing the acoustic energy.” Although I wouldn’t have it otherwise—they and other caregivers are protecting their patients, and protecting themselves from their patients—masks do impede accessibility. More than we realize, we are all natural lip readers. Even a normal-hearing friend, visiting an ice cream shop, could not make out the masked clerk’s words: “Cup or cone”? Another acquaintance, during a hospital ER visit, reporting understanding only about half of what the masked nurses and doctors said to her. In the fully masked classrooms of my campus, colleagues tell me that, for example, “I have found myself asking students to repeat their questions.” Another colleague says “I am using my outside voice,” which takes more energy (and which other colleagues report leaves them drained). Another reports that “It is frustrating to continue to ask a student to repeat something and I fear it will shut down discussion and make most classes a lecture performance—in which case I might as well go completely online.” Another has, while the weather allows, taken his class outdoors where, socially distanced, they can see facial expressions and lip-read one another, mask-free. The essential lesson: There is more to hearing than meets the ears. What our eyes see influences what our brain hears. That phenomenon, which you can experience here , is called the McGurk effect. Moreover, thanks to our powers of instantly reading facial expressions, much of our communication is nonverbal. We share our emotions through our words but also through our smiles, our tight lips, our gaping mouths. Even our emojis vary the mouth: :- ( and :- ) . One colleague explains: “It adds a barrier that feels formal and inaccessible when you can't shake someone's hand, and then you can't smile at them to say ‘but I still want to get to know you.’” Cut off from facial expression, our communication is hampered. So is face recognition. With students’ faces masked, colleagues report becoming partially face-blind. They’re not only having more difficultly immediately knowing which student is speaking, but also recognizing their obscured faces: “I cannot call on a familiar student by name, because I can't tell who anyone is.” Add to this the depletion of normal emotional display and mimicry and the natural result will be weakened social bonds, including those between teacher and student, argues German psychiatrist and psychologist Manfred Spitzer. Given that masks—and also face shields in health care—are essential to controlling the pandemic, how can we salvage hearing accessibility in a masked world? Clear hearing is helpful to everyone—our minds wander less when little cognitive effort is required--but especially for those with hearing loss. In retail contexts, where a transaction occurs with a masked person behind a clear plastic screen, a simple solution can serve most people with hearing aids. Given a microphone and an installed hearing loop , a clerk’s voice will magnetically transmit to the telecoil sensor in most aids and all cochlear implants. As I can vouch , the system also works beautifully in other venues, including auditoriums, airports, and places of worship . With the mere push of a button, my hearing aids can become in-the-ear speakers that receive PA sound and customize it for my hearing needs. But what about classrooms, where campus face-mask mandates will require teachers and students to wear mutually protective masks—and in some cases (including the classrooms of my own campus) also to speak from behind a plastic barrier? What can schools and colleges do to enable hearing accessibility while also supporting public health? Admonish clarity. Schools can admonish instructors to be mindful that their audience is experiencing some muffling of sound, without supportive lip reading. Health care workers can likewise be coached to speak more deliberately and distinctly: “Your patients, especially your older patients, are having more trouble hearing you than you suppose.” That, alas, will be only a modestly effective solution, because we soon revert to our natural speaking styles. When one experimenter asked people to act as expressive or inhibited as possible while stating opinions, the naturally expressive people—even when feigning inhibition—were less inhibited than naturally inhibited people. And inexpressive people, when feigning expressiveness, were less expressive than naturally expressive folks. It’s hard to be, for any length of time, someone you’re not. Your speaking speed and style is, once your self-consciousness subsides, irrepressible. Transparent face masks. A second solution is to equip instructors with a face mask or shield that allows people to read lips and facial expressions. One example, used by some on my campus (such as the colleague below, at left) is the ClearMask. (An alternative, germ-filtering transparent Swiss surgical mask to be available in 2021 from hmcare.ch is shown at right.) Mindful of the face’s role in communication, one colleague is hoping, with appropriate permissions, to equip all his students with face shields. Two other colleagues have, however, told me of being bothered both by breathing issues with a clear mask, and also by the altered sound of their own voice (a familiar distraction to new hearing aid wearers). Define safe distance. A third solution is to specify a safe distance at which an instructor may lower the mask while lecturing. Imagine two very different classrooms. In a small seminar, colleges would surely mandate a professor's mask wearing when seated around a table with students. When lecturing while alone as a sage on the stage of a large auditorium, the professor would be sufficiently physically distanced to make a mask superfluous. In the gradations of classrooms in between, could colleges define a minimum safe distance at which a mask could be lowered while teaching? Add PA systems. A fourth solution is to add PA systems to intermediate-size rooms. An instructor’s head-mounted mic could transmit to a class through newly installed speakers. Live captioning. Google Meet’s captioning illustrates the potential for instant, accurate captioning that rivals the speed and precision of human captioner. Not only is it, therefore, a preferred video conferencing technology for accessibility (Zoom, take note), the visual information display aids anyone whose mind has momentarily wandered. Might classrooms be similarly equipped with open captioned displays of instructors’ remarks? Hearing loops. Finally, schools could employ hearing technology. Such ranges from personal assistive technology—in which an instructor wears a mic that transmits to individual hard-of-hearing students with special receivers—to class and auditorium hearing loops that transmit to most of today’s hearing aids and cochlear implants (as I illustrate here from my Hope College campus). We want to stay healthy. And we want to hear. Let those planning for in-person, under-the-pandemic instruction aim for both—a health-protecting accessibility. (For David Myers’ other essays on psychological science and everyday life, visit TalkPsych.com .) ... View more