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(An early conclusion: while we were late to understand how angry white voters were, a perhaps even more serious lapse was in failing to recognize how many disaffected Democrats there were who would stay home rather than support their party’s flawed candidate.)

Stories that would have killed any other politician—truly worrisome revelations about everything from the federal taxes Trump dodged to the charitable donations he lied about, the women he insulted and allegedly assaulted, and the mob ties that have long dogged him—did not stop Trump from thriving in this election year

the Oxford Dictionaries announced that “post-truth” had been chosen as the 2016 word of the year, defining it as a condition “in which objective facts are less influential in shaping public opinion than appeals to emotion and personal belief.”

Meantime, Trump personally blacklisted news organizations like Politico and The Washington Post when they published articles he didn’t like during the campaign, has openly mused about rolling back press freedoms enshrined by the U.S. Supreme Court, and has now named Stephen Bannon, until recently the executive chairman of Breitbart—a right-wing fringe website with a penchant for conspiracy theories and anti-Semitic tropes—to serve as one of his top White House advisers.

none of this has any modern precedent. And what makes it unique has nothing to do with the outcome of the election. This time, the victor was a right-wing demagogue; next time, it may be a left-wing populist who learns the lessons of Trump’s win.

This is no mere academic argument. The election of 2016 showed us that Americans are increasingly choosing to live in a cloud of like-minded spin, surrounded by the partisan political hackery and fake news that poisons their Facebook feeds.

To help us understand it all, there were choices, but not that many: three TV networks that mattered, ABC, CBS, and NBC; two papers for serious journalism, The New York Times and The Washington Post; and two giant-circulation weekly newsmagazines, Time and Newsweek. That, plus whatever was your local daily newspaper, pretty much constituted the news.

Fake news is thriving In the final three months of the presidential campaign, the 20 top-performing fake election news stories generated more engagement on Facebook than the top stories from major news outlets such as The New York Times.

Eventually, I came to think of the major media outlets of that era as something very similar to the big suburban shopping malls we flocked to in the age of shoulder pads and supply-side economics: We could choose among Kmart and Macy’s and Saks Fifth Avenue as our budgets and tastes allowed, but in the end the media were all essentially department stores, selling us sports and stock tables and foreign news alongside our politics, whether we wanted them or not. It may not have been a monopoly, but it was something pretty close.

This was still journalism in the scarcity era, and it affected everything from what stories we wrote to how fast we could produce them. Presidents could launch global thermonuclear war with the Russians in a matter of minutes, but news from the American hinterlands often took weeks to reach their sleepy capital. Even information within that capital was virtually unobtainable without a major investment of time and effort. Want to know how much a campaign was raising and spending from the new special-interest PACs that had proliferated? Prepare to spend a day holed up at the Federal Election Commission’s headquarters down on E Street across from the hulking concrete FBI building, and be sure to bring a bunch of quarters for the copy machine.

I am writing this in the immediate, shocking aftermath of a 2016 presidential election in which the Pew Research Center found that a higher percentage of Americans got their information about the campaign from late-night TV comedy shows than from a national newspaper. Don Graham sold the Post three years ago and though its online audience has been skyrocketing with new investments from Amazon.com founder Jeff Bezos, it will never be what it was in the ‘80s. That same Pew survey reported that a mere 2 percent of Americans today turned to such newspapers as the “most helpful” guides to the presidential campaign.

In 2013, Mark Leibovich wrote a bestselling book called This Town about the party-hopping, lobbyist-enabling nexus between Washington journalists and the political world they cover. A key character was Politico’s Mike Allen, whose morning email newsletter “Playbook” had become a Washington ritual, offering all the news and tidbits a power player might want to read before breakfast—and Politico’s most successful ad franchise to boot. In many ways, even that world of just a few years ago now seems quaint: the notion that anyone could be a single, once-a-day town crier in This Town (or any other) has been utterly exploded by the move to Twitter, Facebook, and all the rest. We are living, as Mark put it to me recently, “in a 24-hour scrolling version of what ‘Playbook’ was.”

Whether it was Walter Cronkite or The New York Times, they preached journalistic “objectivity” and spoke with authority when they pronounced on the day’s developments—but not always with the depth and expertise that real competition or deep specialization might have provided. They were great—but they were generalists.

I remained convinced that reporting would hold its value, especially as our other advantages—like access to information and the expensive means to distribute it—dwindled. It was all well and good to root for your political team, but when it mattered to your business (or the country, for that matter), I reasoned, you wouldn’t want cheerleading but real reporting about real facts. Besides, the new tools might be coming at us with dizzying speed—remember when that radical new video app Meerkat was going to change absolutely everything about how we cover elections?—but we would still need reporters to find a way inside Washington’s closed doors and back rooms, to figure out what was happening when the cameras weren’t rolling.

And if the world was suffering from information overload—well, so much the better for us editors; we would be all the more needed to figure out what to listen to amid the noise.

Trump turned out to be more correct than we editors were: the more relevant point of the Access Hollywood tape was not about the censure Trump would now face but the political reality that he, like Bill Clinton, could survive this—or perhaps any scandal. Yes, we were wrong about the Access Hollywood tape, and so much else.

These days, Politico has a newsroom of 200-odd journalists, a glossy award-winning magazine, dozens of daily email newsletters, and 16 subscription policy verticals. It’s a major player in coverage not only of Capitol Hill but many other key parts of the capital, and some months during this election year we had well over 30 million unique visitors to our website, a far cry from the controlled congressional circulation of 35,000 that I remember Roll Call touting in our long-ago sales materials.

, we journalists were still able to cover the public theater of politics while spending more of our time, resources, and mental energy on really original reporting, on digging up stories you couldn’t read anywhere else. Between Trump’s long and checkered business past, his habit of serial lying, his voluminous and contradictory tweets, and his revision of even his own biography, there was lots to work with. No one can say that Trump was elected without the press telling us all about his checkered past.

politics was NEVER more choose-your-own-adventure than in 2016, when entire news ecosystems for partisans existed wholly outside the reach of those who at least aim for truth

Pew found that nearly 50 percent of self-described conservatives now rely on a single news source, Fox, for political information they trust.

As for the liberals, they trust only that they should never watch Fox, and have MSNBC and Media Matters and the remnants of the big boys to confirm their biases.

And then there are the conspiracy-peddling Breitbarts and the overtly fake-news outlets of this overwhelming new world; untethered from even the pretense of fact-based reporting, their version of the campaign got more traffic on Facebook in the race’s final weeks than all the traditional news outlets combined.

When we assigned a team of reporters at Politico during the primary season to listen to every single word of Trump’s speeches, we found that he offered a lie, half-truth, or outright exaggeration approximately once every five minutes—for an entire week. And it didn’t hinder him in the least from winning the Republican presidential nomination.

when we repeated the exercise this fall, in the midst of the general election campaign, Trump had progressed to fibs of various magnitudes just about once every three minutes!

By the time Trump in September issued his half-hearted disavowal of the Obama “birther” whopper he had done so much to create and perpetuate, one national survey found that only 1 in 4 Republicans was sure that Obama was born in the U.S., and various polls found that somewhere between a quarter and a half of Republicans believed he’s Muslim. So not only did Trump think he was entitled to his own facts, so did his supporters. It didn’t stop them at all from voting for him.

in part, it’s not just because they disagree with the facts as reporters have presented them but because there’s so damn many reporters, and from such a wide array of outlets, that it’s often impossible to evaluate their standards and practices, biases and preconceptions. Even we journalists are increasingly overwhelmed.

So much terrific reporting and writing and digging over the years and … Trump? What happened to consequences? reporting that matters? Sunlight, they used to tell us, was the best disinfectant for what ails our politics.

2016 suggests a different outcome: We’ve achieved a lot more transparency in today’s Washington—without the accountability that was supposed to come with it.

Friday’s report encompasses 144 reports of unidentified aerial phenomena from 2004 until this year and offers almost no conclusive interpretation for the sightings. “They very clearly demonstrate an array of aerial behaviors, which makes it very clear to us that there are multiple types of unidentified aerial phenomena that require different explanations,” one of the officials said.

“The potential of this report was actually significant,” said Seth Shostak, a senior astronomer at the SETI Institute in Mountain View, Calif. “It could have come up with something that was incontrovertible evidence for extraterrestrial flight. That was the implicit promise here. But in the end, it didn’t go any farther than reports made in the 1950s. We can explain some of these things, but we can’t explain them all.”

Since the 1960s, advances in resuscitation had helped to revive thousands of people who might otherwise have died. About 10% or 20% of those people brought with them stories of near-death experiences in which they felt their souls or selves departing from their bodies

According to several international surveys and studies, one in 10 people claims to have had a near-death experience involving cardiac arrest, or a similar experience in circumstances where they may have come close to death. That’s roughly 800 million souls worldwide who may have dipped a toe in the afterlife.

In the 1970s, a small network of cardiologists, psychiatrists, medical sociologists and social psychologists in North America and Europe began investigating whether near-death experiences proved that dying is not the end of being, and that consciousness can exist independently of the brain. The field of near-death studies was born.

in 1975, an American medical student named Raymond Moody published a book called Life After Life.

Meanwhile, new technologies and techniques were helping doctors revive more and more people who, in earlier periods of history, would have almost certainly been permanently deceased.

“We are now at the point where we have both the tools and the means to scientifically answer the age-old question: What happens when we die?” wrote Sam Parnia, an accomplished resuscitation specialist and one of the world’s leading experts on near-death experiences, in 2006. Parnia himself was devising an international study to test whether patients could have conscious awareness even after they were found clinically dead.

Borjigin, together with several colleagues, took the first close look at the record of electrical activity in the brain of Patient One after she was taken off life support. What they discovered – in results reported for the first time last year – was almost entirely unexpected, and has the potential to rewrite our understanding of death.

“I believe what we found is only the tip of a vast iceberg,” Borjigin told me. “What’s still beneath the surface is a full account of how dying actually takes place. Because there’s something happening in there, in the brain, that makes no sense.”

Over the next 30 years, researchers collected thousands of case reports of people who had had near-death experiences

Moody was their most important spokesman; he eventually claimed to have had multiple past lives and built a “psychomanteum” in rural Alabama where people could attempt to summon the spirits of the dead by gazing into a dimly lit mirror.

near-death studies was already splitting into several schools of belief, whose tensions continue to this day. One influential camp was made up of spiritualists, some of them evangelical Christians, who were convinced that near-death experiences were genuine sojourns in the land of the dead and divine

It is no longer unheard of for people to be revived even six hours after being declared clinically dead. In 2011, Japanese doctors reported the case of a young woman who was found in a forest one morning after an overdose stopped her heart the previous night; using advanced technology to circulate blood and oxygen through her body, the doctors were able to revive her more than six hours later, and she was able to walk out of the hospital after three weeks of care

The second, and largest, faction of near-death researchers were the parapsychologists, those interested in phenomena that seemed to undermine the scientific orthodoxy that the mind could not exist independently of the brain. These researchers, who were by and large trained scientists following well established research methods, tended to believe that near-death experiences offered evidence that consciousness could persist after the death of the individua

Their aim was to find ways to test their theories of consciousness empirically, and to turn near-death studies into a legitimate scientific endeavour.

Finally, there emerged the smallest contingent of near-death researchers, who could be labelled the physicalists. These were scientists, many of whom studied the brain, who were committed to a strictly biological account of near-death experiences. Like dreams, the physicalists argued, near-death experiences might reveal psychological truths, but they did so through hallucinatory fictions that emerged from the workings of the body and the brain.

Between 1975, when Moody published Life After Life, and 1984, only 17 articles in the PubMed database of scientific publications mentioned near-death experiences. In the following decade, there were 62. In the most recent 10-year span, there were 221.

Today, there is a widespread sense throughout the community of near-death researchers that we are on the verge of great discoveries

“We really are in a crucial moment where we have to disentangle consciousness from responsiveness, and maybe question every state that we consider unconscious,”

“I think in 50 or 100 years time we will have discovered the entity that is consciousness,” he told me. “It will be taken for granted that it wasn’t produced by the brain, and it doesn’t die when you die.”

it is in large part because of a revolution in our ability to resuscitate people who have suffered cardiac arrest

In his book, Moody distilled the reports of 150 people who had had intense, life-altering experiences in the moments surrounding a cardiac arrest. Although the reports varied, he found that they often shared one or more common features or themes. The narrative arc of the most detailed of those reports – departing the body and travelling through a long tunnel, having an out-of-body experience, encountering spirits and a being of light, one’s whole life flashing before one’s eyes, and returning to the body from some outer limit – became so canonical that the art critic Robert Hughes could refer to it years later as “the familiar kitsch of near-death experience”.

Loss of oxygen to the brain and other organs generally follows within seconds or minutes, although the complete cessation of activity in the heart and brain – which is often called “flatlining” or, in the case of the latter, “brain death” – may not occur for many minutes or even hours.

That began to change in 1960, when the combination of mouth-to-mouth ventilation, chest compressions and external defibrillation known as cardiopulmonary resuscitation, or CPR, was formalised. Shortly thereafter, a massive campaign was launched to educate clinicians and the public on CPR’s basic techniques, and soon people were being revived in previously unthinkable, if still modest, numbers.

scientists learned that, even in its acute final stages, death is not a point, but a process. After cardiac arrest, blood and oxygen stop circulating through the body, cells begin to break down, and normal electrical activity in the brain gets disrupted. But the organs don’t fail irreversibly right away, and the brain doesn’t necessarily cease functioning altogether. There is often still the possibility of a return to life. In some cases, cell death can be stopped or significantly slowed, the heart can be restarted, and brain function can be restored. In other words, the process of death can be reversed.

In a medical setting, “clinical death” is said to occur at the moment the heart stops pumping blood, and the pulse stops. This is widely known as cardiac arrest

In 2019, a British woman named Audrey Schoeman who was caught in a snowstorm spent six hours in cardiac arrest before doctors brought her back to life with no evident brain damage.

That is a key tenet of the parapsychologists’ arguments: if there is consciousness without brain activity, then consciousness must dwell somewhere beyond the brain

Some of the parapsychologists speculate that it is a “non-local” force that pervades the universe, like electromagnetism. This force is received by the brain, but is not generated by it, the way a television receives a broadcast.

In order for this argument to hold, something else has to be true: near-death experiences have to happen during death, after the brain shuts down

To prove this, parapsychologists point to a number of rare but astounding cases known as “veridical” near-death experiences, in which patients seem to report details from the operating room that they might have known only if they had conscious awareness during the time that they were clinically dead.

At the very least, Parnia and his colleagues have written, such phenomena are “inexplicable through current neuroscientific models”. Unfortunately for the parapsychologists, however, none of the reports of post-death awareness holds up to strict scientific scrutiny. “There are many claims of this kind, but in my long decades of research into out-of-body and near-death experiences I never met any convincing evidence that this is true,”

In other cases, there’s not enough evidence to prove that the experiences reported by cardiac arrest survivors happened when their brains were shut down, as opposed to in the period before or after they supposedly “flatlined”. “So far, there is no sufficiently rigorous, convincing empirical evidence that people can observe their surroundings during a near-death experience,”

The parapsychologists tend to push back by arguing that even if each of the cases of veridical near-death experiences leaves room for scientific doubt, surely the accumulation of dozens of these reports must count for something. But that argument can be turned on its head: if there are so many genuine instances of consciousness surviving death, then why should it have so far proven impossible to catch one empirically?

The spiritualists and parapsychologists are right to insist that something deeply weird is happening to people when they die, but they are wrong to assume it is happening in the next life rather than this one. At least, that is the implication of what Jimo Borjigin found when she investigated the case of Patient One.

Given the levels of activity and connectivity in particular regions of her dying brain, Borjigin believes it’s likely that Patient One had a profound near-death experience with many of its major features: out-of-body sensations, visions of light, feelings of joy or serenity, and moral re-evaluations of one’s life. Of course,

“As she died, Patient One’s brain was functioning in a kind of hyperdrive,” Borjigin told me. For about two minutes after her oxygen was cut off, there was an intense synchronisation of her brain waves, a state associated with many cognitive functions, including heightened attention and memory. The synchronisation dampened for about 18 seconds, then intensified again for more than four minutes. It faded for a minute, then came back for a third time.

n those same periods of dying, different parts of Patient One’s brain were suddenly in close communication with each other. The most intense connections started immediately after her oxygen stopped, and lasted for nearly four minutes. There was another burst of connectivity more than five minutes and 20 seconds after she was taken off life support. In particular, areas of her brain associated with processing conscious experience – areas that are active when we move through the waking world, and when we have vivid dreams – were communicating with those involved in memory formation. So were parts of the brain associated with empathy. Even as she slipped irre

something that looked astonishingly like life was taking place over several minutes in Patient One’s brain.

Although a few earlier instances of brain waves had been reported in dying human brains, nothing as detailed and complex as what occurred in Patient One had ever been detected.

In the moments after Patient One was taken off oxygen, there was a surge of activity in her dying brain. Areas that had been nearly silent while she was on life support suddenly thrummed with high-frequency electrical signals called gamma waves. In particular, the parts of the brain that scientists consider a “hot zone” for consciousness became dramatically alive. In one section, the signals remained detectable for more than six minutes. In another, they were 11 to 12 times higher than they had been before Patient One’s ventilator was removed.

“The brain, contrary to everybody’s belief, is actually super active during cardiac arrest,” Borjigin said. Death may be far more alive than we ever thought possible.

“The brain is so resilient, the heart is so resilient, that it takes years of abuse to kill them,” she pointed out. “Why then, without oxygen, can a perfectly healthy person die within 30 minutes, irreversibly?”

Evidence is already emerging that even total brain death may someday be reversible. In 2019, scientists at Yale University harvested the brains of pigs that had been decapitated in a commercial slaughterhouse four hours earlier. Then they perfused the brains for six hours with a special cocktail of drugs and synthetic blood. Astoundingly, some of the cells in the brains began to show metabolic activity again, and some of the synapses even began firing.

In case you don’t speak fluent bureaucratese, “good discussion” means that the Republicans made it clear the report had to go. And “it was pulled” means the CRS obeyed. The Times quoted a person with knowledge of the deliberations as saying the decision on Sept. 28 to withdraw the report was “made against the advice of the research service’s economics division” and that the author, Thomas Hungerford, stood by its findings.

While the physical sciences produce many detailed and precise predictions, the social sciences do not.  The reason is that such predictions almost always require randomized controlled experiments, which are seldom possible when people are involved.  For one thing, we are too complex: our behavior depends on an enormous number of tightly interconnected variables that are extraordinarily difficult to  distinguish and study separately

Without a strong track record of experiments leading to successful predictions, there is seldom a basis for taking social scientific results as definitive

our policy discussions should simply ignore social scientific research.  We should, as Manzi himself proposes, find ways of injecting more experimental data into government decisions.  But above all, we need to develop a much better sense of the severely limited reliability of social scientific results.   Media reports of research should pay far more attention to these limitations, and scientists reporting the results need to emphasize what they don’t show as much as what they do.

Given the limited predictive success and the lack of consensus in social sciences, their conclusions can seldom be primary guides to setting policy.  At best, they can supplement the general knowledge, practical experience, good sense and critical intelligence that we can only hope our political leaders will have.

How much authority should we give to such work in our policy decisions?  The question is important because media reports often seem to assume that any result presented as “scientific” has a claim to our serious attention.

Without a strong track record of experiments leading to successful predictions, there is seldom a basis for taking social scientific results as definitive

our policy discussions should simply ignore social scientific research.  We should, as Manzi himself proposes, find ways of injecting more experimental data into government decisions.  But above all, we need to develop a much better sense of the severely limited reliability of social scientific results.   Media reports of research should pay far more attention to these limitations, and scientists reporting the results need to emphasize what they don’t show as much as what they do

our policy discussions should simply ignore social scientific research.  We should, as Manzi himself proposes, find ways of injecting more experimental data into government decisions.  But above all, we need to develop a much better sense of the severely limited reliability of social scientific results.   Media reports of research should pay far more attention to these limitations, and scientists reporting the results need to emphasize what they don’t show as much as what they do.

Social sciences may be surrounded by the “paraphernalia” of the natural sciences, such as technical terminology, mathematical equations, empirical data and even carefully designed experiments. 

Given the limited predictive success and the lack of consensus in social sciences, their conclusions can seldom be primary guides to setting policy.  At best, they can supplement the general knowledge, practical experience, good sense and critical intelligence that we can only hope our political leaders will have.

For the well-being of its users, Bejar argued, Meta needed to change course, focusing less on a flawed system of rules-based policing and more on addressing such bad experiences

The company would need to collect data on what upset users and then work to combat the source of it, nudging those who made others uncomfortable to improve their behavior and isolating communities of users who deliberately sought to harm others.

“I am appealing to you because I believe that working this way will require a culture shift,” Bejar wrote to Zuckerberg—the company would have to acknowledge that its existing approach to governing Facebook and Instagram wasn’t working.

During and after Bejar’s time as a consultant, Meta spokesman Andy Stone said, the company has rolled out several product features meant to address some of the Well-Being Team’s findings. Those features include warnings to users before they post comments that Meta’s automated systems flag as potentially offensive, and reminders to be kind when sending direct messages to users like content creators who receive a large volume of messages. 

Meta’s classifiers were reliable enough to remove only a low single-digit percentage of hate speech with any degree of precision.

Bejar was floored—all the more so when he learned that virtually all of his daughter’s friends had been subjected to similar harassment. “DTF?” a user they’d never met would ask, using shorthand for a vulgar proposition. Instagram acted so rarely on reports of such behavior that the girls no longer bothered reporting them. 

Meta’s own statistics suggested that big problems didn’t exist. 

Meta had come to approach governing user behavior as an overwhelmingly automated process. Engineers would compile data sets of unacceptable content—things like terrorism, pornography, bullying or “excessive gore”—and then train machine-learning models to screen future content for similar material.

While users could still flag things that upset them, Meta shifted resources away from reviewing them. To discourage users from filing reports, internal documents from 2019 show, Meta added steps to the reporting process. Meta said the changes were meant to discourage frivolous reports and educate users about platform rules. 

The outperformance of Meta’s automated enforcement relied on what Bejar considered two sleights of hand. The systems didn’t catch anywhere near the majority of banned content—only the majority of what the company ultimately removed

“Please don’t talk about my underage tits,” Bejar’s daughter shot back before reporting his comment to Instagram. A few days later, the platform got back to her: The insult didn’t violate its community guidelines.

Also buttressing Meta’s statistics were rules written narrowly enough to ban only unambiguously vile material. Meta’s rules didn’t clearly prohibit adults from flooding the comments section on a teenager’s posts with kiss emojis or posting pictures of kids in their underwear, inviting their followers to “see more” in a private Facebook Messenger group. 

“Mark personally values freedom of expression first and foremost and would say this is a feature and not a bug,” Rosen responded

Narrow rules and unreliable automated enforcement systems left a lot of room for bad behavior—but they made the company’s child-safety statistics look pretty good according to Meta’s metric of choice: prevalence.

Defined as the percentage of content viewed worldwide that explicitly violates a Meta rule, prevalence was the company’s preferred measuring stick for the problems users experienced.

According to prevalence, child exploitation was so rare on the platform that it couldn’t be reliably estimated, less than 0.05%, the threshold for functional measurement. Content deemed to encourage self-harm, such as eating disorders, was just as minimal, and rule violations for bullying and harassment occurred in just eight of 10,000 views. 

“There’s a grading-your-own-homework problem,”

Meta defines what constitutes harmful content, so it shapes the discussion of how successful it is at dealing with it.”

It could reconsider its AI-generated “beauty filters,” which internal research suggested made both the people who used them and those who viewed the images more self-critical

the team built a new questionnaire called BEEF, short for “Bad Emotional Experience Feedback.

A recurring survey of issues 238,000 users had experienced over the past seven days, the effort identified problems with prevalence from the start: Users were 100 times more likely to tell Instagram they’d witnessed bullying in the last week than Meta’s bullying-prevalence statistics indicated they should.

“People feel like they’re having a bad experience or they don’t,” one presentation on BEEF noted. “Their perception isn’t constrained by policy.

they seemed particularly common among teens on Instagram.

Among users under the age of 16, 26% recalled having a bad experience in the last week due to witnessing hostility against someone based on their race, religion or identity

More than a fifth felt worse about themselves after viewing others’ posts, and 13% had experienced unwanted sexual advances in the past seven days. 

The vast gap between the low prevalence of content deemed problematic in the company’s own statistics and what users told the company they experienced suggested that Meta’s definitions were off, Bejar argued

To minimize content that teenagers told researchers made them feel bad about themselves, Instagram could cap how much beauty- and fashion-influencer content users saw.

Proving to Meta’s leadership that the company’s prevalence metrics were missing the point was going to require data the company didn’t have. So Bejar and a group of staffers from the Well-Being Team started collecting it

And it could build ways for users to report unwanted contacts, the first step to figuring out how to discourage them.

One experiment run in response to BEEF data showed that when users were notified that their comment or post had upset people who saw it, they often deleted it of their own accord. “Even if you don’t mandate behaviors,” said Krieger, “you can at least send signals about what behaviors aren’t welcome.”

But among the ranks of Meta’s senior middle management, Bejar and Krieger said, BEEF hit a wall. Managers who had made their careers on incrementally improving prevalence statistics weren’t receptive to the suggestion that the approach wasn’t working. 

After three decades in Silicon Valley, he understood that members of the company’s C-Suite might not appreciate a damning appraisal of the safety risks young users faced from its product—especially one citing the company’s own data. 

“This was the email that my entire career in tech trained me not to send,” he says. “But a part of me was still hoping they just didn’t know.”

“Policy enforcement is analogous to the police,” he wrote in the email Oct. 5, 2021—arguing that it’s essential to respond to crime, but that it’s not what makes a community safe. Meta had an opportunity to do right by its users and take on a problem that Bejar believed was almost certainly industrywide.

fter Haugen’s airing of internal research, Meta had cracked down on the distribution of anything that would, if leaked, cause further reputational damage. With executives privately asserting that the company’s research division harbored a fifth column of detractors, Meta was formalizing a raft of new rules for employees’ internal communication.

Among the mandates for achieving “Narrative Excellence,” as the company called it, was to keep research data tight and never assert a moral or legal duty to fix a problem.

“I had to write about it as a hypothetical,” Bejar said. Rather than acknowledging that Instagram’s survey data showed that teens regularly faced unwanted sexual advances, the memo merely suggested how Instagram might help teens if they faced such a problem.

The hope that the team’s work would continue didn’t last. The company stopped conducting the specific survey behind BEEF, then laid off most everyone who’d worked on it as part of what Zuckerberg called Meta’s “year of efficiency.

If Meta was to change, Bejar told the Journal, the effort would have to come from the outside. He began consulting with a coalition of state attorneys general who filed suit against the company late last month, alleging that the company had built its products to maximize engagement at the expense of young users’ physical and mental health. Bejar also got in touch with members of Congress about where he believes the company’s user-safety efforts fell short. 

Jobs reports reveal key economic indicators, and thus this one will likely influence the Federal Reserve’s decision making  at the next Federal Open Market Committee meeting on June 14.

If replication is what separates the rigor of science from the squishiness of pseudoscience, where do we put all these rigorously validated findings that can no longer be proved? Which results should we believe?

Schooler demonstrated that subjects shown a face and asked to describe it were much less likely to recognize the face when shown it later than those who had simply looked at it. Schooler called the phenomenon “verbal overshadowing.”

The most likely explanation for the decline is an obvious one: regression to the mean. As the experiment is repeated, that is, an early statistical fluke gets cancelled out. The extrasensory powers of Schooler’s subjects didn’t decline—they were simply an illusion that vanished over time.

yet Schooler has noticed that many of the data sets that end up declining seem statistically solid—that is, they contain enough data that any regression to the mean shouldn’t be dramatic. “These are the results that pass all the tests,” he says. “The odds of them being random are typically quite remote, like one in a million. This means that the decline effect should almost never happen. But it happens all the time!

this is why Schooler believes that the decline effect deserves more attention: its ubiquity seems to violate the laws of statistics

In 2001, Michael Jennions, a biologist at the Australian National University, set out to analyze “temporal trends” across a wide range of subjects in ecology and evolutionary biology. He looked at hundreds of papers and forty-four meta-analyses (that is, statistical syntheses of related studies), and discovered a consistent decline effect over time, as many of the theories seemed to fade into irrelevance.

Jennions admits that his findings are troubling, but expresses a reluctance to talk about them

publicly. “This is a very sensitive issue for scientists,” he says. “You know, we’re supposed to be dealing with hard facts, the stuff that’s supposed to stand the test of time. But when you see these trends you become a little more skeptical of things.”

While publication bias almost certainly plays a role in the decline effect, it remains an incomplete explanation. For one thing, it fails to account for the initial prevalence of positive results among studies that never even get submitted to journals. It also fails to explain the experience of people like Schooler, who have been unable to replicate their initial data despite their best efforts.

Jennions, similarly, argues that the decline effect is largely a product of publication bias, or the tendency of scientists and scientific journals to prefer positive data over null results, which is what happens when no effect is found. The bias was first identified by the statistician Theodore Sterling, in 1959, after he noticed that ninety-seven per cent of all published psychological studies with statistically significant data found the effect they were looking for

Sterling saw that if ninety-seven per cent of psychology studies were proving their hypotheses, either psychologists were extraordinarily lucky or they published only the outcomes of successful experiments.

One of his most cited papers has a deliberately provocative title: “Why Most Published Research Findings Are False.”

suspects that an equally significant issue is the selective reporting of results—the data that scientists choose to document in the first place. Palmer’s most convincing evidence relies on a statistical tool known as a funnel graph. When a large number of studies have been done on a single subject, the data should follow a pattern: studies with a large sample size should all cluster around a common value—the true result—whereas those with a smaller sample size should exhibit a random scattering, since they’re subject to greater sampling error. This pattern gives the graph its name, since the distribution resembles a funnel.

after Palmer plotted every study of fluctuating asymmetry, he noticed that the distribution of results with smaller sample sizes wasn’t random at all but instead skewed heavily toward positive results. Palmer has since documented a similar problem in several other contested subject areas. “Once I realized that selective reporting is everywhere in science, I got quite depressed,” Palmer told me. “As a researcher, you’re always aware that there might be some nonrandom patterns, but I had no idea how widespread it is.”

Palmer summarized the impact of selective reporting on his field: “We cannot escape the troubling conclusion that some—perhaps many—cherished generalities are at best exaggerated in their biological significance and at worst a collective illusion nurtured by strong a-priori beliefs often repeated.”

Palmer emphasizes that selective reporting is not the same as scientific fraud. Rather, the problem seems to be one of subtle omissions and unconscious misperceptions, as researchers struggle to make sense of their results. Stephen Jay Gould referred to this as the “sho

horning” process.

“A lot of scientific measurement is really hard,” Simmons told me. “If you’re talking about fluctuating asymmetry, then it’s a matter of minuscule differences between the right and left sides of an animal. It’s millimetres of a tail feather. And so maybe a researcher knows that he’s measuring a good male”—an animal that has successfully mated—“and he knows that it’s supposed to be symmetrical. Well, that act of measurement is going to be vulnerable to all sorts of perception biases. That’s not a cynical statement. That’s just the way human beings work.”

For Simmons, the steep rise and slow fall of fluctuating asymmetry is a clear example of a scientific paradigm, one of those intellectual fads that both guide and constrain research: after a new paradigm is proposed, the peer-review process is tilted toward positive results. But then, after a few years, the academic incentives shift—the paradigm has become entrenched—so that the most notable results are now those that disprove the theory.

John Ioannidis, an epidemiologist at Stanford University, argues that such distortions are a serious issue in biomedical research. “These exaggerations are why the decline has become so common,” he says. “It’d be really great if the initial studies gave us an accurate summary of things. But they don’t. And so what happens is we waste a lot of money treating millions of patients and doing lots of follow-up studies on other themes based on results that are misleading.”

In 2005, Ioannidis published an article in the Journal of the American Medical Association that looked at the forty-nine most cited clinical-research studies in three major medical journals.

the data Ioannidis found were disturbing: of the thirty-four claims that had been subject to replication, forty-one per cent had either been directly contradicted or had their effect sizes significantly downgraded.

the most troubling fact emerged when he looked at the test of replication: out of four hundred and thirty-two claims, only a single one was consistently replicable. “This doesn’t mean that none of these claims will turn out to be true,” he says. “But, given that most of them were done badly, I wouldn’t hold my breath.”

According to Ioannidis, the main problem is that too many researchers engage in what he calls “significance chasing,” or finding ways to interpret the data so that it passes the statistical test of significance—the ninety-five-per-cent boundary invented by Ronald Fisher.

One of the classic examples of selective reporting concerns the testing of acupuncture in different countries. While acupuncture is widely accepted as a medical treatment in various Asian countries, its use is much more contested in the West. These cultural differences have profoundly influenced the results of clinical trials.

The problem of selective reporting is rooted in a fundamental cognitive flaw, which is that we like proving ourselves right and hate being wrong.

“It feels good to validate a hypothesis,” Ioannidis said. “It feels even better when you’ve got a financial interest in the idea or your career depends upon it. And that’s why, even after a claim has been systematically disproven”—he cites, for instance, the early work on hormone replacement therapy, or claims involving various vitamins—“you still see some stubborn researchers citing the first few studies

That’s why Schooler argues that scientists need to become more rigorous about data collection before they publish. “We’re wasting too much time chasing after bad studies and underpowered experiments,”

The current “obsession” with replicability distracts from the real problem, which is faulty design.

“Every researcher should have to spell out, in advance, how many subjects they’re going to use, and what exactly they’re testing, and what constitutes a sufficient level of proof. We have the tools to be much more transparent about our experiments.”

Schooler recommends the establishment of an open-source database, in which researchers are required to outline their planned investigations and document all their results. “I think this would provide a huge increase in access to scientific work and give us a much better way to judge the quality of an experiment,”

scientific research will always be shadowed by a force that can’t be curbed, only contained: sheer randomness. Although little research has been done on the experimental dangers of chance and happenstance, the research that exists isn’t encouraging.

The disturbing implication of the Crabbe study is that a lot of extraordinary scientific data are nothing but noise. The hyperactivity of those coked-up Edmonton mice wasn’t an interesting new fact—it was a meaningless outlier, a by-product of invisible variables we don’t understand.

The problem, of course, is that such dramatic findings are also the most likely to get published in prestigious journals, since the data are both statistically significant and entirely unexpected

This suggests that the decline effect is actually a decline of illusion. While Karl Popper imagined falsification occurring with a single, definitive experiment—Galileo refuted Aristotelian mechanics in an afternoon—the process turns out to be much messier than that.

Many scientific theories continue to be considered true even after failing numerous experimental tests.

Even the law of gravity hasn’t always been perfect at predicting real-world phenomena. (In one test, physicists measuring gravity by means of deep boreholes in the Nevada desert found a two-and-a-half-per-cent discrepancy between the theoretical predictions and the actual data.)

Such anomalies demonstrate the slipperiness of empiricism. Although many scientific ideas generate conflicting results and suffer from falling effect sizes, they continue to get cited in the textbooks and drive standard medical practice. Why? Because these ideas seem true. Because they make sense. Because we can’t bear to let them go. And this is why the decline effect is so troubling. Not because it reveals the human fallibility of science, in which data are tweaked and beliefs shape perceptions. (Such shortcomings aren’t surprising, at least for scientists.) And not because it reveals that many of our most exciting theories are fleeting fads and will soon be rejected. (That idea has been around since Thomas Kuhn.)

The decline effect is troubling because it reminds us how difficult it is to prove anything. We like to pretend that our experiments define the truth for us. But that’s often not the case. Just because an idea is true doesn’t mean it can be proved. And just because an idea can be proved doesn’t mean it’s true. When the experiments are done, we still have to choose what to believe. ♦

HRW's experts take a close look at witness statements and photographs and video of the victims and -- above all -- the remains of the weapons that appear to have been used.

The report provides another map that shows that there were several military bases around Zamalka and Moadimiyeh on August 21st, that were within the correct firing distanc

In two nonfiction books, scheduled to be published in January, technology experts examine similar consumer-ranking techniques already in widespread use.

While a federal law called the Fair Credit Reporting Act requires consumer Reporting agencies to provide individuals with copies of their credit reports on request, many other companies are free to keep their proprietary consumer scores to themselves.

Befitting the founder of a firm that markets reputation management, Mr. Fertik contends that individuals have some power to influence commercial scoring systems.

“This will happen whether or not you want to participate, and these scores will be used by others to make major decisions about your life, such as whether to hire, insure, or even date you,”

“Important corporate actors have unprecedented knowledge of the minutiae of our daily lives,” he writes in “The Black Box Society: The Secret Algorithms That Control Money and Information” (Harvard University Press), “while we know little to nothing about how they use this knowledge to influence important decisions that we — and they — make.”

Data brokers amass dossiers with thousands of details about individual consumers, like age, religion, ethnicity, profession, mortgage size, social networks, estimated income and health concerns such as impotence and irritable bowel syndrome. Then analytics engines can compare patterns in those variables against computer forecasting models. Algorithms are used to assign consumers scores — and to recommend offering, or withholding, particular products, services or fees — based on predictions about their behavior.

It’s a fictional forecast of a data-deterministic culture in which computer algorithms constantly analyze consumers’ profiles, issuing individuals numeric rankings that may benefit or hinder them.

Think of this technique as reputation engine optimization. If an algorithm incorrectly pegs you as physically unfit, for instance, the book suggests that you can try to mitigate the wrong. You can buy a Fitbit fitness tracker, for instance, and upload the exercise data to a public profile — or even “snap that Fitbit to your dog” and “you’ll quickly be the fittest person in your town.”

Professor Pasquale offers a more downbeat reading. Companies, he says, are using such a wide variety of numerical rating systems that it would be impossible for average people to significantly influence their scores.

“Corporations depend on automated judgments that may be wrong, biased or destructive,” Professor Pasquale writes. “Faulty data, invalid assumptions and defective models can’t be corrected when they are hidden.”

Moreover, trying to influence scoring systems could backfire. If a person attached a fitness device to a dog and tried to claim the resulting exercise log, he suggests, an algorithm might be able to tell the difference and issue that person a high score for propensity toward fraudulent activity.

“People shouldn’t think they can outwit corporations with hundreds of millions of dollars,” Professor Pasquale said in a phone interview.Consumers would have more control, he argues, if Congress extended the right to see and correct credit reports to other kinds of rankings.

provided by democracy are able to constrain governments’ desire to manipulate information or, more specifically, their desire to exaggerate how well the economy is doing,

"The way I try to answer the question above is by comparing GDP (a self-reported indicator, prone to manipulation) and nighttime lights (recorded by satellites from outer space and much harder to manipulate) as measures of economic activity."

"Consumption of nearly all goods in the evening requires lights," that paper explained. "As income rises, so does light usage per person, in both consumption activities and many investment activities."

As a result, increases in nighttime lighting generally track with increases in GDP

Martinez sorted the world's countries by their Freedom House score, which classifies countries on a spectrum ranging from "free" to "not free," based on categories such as civil rights protections and civil liberties. He then looked at how changes in nighttime lighting correlated with the countries' self-reported GDP measures.

"I find that a 10 percent increase in nighttime lights is associated with a 2.4 percent increase in GDP in the most democratic countries and with a 2.9 percent to 3.4 percent increase in GDP in the most authoritarian ones," Martinez said. The most obvious explanation is that those countries are the most likely to fudge their GDP figures to make their political leaders look good.

Beyond that, he found that authoritarian countries previously ruled by communist governments were particularly likely to report high GDP relative to nighttime lighting, as were authoritarian countries that were coming up on an election year.

In the early months of the pandemic, the economic downturn in low- and middle-income countries was almost certainly worse than any other recent global economic crisis that we know of, whether the Asian financial crisis of the late 1990s, the Great Recession that started in 2008, or the more recent Ebola crisis,

The pandemic has produced some hopeful innovations, including a partnership between the government of Togo in West Africa and UC Berkeley's Center for Effective Global Action (CEGA) on a system to provide relief payments via digital networks.

The new study -- the first of its kind globally -- reports that after two decades of growth in many low- and middle-income countries, the economic crisis resulting from the COVID-19 pandemic threatens profound long-term impact: Reduced childhood nutrition could have health consequences later in life.

The study was launched in spring 2020, as China, Europe and the U.S. led global efforts to check spread of the virus through ambitious lockdowns of business, schools and transit. Three independent research teams, including CEGA, joined to conduct surveys in the countries where they already worked.

"COVID-19 and its economic shock present a stark threat to residents of low- and middle-income countries -- where most of the world's population resides -- which lack the social safety nets that exist in rich countries,

Reports early in the pandemic suggested that developing countries might be less vulnerable because their populations are so much younger than those in Europe and North America.

In Colombia, 87% of respondents nationwide reported lost income in the early phase of the pandemic. Such losses were reported by more than 80% of people nationwide in Rwanda and Ghana.

In the Philippines, 77% of respondents nationwide said they faced difficulty purchasing food because stores were closed, transport was shut down or food supplies were inadequate. Similar reports came from 68% of Colombians and 64% of respondents in Sierra Leone; rates were similar for some communities within other countries.

Food insecurity rose sharply.

: In Bangladesh, 69% of landless agricultural households reported that they were forced to eat less, along with 48% of households in rural Kenya

Between April and early July 2020, they connected with 30,000 households, including over 100,000 people, in nine countries with a combined population of 500 million: Burkina Faso, Ghana, Kenya, Rwanda and Sierra Leone in Africa; Bangladesh, Nepal and the Philippines in Asia; and Colombia in South America. The surveys were conducted by telephone.

The evidence we've collected shows dire economic consequences ... which, if left unchecked, could thrust millions of vulnerable households into poverty."

In North America and Europe, nations may be struggling with vaccination plans, but vaccines have barely arrived in most low-income countries, he said

If we can spread the wealth in terms of pandemic relief assistance and vaccine distribution, we're all going to get out of this hole faster."

Until now, that term had been widely understood to refer to fabricated news accounts that are meant to spread virally online.

But conservative cable and radio personalities, top Republicans and even Mr. Trump himself, incredulous about suggestions that that fake stories may have helped swing the election, have appropriated the term and turned it against any news they see as hostile to their agenda.

In defining “fake news” so broadly and seeking to dilute its meaning, they are capitalizing on the declining credibility of all purveyors of information, one product of the country’s increasing political polarization.

“Over the years, we’ve effectively brainwashed the core of our audience to distrust anything that they disagree with. And now it’s gone too far,” said John Ziegler, a conservative radio host, who has been critical of what he sees as excessive partisanship by pundits. “Because the gatekeepers have lost all credibility in the minds of consumers, I don’t see how you reverse it.”

Others see a larger effort to slander the basic journalistic function of fact-checking. Nonpartisan websites like Snopes and Factcheck.org have found themselves maligned when they have disproved stories that had been flattering to conservatives.

“Fake news was a term specifically about people who purposely fabricated stories for clicks and revenue,” said David Mikkelson, the founder of Snopes, the myth-busting website. “Now it includes bad reporting, slanted journalism and outright propaganda. And I think we’re doing a disservice to lump all those things together.”

Journalists who work to separate fact from fiction see a dangerous conflation of stories that turn out to be wrong because of a legitimate misunderstanding with those whose clear intention is to deceive. A report, shared more than a million times on social media, that the pope had endorsed Mr. Trump was undeniably false. But was it “fake news” to report on data models that showed Hillary Clinton with overwhelming odds of winning the presidency? Are opinion articles fake if they cherry-pick facts to draw disputable conclusions?

conservatives’ appropriation of the “fake news” label is an effort to further erode the mainstream media’s claim to be a reliable and accurate source.

Conservative news media are now awash in the “fake news” condemnations

Many conservatives are pushing back at the outrage over fake news because they believe that liberals, unwilling to accept Mr. Trump’s victory, are attributing his triumph to nefarious external factors.

The right’s labeling of “fake news” evokes one of the most successful efforts by conservatives to reorient how Americans think about news media objectivity: the move by Fox News to brand its conservative-slanted coverage as “fair and balanced.” Traditionally, mainstream media outlets had thought of their own approach in those terms, viewing their coverage as strictly down the middle. Republicans often found that laughable.

“They’re trying to float anything they can find out there to discredit fact-checking,”

There are already efforts by highly partisan conservatives to claim that their fact-checking efforts are the same as those of independent outlets like Snopes, which employ research teams to dig into seemingly dubious claims.

Sean Hannity, the Fox News host, has aired “fact-checking” segments on his program. Michelle Malkin, the conservative columnist, has a web program, “Michelle Malkin Investigates,” in which she conducts her own investigative reporting.

The market in these divided times is undeniably ripe. “We now live in this fragmented media world where you can block people you disagree with. You can only be exposed to stories that make you feel good about what you want to believe,” Mr. Ziegler, the radio host, said. “Unfortunately, the truth is unpopular a lot. And a good fairy tale beats a harsh truth every time.”

“The big problem is that the culture is such that researchers spin their work in a way that tells a prettier story than what they really found,” said Jonathan Schooler, a psychologist at the University of California, Santa Barbara. “It’s almost like everyone is on steroids, and to compete you have to take steroids as well.”

Dr. Stapel published papers on the effect of power on hypocrisy, on racial stereotyping and on how advertisements affect how people view themselves. Many of his findings appeared in newspapers around the world, including The New York Times, which reported in December on his study about advertising and identity.

In a survey of more than 2,000 American psychologists scheduled to be published this year, Leslie John of Harvard Business School and two colleagues found that 70 percent had acknowledged, anonymously, to cutting some corners in reporting data. About a third said they had reported an unexpected finding as predicted from the start, and about 1 percent admitted to falsifying data.

Dr. Stapel was able to operate for so long, the committee said, in large measure because he was “lord of the data,” the only person who saw the experimental evidence that had been gathered (or fabricated). This is a widespread problem in psychology, said Jelte M. Wicherts, a psychologist at the University of Amsterdam. In a recent survey, two-thirds of Dutch research psychologists said they did not make their raw data available for other researchers to see. “This is in violation of ethical rules established in the field,” Dr. Wicherts said.

Also common is a self-serving statistical sloppiness. In an analysis published this year, Dr. Wicherts and Marjan Bakker, also at the University of Amsterdam, searched a random sample of 281 psychology papers for statistical errors. They found that about half of the papers in high-end journals contained some statistical error, and that about 15 percent of all papers had at least one error tha

t changed a reported finding — almost always in opposition to the authors’ hypothesis.

an analysis of 49 studies appearing Wednesday in the journal PLoS One, by Dr. Wicherts, Dr. Bakker and Dylan Molenaar, found that the more reluctant that scientists were to share their data, the more likely that evidence contradicted their reported findings.

“We know the general tendency of humans to draw the conclusions they want to draw — there’s a different threshold,” said Joseph P. Simmons, a psychologist at the University of Pennsylvania’s Wharton School. “With findings we want to see, we ask, ‘Can I believe this?’ With those we don’t, we ask, ‘Must I believe this?’

Bohannon had done similar work before — in 2013 he submitted a fake research paper to more than 300 open-access journals as part of a sting operation for the journal Science.

Studies like his are called “underpowered,” meaning that they aren’t designed to distinguish between a real effect and pure luck. A study with thousands of participants being measured for just a few effects is “powerful.” But one like Bohannon’s, with just five people per group being measured according to any of 18 different variables? Any number of factors unrelated to the study could cause one of the variables to fluctuate, allowing researchers to irresponsibly — but not untruthfully — state that eating chocolate while dieting helps you lose more weight.

A responsible scientist shouldn’t conduct a trial like this, Bohannon said, and a responsible scientific journal shouldn’t publish it. But Bohannon is not a nutrition scientist (he does have a PhD in molecular biology) and the International Archives of Medicine, he says, is not the most responsible journal.

According to Bohannon, the journal didn’t peer review his study or even edit it (and the study could have used an edit — “chocolate” is misspelled more than once).

“It’s the reporters,” he told The Post. “The reporters and ultimately the editors. … People who are on the health science beat need to treat it like science, and that has to come from the editors. And if you’re reporting on a scientific study you need to actually look at the paper, you need to talk to a source who has real scientific expertise.”

Bohannon said he didn’t have any ethical qualms about tricking his fellow journalists this way. “I didn’t lie to reporters, except about my name. And whenever they asked me a scientific question about the study I gave them a completely honest answer,” he said. “The whole point is that this was as bad as a lot of science that is considered ‘real’ science. It gets reported without people asking the right questions.”

more than half the respondents consider expressing views beyond a certain consensus in an academic setting quite dangerous to their career trajectory.

various people insisted that I was, essentially, lying; they simply do not believe that anyone remotely reasonable has anything to worry about.

in July I tweeted that I (as well as my Bloggingheads sparring partner Glenn Loury) have been receiving missives since May almost daily from professors living in constant fear for their career because their opinions are incompatible with the current woke playbook.

Overall I found it alarming how many of the letters sound as if they were written from Stalinist Russia or Maoist China.

A statistics professor says: I routinely discuss the fallacy of assuming that disparity implies discrimination, which is just a specific way of confusing correlation for causality. Frankly, I'm now somewhat afraid to broach these topics … since according to the new faith, disparity actually is conclusive evidence of discrimination.

The new mood has even reached medieval studies; an assistant professor reports having recently just survived an attack by a cadre of scholars who are “unspeakably mean and disingenuous once they have you in their sights,” regularly “mounting PR campaigns to get academics and grad students fired, removed from programs, expelled from scholarly groups, or simply to cease speaking.”

Being nonwhite leaves one protected in this environment only to the extent that one toes the ideological line. An assistant professor of color who cannot quite get with the program writes, “At the moment, I’m more anxious about this problem than anything else in my career,” noting that “the truth is that over the last few years, this new norm of intolerance and cult of social justice has marginalized me more than all racism I have ever faced in my life.”

The charges levied against many of these professors are rooted in a fanatical worldview, one devoted to spraying for any utterances possibly interpretable as “supremacist,” although the accusers sincerely think they have access to higher wisdom. A white professor read a passage from an interview with a well-known Black public intellectual who mentions the rap group NWA, and because few of the students knew of the group’s work at this late date, the professor parenthetically noted what the initials stand for. None of the Black students batted an eye, according to my correspondent, but a few white students demanded a humiliating public apology.

This episode represents a pattern in the letters, wherein it is white students who are “woker” than their Black classmates, neatly demonstrating the degree to which this new religion is more about virtue signaling than social justice

let’s face it: Half a dozen reports of teachers grading Black students more harshly than white students would be accepted by many as demonstrating a stain on our entire national fabric. These 150 missives stand as an articulate demonstration of something general—and deeply disturbing—as well.

A history professor reports that at his school, the administration is seriously considering setting up an anonymous reporting system for students and professors to report “bias” that they have perceived.

So no one should feign surprise or disbelief that academics write to me with great frequency to share their anxieties. In a three-week period early this summer, I counted some 150 of these messages. And what they reveal is a very rational culture of fear among those who dissent, even slightly, with the tenets of the woke left.

The result is academics living out loud only in whispers

A creative-writing instructor:

The majority of my fellow instructors and staff constantly self-censor themselves in fear of being fired for expressing the “wrong opinions.” It’s gotten to the point where many are too terrified to even like or retweet a tweet, lest it lead to some kind of disciplinary measure … They are supporters of free speech, scientific data, and healthy debate, but they are too fearful today to publicly declare such support. However, they’ll tell it to a sympathetic ear in the back corner booth of a quiet bar after two or three pints. These ideas have been reduced to lurking in the shadows now.

Some will process this as a kind of whining, supposing that all we should really be concerned about is whether people are outright dismissed. However, elsewhere a hostile work environment is considered a breach of civil rights, and as one correspondent wrote

“It isn’t just fear of firing that motivates professors and grad students to be quiet. It is a desire to have friends, to be part of a community. This is a fundamental part of human psychology. Indeed, experiments examining the effects of ostracism highlight what a powerful existential threat it is to be ignored, excluded, or rejected. This has been documented at the neurological level. Ostracism is a form of social death. It is a very potent threat.”

Especially sad is the extent to which this new Maoism can dilute the richness of a curriculum and discourage people from becoming professors at all

Very few of the people who wrote to me are of conservative political orientation. Rather, a main thread in the missives is people left-of-center wondering why, suddenly, to be anything but radical is to be treated as a retrograde heretic

It is now no longer “Why aren’t you on the left?” but “How dare you not be as left as we are.”

One professor committed the sin of “privileging the white male perspective” in giving a lecture on the philosophy of one of the Founding Fathers, even though Frederick Douglass sang that Founder’s praises. The administration tried to make him sit in a “listening circle,” in which his job was to stay silent while students explained how he had hurt them—in other words, a 21st-century-American version of a struggle session straight out of the Cultural Revolution.

The goal, they suggest, is less to eliminate all signs of a person’s existence—which tends to be impractical anyway— than to supplement critique with punishment of some kind.

One professor notes, “Even with tenure and authority, I worry that students could file spurious Title IX complaints … or that students could boycott me or remove me as Chair.”

From the same well is this same professor finding that the gay men in his class had no problem with his assigning a book with a gay slur in its title, a layered, ironic title for a book taking issue with traditional concepts of masculinity—but that a group of straight white women did, and reported him to his superiors.

degree of sheer worry among the people

"The United States has seen its relative share of global S&T [science and technology] activity flatten or shrink, even as its absolute activity levels kept rising," the authors wrote in the report. "As more countries around the world develop R&D and human capital infrastructure to sustain and compete in a knowledge-oriented economy, the United States is playing a less dominant role in many areas of S&E [science and engineering] activity."

"Research is now a truly global enterprise. Opportunities are everywhere and humanity's collective knowledge is growing exponentially," Souvaine said. "To remain a leader, we need to tap into our American 'can do' spirit and recommit to strong partnerships among government, universities and industry that have been the hallmarks of our success. I believe we should react with excitement, not fear, because we are well positioned to compete, collaborate and thrive."

This means that, even under the best circumstances, scientists can’t directly test what the results of a given gun policy are. The best you can do is to compare what was happening in a state before and after a policy was enacted, or to compare two different states, one that has the policy and one that doesn’t. And that’s a pretty inexact way of working.

Add in enough assumptions, and you can eventually come up with an estimate. But is the estimate correct? Is it even close to reality? That’s a hard question to answer, because the assumptions you made—the correlations you drew between cause and effect, what you know and what you assume to be true because of that—might be totally wrong.

It’s hard to tease apart the effect of one specific change, compared to the effects of other things that could be happening at the same time.

This process of taking the observational data we do have and then running it through a filter of assumptions plays out in the real world in the form of statistical modeling. When the NAS report says that nobody yet knows whether more guns lead to more crime, or less crime, what they mean is that the models and the assumptions built into those models are all still proving to be pretty weak.

From either side of the debate, he said, scientists continue to produce wildly different conclusions using the same data. On either side, small shifts in the assumptions lead the models to produce different results. Both factions continue to choose sets of assumptions that aren’t terribly logical. It’s as if you decided that anybody with blue shoes probably had a belly-button piercing. There’s not really a good reason for making that correlation. And if you change the assumption—actually, belly-button piercings are more common in people who wear green shoes—you end up with completely different results.

The Intergovernmental Panel on Climate Change (IPCC) produces these big reports periodically, which analyze lots of individual papers. In essence, they’re looking at lots of trees and trying to paint you a picture of the forest. IPCC reports are available for free online, you can go and read them yourself. When you do, you’ll notice something interesting about the way that the reports present results. The IPCC never says, “Because we burned fossil fuels and emitted carbon dioxide into the atmosphere then the Earth will warm by x degrees.” Instead, those reports present a range of possible outcomes … for everything. Depending on the different models used, different scenarios presented, and the different assumptions made, the temperature of the Earth might increase by anywhere between 1.5 and 4.5 degrees Celsius.

What you’re left with is an environment where it’s really easy to prove that your colleague’s results are probably wrong, and it’s easy for him to prove that yours are probably wrong. But it’s not easy for either of you to make a compelling case for why you’re right.

Statistical modeling isn’t unique to gun research. It just happens to be particularly messy in this field. Scientists who study other topics have done a better job of using stronger assumptions and of building models that can’t be upended by changing one small, seemingly randomly chosen detail. It’s not that, in these other fields, there’s only one model being used, or even that all the different models produce the exact same results. But the models are stronger and, more importantly, the scientists do a better job of presenting the differences between models and drawing meaning from them.

“Climate change is one of the rare scientific literatures that has actually faced up to this,” Charles Manski said. What he means is that, when scientists model climate change, they don’t expect to produce exact, to-the-decimal-point answers.

“It’s been a complete waste of time, because we can’t validate one model versus another,” Pepper said. Most likely, he thinks that all of them are wrong. For instance, all the models he’s seen assume that a law will affect every state in the same way, and every person within that state in the same way. “But if you think about it, that’s just nonsensical,” he said.

On the one hand, that leaves politicians in a bit of a lurch. The response you might mount to counteract a 1.5 degree increase in global average temperature is pretty different from the response you’d have to 4.5 degrees. On the other hand, the range does tell us something valuable: the temperature is increasing.

The problem with this is that it flies in the face of what most of us expect science to do for public policy. Politics is inherently biased, right? The solutions that people come up with are driven by their ideologies. Science is supposed to cut that Gordian Knot. It’s supposed to lay the evidence down on the table and impartially determine who is right and who is wrong.

Manski and Pepper say that this is where we need to rethink what we expect science to do. Science, they say, isn’t here to stop all political debate in its tracks. In a situation like this, it simply can’t provide a detailed enough answer to do that—not unless you’re comfortable with detailed answers that are easily called into question and disproven by somebody else with a detailed answer.

Instead, science can reliably produce a range of possible outcomes, but it’s still up to the politicians (and, by extension, up to us) to hash out compromises between wildly differing values on controversial subjects. When it comes to complex social issues like gun ownership and gun violence, science doesn’t mean you get to blow off your political opponents and stake a claim on truth. Chances are, the closest we can get to the truth is a range that encompasses the beliefs of many different groups.

MTurk is a fantastic tool available to quickly collect human subjects data. It pulls from a massive group of people looking to complete small tasks for small amounts of money. So for 5 cents per survey, I collected 100 responses to a short survey from American MTurk Workers. It asked only 3 questions:Please define astrology in 25 words or less.Do you believe astrology to be scientific? (using the same scale as the NSF study)What is your highest level of education completed? (using the same scale as the NSF study)

Among those that correctly identified astrology as astrology, only 13.5% found it “pretty scientific” or “very scientific”. Only 1 person said it was “very scientific.” Among those that identified astrology as astronomy, the field was overwhelmingly seen as scientific, exactly as I expected. This is the true driver of the NSF report findings

A landmark Johns Hopkins study in 1990 found that lawyers were 3.6 times as likely as non-lawyers to suffer from depression, putting them at greater risk than people in any other occupation. In December, Yale Law School released a study that said 70 percent of its students were affected by mental health issues.

From 1999 to 2007, lawyers were 54 percent more likely to commit suicide than people in other profession

the job requires an unhealthy degree of cynicism. “Research shows that an optimistic outlook is good for your mental health,” said Patricia Spataro, director of the New York State Lawyer Assistance Program, a resource for attorneys with mental health concerns. “But lawyers are trained to always look for the worst-case scenario. They benefit more from being pessimistic, and that takes a toll.”

the pressure to be hired by a big-name firm is so strongly ingrained in law school culture, one George Washington University student said, that even those who enroll with the intention of performing public service often find themselves redirected.

“It’s a very real pressure in law school,” Helen Clemens, the law student, said. “It comes from all kinds of avenues, but mostly I would say it just comes from the people surrounding you. If everyone is talking about leaders from our school who have gotten jobs at a really prestigious firm, the assumption is that we all should be trying to work at a similar place.”