Performa, the New York performance biennial thats now in its 16th year, has developed a reputation for forcing artists into unfamiliar territory. Indeed, for many artists, Performa commissions are their first opportunities to arrange events, which presents unique challenges.

The learning curve can be steep, and artists often have to learn on the fly.For many artists, the unpredictability is precisely the appeal: the chance to take a big risk can be a transformative opportunity.

As Performa comes to a close this weekend, we spoke with three artists doing live events for the first time to see what they learned from their experiences.

Paul Pfeiffer, University of Georgia Redcoat Band Live (2019). Photo: Paula Court.

When Paul Pfeiffer planned to bring the University of Georgias marching band to New York for his Performa outing, he envisioned them playing in an empty stadium. The original idea was to recontextualize how the band is perceived (they usually perform at football games)by placing them in an arena with no athletes in sight.

Pfeiffereven had one of the citys major stadiums lined up for the performance. But late in the process, the NBA swooped in and outbid the artist for the venue.

The irony that the NBA quashed his performancewhich emphasizes the corporate spectacle of professional sportswas not lost onPfeiffer. But it still left him with a problem to solve: where would the 50-member band play now? Eventually, he locked down the historic Apollo Theater in Harlem, which opened up new possibilities, Pfeiffer explains.

The band is nothing if not a machine; they are constantly on script, the artist says. To turn them into performers in a different context was a total unknown. And to an extent beyond what I anticipated, they performed their roles as hype generators in an amazing way. The audience had access to them, not just as a group, but individually. There were interactions happening that I did not expect. Individual personalities of the band members came out.

Paul Pfeiffer, University of Georgia Redcoat Band Live (2019). Photo: Paula Court.

The change also spurred Pfeiffer to expand the piece: while some members of the band played in New York, those who didnt make the trip performedsimultaneously at the vacant University of Georgia stadium. Their performance was then live-streamed at the Apollo.

The whole thing was an improvised negotiation happening in real-time, Pfeiffer says.

Theres a grey area between the notion that performance is something that happens on a stage, and a wider idea of performance as all human behavior, he adds. Thats absolutely fascinating to me. Thats what makes performance so exciting and pertinent right now. As an artist, thats where the action is.

Installation view of Tara Subkoffs DEEPFAKE, 2019. Courtesy of the Hole.

It was a very personal piece, says Tara Subkoff of her Performa commission, Deepfake.

An exploration of chaos theory and the way in which our lives are shaped by the choices we make moment-to-moment, the work was simultaneously staged at four different locations, which forced viewers to pick just one perspective on the sprawling event. Dancers moved to a capella renditions of a Nina Simone song at two separate churches uptown, while in Brooklyn, another group performed a water ballet.

And at the Hole, the gallery where Subkoff currently has a solo show, she staged a three-ring circus with jugglers, a mime, a magician, and a contortionist. As they pranced about,the artist chased her daughter around in a circle while her cousin, a tap dancer, performed nearby.

Subkoff didnt plan on being in the piece herself. (The one time she starred in her own work was, according to her, the worst piece shes ever done. It was worse than the time I sang karaoke in Tokyo and cleared the room, she says.) But her three-year-old daughter insisted on being part of the work, and so Subkoff decided to participate too.

It was a comedic version of what its like to be a female in our society, trying to be all these things to all these people at the same time, Subkoff says of the performance. As a single mom, I feel like Im always running in circles and juggling.

va Mag, Stand Up, still (2015). Courtesy of the artist.

Theres a Swedish expression (kpa grisen i scken, which translates roughly tobuy a pig in a sack) thats used to describe a situation in which you agree to do something without really knowing what it is.

va Mag, a Swedish sculptor and performance artist, says Performa was her pig in a sack.

It was a challenge for me to understand what this is, who the artists are, and how I fit in, Mag says. Im doing a project I havent done before in a new environment. I had to figure out how to get the help I needed. I had no idea what the outcome was going to be.

As a performer, Mag explains, you have to learn not to be totally nervous and freeze, but actually trust yourself and go on.

Mags work,Dead Matter Moves, is a durational performance that took place across six nights at the historic Judson Memorial Church. It features 10 performers erecting lifesize figures of clay and stuffing them into patchwork skins made of found textiles.

Mag says that talking with Performa curator Kathy Noble played a big part in shaping the piece, as did working with a production teamsomething shes never done before.

They helped with small details like scheduling throughout the day, and setting up the space for me to totally develop myself and investigate my techniques, says the artist.They pushed me to do more and to grow. That is really Americanyou can dream big!

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I Had No Idea What the Outcome Was Going to Be: What Three Non-Performance Artists Learned by Doing Their First Performa Commissions - artnet News

Narcissists, like sharks, get a bad press. Both are generally seen as menacing, negative forces to be feared and avoided.

But as any biologist will tell you, sharks play a vital role in the marine ecosystem. And it may be that narcissists also have a necessary part to play in human society.

This, of course, goes against the widely accepted perception of personality traits that it is good to be agreeable and outgoing and bad to be narcissistic.

After all, narcissistic people engage in risky behavior, hold an unrealistic superior view of themselves, are overconfident, show little empathy for others, and have little shame or guilt. But if narcissism is so socially toxic, why does it persist and why is it said to be on the rise in modern societies?

The answer is that human nature is complex. And while narcissism is often associated with dark traits like psychopathy and sadism, it also has aspects which are widely considered to be positive, such as extroversion and confidence.

In saying this, I do not mean to defend or excuse the worst examples of narcissistic behavior. Instead, I want to highlight the potentially beneficial elements which could then enable society to harness the positive potential of dark personalities while also curtailing their potential for harm.

There are two main types of narcissism: grandiose and vulnerable. Vulnerable narcissists are likely to be more defensive and view the behavior of others as hostile, whereas grandiose narcissists usually have an over inflated sense of importance and a preoccupation with status and power.

The results from our studies (on the personality trait of sub-clinical narcissism, not narcissistic personality disorder) show that grandiose narcissism correlates with highly positive components of mental toughness. These include confidence and a focus on achieving goals, which help protect against symptoms of depression and stress.

The association between narcissism and mental toughness may help to explain the variation in symptoms of depression in society. If a person is more mentally tough, they are likely to embrace challenges head on, rather than viewing them as a hurdle.

So while not all dimensions of narcissism are good, certain aspects can lead to positive outcomes. And a little bit of narcissism can be a useful tool when faced with stressful situations, providing that extra bit of mental toughness we need to get through.

Its a bit like having the ability to run when walking is not enough. The idea is that people need to be flexible. They need to walk when thats all that is required, but run when thats whats necessary. Likewise, the ability to call on a little bit of narcissism when faced with a challenge, socially or professionally, is a useful skill.

Recent research from our lab suggests that narcissism may act as a bridge connecting the dark (anti-social) and light (pro-social) sides of the human personality. Put simply, individuals can cross that bridge to use their dark traits when facing a challenge, and pro-social characteristics when in a safe environment.

Our work suggests that instead of perceiving human personality as a dichotomy (narcissistic versus agreeable), we should treat it as a constantly changing spectrum.

It is not about promoting grandiosity over healthy self-esteem and modesty. Instead it is about promoting diversity of people and ideas by advocating that dark traits, such as narcissism, should not be seen as either good or bad. They are products of evolution, and expressions of human nature that may be beneficial or harmful depending on the context.

This may help to reduce the marginalization of individuals that score high on dark traits, and work out how best to cultivate some manifestations of these traits, while discouraging others, for the collective good.

It is too simplistic to say that personality traits like narcissism, which help individual empowerment, are socially toxic. People are trying to adapt, survive, and succeed in a social, political, and economic environment that promotes the self-made man or woman, and if they exhibit antagonistic traits such as narcissism, they receive negative attention. Yet grandiose narcissism may be the key to protecting individuals from such needless pressure.

Nor do I think there are individuals who live without narcissism. In common with other psychological traits, it exists on a spectrum, with some individuals scoring higher than others.

Elsewhere in the natural world, a human fear and distrust of sharks has led to a widespread attitude of us versus them. After the movie Jaws was released, according to one conservationist there was a collective testosterone rush which led to thousands of anglers targeting and killing sharks off the American coast.

Shark numbers have dropped dramatically (by up to 92%) in the past half century. So just as we are starting to understand the importance of sharks for the marine ecosystem, we have run out of sharks to study.

We should not let narcissists be similarly marginalized just because we dont understand them. Instead of demonizing parts of our personality, we need to celebrate all of its aspects and work out how best to use them, for our own benefit and the benefit of society.

This article was originally published on The Conversation by Kostas Papageorgiou. Read the original article here.

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Psychologists say there are 2 types of narcissists: Which one are you? - Inverse

Taking the broadest cultural and political view, the past two weeks or so have provided a solid, sobering representation of where women stand in America right now.

All of us are passing through a time of triumph and trial, obviously. Proof of this is playing out across TV in examples ranging from moving to enraging to outright depressing.

But in this context Im mostly speaking about watching women in three different settings playing out within the same general time frame: the public hearings portion of Congress impeachment inquiry, Wednesdays Democratic debates in Atlanta, and a disheartening parable dispatched from the Mamanuca Islands of Fiji.

That third mention refers to CBS' Survivor: Island of the Idols, unscripted entertainment edited to fit whatever narrative producers deem to be most provocative. The 39th season is embroiled in a controversy involving several women being subjected to unwanted touching by castaway Dan Spilo, a Hollywood talent manager .

Dan is still part of the game whereas Kellee Kim, the contestant who raised her voice about Spilos groping both directly to him and to other women, ended up being voted off the island. Kim's confessionals about the experience are raw and charged; at one point she visibly tears up, and a producer, speaking off camera, lets her know that if she's says the word they'll step in.

With $1 million on the line, however, taking such action would not have been without penalty. Then again, her trust that the tribe's other women would stand with her was misplaced. Several of them used her candor with them against her to blindside her, saying "me too" to her face and then putting her on the chopping block at Tribal Council.

"Survivor executive producer and host Jeff Probst likes to remind people that the game plays out as a microcosm of society. Its also a program run by producers who have an obligation to ensure the people in their charge feel safe. The first half of the Nov. 13 back-to-back episodes actually includes an onscreen message that Spilo received an official warning from producers.

Given everything Probst and Survivor producers knew about Spilos behavior before Kim and the man who defended her, Jamal Shipman, were voted off, the general consensus from passionate fans is that Spilo should have been ousted from the game instead of Kim, the woman whose boundaries he violated. (Shipman, it must be said, made an unrelated strategic mistake that doomed him. His eloquent, empathetic defense of Kim still stands.)

But this is Survivor; this is television. As Shipman told Entertainment Weekly in his exit interview, the understanding is that once you set foot on the island, the game is in play and barring a medical emergency of which the show has had its share there is no pause or reset button aside from the ones producers toss in as part of the game.

The consequences for a player asking for production to get involved are monumental, Shipman said. . . . Therefore, I think it is a judgment call that only the producers can make. They are monitoring the camp 24/7. They need to be the ones to decide when to prioritize the safety of the players. They should recognize that we are in a situation where we cannot advocate for ourselves without the fear of compromising our endgame.

I am not a regular Survivor viewer. In fact, it only occurred to me to watch the Nov. 13 and 20 episodes when it came up in a number of conversations. My friend and colleague Andy Dehnarts rapier-pointed critique of the situation, by the way, is a must-read for anyone seeking a concise breakdown of the ethical quandaries this development presents.

And he concisely spells out one of the main reasons for the general outcry among viewers sensitive to a womans right to have her personal and physical boundaries respected:

At Tribal Council, Probst was more concerned about making a Survivor Cultural Touchstone Moment than just being honest and open about what he already knew. For Probst to get irritated with Dan while simultaneously pretending like he had no idea what was going on was quite the choice.

The Nov. 13 Survivor is fascinating to watch now, in the wake of five days worth of impeachment inquiry testimony and Wednesdays debate, because of what events of the day prove about the Survivor theory of human behavior and society.

The common denominators in all three events the reality show, the hearings and to some degree, the debate stem from our feelings concerning right or wrong, and consequence, with women playing key roles at each juncture.

Even more starkly, it shows why movements like #MeToo and the struggle for gender inequality are not blown out of proportion or the latest social justice fever to hit the entertainment industry. And they also remind us that our problems are far from solved.

The fifth Democratic primary face-off,held at Tyler Perry Studios in Atlanta, Georgia, was moderated by four women, MSNBCs Rachel Maddow and Andrea Mitchell, NBC White House correspondent Kristen Welker, and Ashley Parker, White House reporter for The Washington Post, which co-hosted the event along with MSNBC.

Among the topics candidates fielded on Wednesday were substantive exchanges about abortion rights, family leave, and gender inequity lines of questioning underrepresented or completely omitted in previous debates.

Out of the 10 contenders on the stage, three out of the four women shone brightest. Sen. Elizabeth Warren was the popular winner in post-debate assessments, but Sen. Kamala Harris also received her share of upvotes.

Sen. Amy Klobuchar performed better than she ever has, while also distinguishing herself by making a reasonable and fai22r stand for gender equality. Referring to a comment Klobuchar previously made about the double standard of Mayor Pete Buttigieg being taken seriously as a candidate given his youth and experience relative to her own, Mitchell asked her to clarify what she meant.

Pete is qualified to be up on this stage, and I am honored to be standing next to him. But what I said is true: Women are held to a higher standard, she told Mitchell Otherwise we could play a game called name your favorite woman president, which we cant do because it has all been men.

On the other hand, Hawaii Rep. Tulsi Gabbard attempted to reprise her attack on Harris and was smacked down badly, and Vice President Joe Bidens second greatest gaffe of the night involved erasing Harris career achievements in attempting to burnish his own by claiming that his strong support among black voters is because they know me, they know who I am. Three former chairs of the black caucus, the only African-American woman that's ever been elected to the United States Senate

No, thats not true, Harris said, stepping in along with Cory Booker. The other one is here.

At the end of the night, the general if unscientific consensus is that Maddow, Mitchell, Welker, and Parker kept the debate running smoothly, allowing candidates to fully deliver their answers while keeping them within their allotted time limits. Maddow, in the post-show, cited the flawless set-up at Tyler Perry Studios, which she says ensured that everyone heard one another and reduced the frequency of outburst and cross-talk

She also opined that the perceived toughness of her fellow moderators may have had influenced the better behavior this time around, jokingly referring to her NBC co-workers Welker and Mitchell as people you dont want to cross "in a dark alley, with no one around you."

The candidates, in turn, refrained from squabbling over one another. For the most part.

The presumption that women would simply run things better is lovely, and I support it. Its also facile. To wit: on "Survivor," two of the other women on the island with Kim played their discomfort with Spilo as a strategy, which paints a repulsive picture in several respects.

At the debate, Welker tried some gamesmanship of her own when she set up Harris to take a shot at Buttigieg for his bungled attempts to inflate his support among African Americans. But the moderator didnt go into specifics of what those missteps are basically putting the weight on Harris to do the work for her and viewers at home and somehow not look like a heel.

Harris strategically pivoted away from the trap, likely aware of the potential optics of a black woman going on the offensive against nice Mayor Pete.

And while debate moved quickly and covered a lot of ground, it sill fell short on depth and substance. LGBTQ issues were barely discussed; the topic of violence and discrimination against transgender Americans did not come up at all.

And yet, taking into account that it came at the end of 10 hours of live political coverage, women got the job done and did it well.

Women, too, put their careers on the line in service of the impeachment inquiry. A week before Wednesdays debates, Former Ukraine Ambassador Marie Yovanovitch appeared before the House Intelligence Committee, and I imagine her testimony might have hit anyone smarting from the events of that Nov. 13 Survivor episode differently than other viewers.

Yovanovitch is a story of a career diplomat who did her job well and was fully versed in the players behind corruption in the Ukraine, and as a reward for doing her job, was pushed out of her position and smeared by her former boss as she testified. (She was sidelined and silenced, in other words. You know, like one of those jurors made to silently witness Tribal Council from the sidelines.)

The unblinking cameras showed America a composed, capable witness who remained even-keeled throughout her testimony, as did Jennifer Williams, an aide to Vice President Mike Pence who listened in on Trumps July 25 phone call to Ukraine PresidentVolodymyr Zelensky and testified on Day Three, or Tuesday of this week, that she found it unusual.

But two other women who appeared as witnesses this week packed more perceptual punch, in part due to how they were scheduled. From most accounts the inquirys climax arrived on Wednesday of this week when EU Ambassador Gordon Sondland sauntered into the Capitol in the way of all entitled rich men who pay their way into positions theyre not qualified to perform.

Sondland, who bought his diplomatic position by writing a $1 million check to Trumps presidential inaugural committee, joked and smiled his way through many hours of questions by Democrats and Republicans on the House Intelligence Committee after kicking off the proceedings with this bombshell:

I know that members of this committee have frequently framed these complicated issues in the form of a simple question: Was there a `quid pro quo? As I testified previously, with regard to the requested White House call and White House meeting, the answer is yes.

Certainly it was a tremendous performance designed for the cameras. His resting grin, in particular, spoke volumes: it was that of a man who knew he could say or do anything without suffering any significant penalty or alteration to his lifestyle because of it. But his role was mainly that of ending a flimsy argument; the rest was artful dodging and schtick.

The more thankless duty fell to the woman who followed Sondland on the schedule, deputy assistant secretary of Defense Laura Cooper, who dispelled the notion that Ukraine didnt know that funds for military assistance were being held up. She confirmed that, indeed, government workers asked about it on the same day as Trumps famous phone call.

In contrast to Sondland, Cooper was not afforded the luxury of engaging in performative hamminess, because she is a career servant; as far as we know she doesnt have a cushion of millions to fall back on if shes fired. The viewer saw a serious woman who chose her words very carefully and let GOP attacks roll off on her when they came her way.

Besides, it was not she who reminded viewers of the inequalities that exist within government, or this situation, or workplaces in general. That fell to Thursdays fact witness, Dr. Fiona Hill, the former top National Security Council official for Europe and Russia.

Questioned about her reaction to Sondland cutting her and her department out of the loop (which includes John Bolton) in terms of their dealings with Ukraine, she admitted having a couple of testy encounters with him.

One of those was in June 18 when I actually said to him, Who put you in charge of Ukraine? Ill admit I was a bit rude, but thats when he told me the president, which shut me up, she said. What she said next speaks to something women face in every setting.

I was actually, to be honest, angry with him, she said. And you know, I hate to say it, but often when women show anger its not fully appreciated. Its often pushed onto emotional issues, perhaps, or deflected onto other people.

She continued, And what I was angry about was that he wasnt coordinating with us. I now actually realize, having listened to his deposition, that he was absolutely right. That he wasnt coordinating with us because we werent doing the same thing that he was doing."

With this, she calmly delivered the coup de grace by characterizing Sondlands actions as being involved in a domestic political errand. And we were being involved in national security foreign policy. And those two things had just diverged. So he was correct . . . And I did say to him, Ambassador Sondland, Gordon, I think this is all going to blow up. And here we are.

Recency bias, that phenomenon of easily recalling the latest events in a timeline with most accuracy, can be a wonderful thing . . . when and if it works in your favor, that is. The problem always is that the latest chapter in a saga doesnt tell the whole tale, which is why researchers and other types of chroniclers caution us about its influence.

Hill, though, gave a hell of a finale, coming across as unshakable even in the face of attempts to besmirch her reputation, even chastising members of the GOP without calling them out by name or party for perpetuating the debunked conspiracy that Ukraine meddled in the 2016 elections, not Russia.

Yet I am left to wonder, at the end of it all, what will happen to this steely survivor and others like her.

If the Senate embarks upon the trial portion of the impeachment, the focus will not be on weighing the evidence but tearing apart the people who submitted it to the public. Senate Majority Leader Mitch McConnell and the rest of the Republicans got quite a preview of what to expect from Hill, Cooper, Williams, and Yovanovitch.

On the other hand, the hearing also served as a coming-out party for Republican New York Rep. Elise Stefanik, who tag teamed with Ohio GOP Congressman Jim Jordan in attacking witnesses.

Politics is a messy, bloody business, even more so when our diplomatic efforts become overtly politicized. Typically, though, what alarms people who consume current events mainly through TV news are acts that have already happened, actions that have been discussed in the halls of Congress or occur in places far away.

The real-time collision of political theater and unscripted reality showbiz adds a new kind of anxiety to what were seeing, in that the manufactured product has the misfortune of auguring the truth of how things are. Four women did a better job of moderating the latest presidential debate than any of the predecessors, yet the debate was the least watched so far, with only 6.6 million viewers tuning in.

Hill's testimony was strong, and her unflappable comportment read brilliantly on live TV. A few hours later, Sean Hannity got an early start on the campaign to discredit Hill on Thursday's installment of his Fox News primetime program.

And some Survivor viewers are upset because they expected an artificial society formed and endured for 39 days, overseen by multiple witnesses behind many cameras, would mete out justice in ways the real world rarely does. The producers saw everything, and we saw enough. Even so, the alleged perpetrator is still on the road to a $1 million payday.

Its super upsetting because its like you cant do anything about it, Kim says on the show. There are always consequences for standing up. This happens in real life, in work settings, in school. You cant say anything because its going to affect your upward trajectory. Its going to affect how people look at you.

Her anger, I think, has not been fully appreciated it. But I do hope what happened to her serves as a warning, perhaps, to prepare for whatever obfuscating storm is coming after these weeks of hard transparency, transmitted via live television.

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From Survivor to D.C., women are showing up strong on TV, but does patriarchal America care? - Salon

In anticipation of Lt. Col. Alexander Vindmans recent public testimony in the Houses impeachment inquiry, the Fox News host Laura Ingraham and a guest concocted an insulting fantasy on her show: the idea that Colonel Vindman might be a Ukrainian spy.

It may have shocked a lot of Americans that Fox News televangelists and establishment conservatives like John Yoo are spinning the narrative of the courageous Colonel Vindman a man who put his countrys interests ahead of his own into one that suggests, as an immigrant, he wasnt loyal to the United States. But as a former Fox News opinion talk-show guest host and contributor for 14 years, it didnt shock me.

I can explain the art and purpose behind throwing a Purple Heart veteran under the Fox News bus. First, we must talk about narratives. In my time at Fox News, narratives were weapons of mass emotional manipulation, what the Nobel laureate Robert J. Shiller defines in Narrative Economics as contagious stories as he put it in a paper of the same name, a simple story or easily expressed explanation of events that many people want to bring up in conversation or on news or social media because it can be used to stimulate the concerns or emotions of others, and/or because it appears to advance self-interest. One recent report said that we find information or misinformation 22 times more memorable in narrative form.

Theres little in this world that has the emotional manipulative power of a good tribalized us versus them narrative. Its a contagion, and thanks to social media, or participatory propaganda, highly viral.

The Fox News counternarrative model is as simple as it is cunning. The segment producers job is to get the answers to two questions: What is the most emotionally engaging story we have right now (in 2019, thats the most recent damaging attack House impeachment hearings on President Trump). The next question is, how do we construct a counternarrative that includes as many existing other believable meta-narratives as possible?

The hunt for the killer narrative starts with the Morning Memo to the producers. It shares the interpretation from the vice president of news of the highest-trending articles on Foxnews.com and Drudge. In the old days, the memo from the C.E.O. Roger Ailes dictated the narratives of the day. The next move is to get a few Fox News contributor regulars elected officials and paid pundits not just to deliver the new counternarrative but also to wrap it inside an existing or new meta-narrative.

What do the ratings tell the producers are the most engaging meta-narratives for the over 80 million Fox News viewers on all digital platforms?

Conspiracy theories.

Why do people love conspiracy stories? Its human behavior. Being in on a good conspiracy theory makes you feel like you know something the other guy in this case, any liberal does not. The emotional payoff from being on the inside of a conspiracy is a self-esteem jolt that makes you feel smarter than your tribal foe and keeps your eyeballs glued to screens television, laptops, tablets, cellphones where the network makes money from advertising.

The Vindman coverage followed the Fox News conspiracy segment playbook perfectly. In the days after Fox News produced it, the spy tale was distributed by other dealers of conspiracy theory. Representative Matt Gaetz of Florida tweeted that Donald Trump is innocent. The deep state is guilty. The congressmans message was amplified by an account tied to the online conspiracy movement QAnon to 160,000 of its followers as well as posted on a QAnon Facebook page.

If some of those who consumed the story go back to the original source, Fox, its more business for the network.

Every successful Fox News segment producer has the conspiracy script down cold. These segments work best when the proof of a conspiracy against a tribal leader in this case the Republican president makes the viewer feel under attack as well. It elevates the fight-or-flight juices. And it helps when a proposed conservative thought leader mixes in the meta-narrative to the effect that we are victimized again by the condescending Beltway elites.

Weaponized and tribalized political video narratives in the hands of Fox News producers can become something like drug-abuse epidemics keeping addicts of that conspiracy theory high and coming back for more.

Believing in conspiracy theories is a psychological construct for people to take back some semblance of control in their lives. It inflates their sense of importance. It makes them feel they have access to special knowledge that the rest of the world is too blind, too dumb or too corrupt to understand.

And that is why they wrote Colonel Vindman into the wrong side of a spy novel.

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Why Fox News Slimed a Purple Heart Recipient - The New York Times

NOVEMBER 21, 2019

THE PINNACLE OF human civilization is junk food. More than any pyramid or tomb, it represents the apex of how humanity has mastered itself and its innate desires. It combines three of the rarest elements in nature salt, fat, and sugar in an affordable, easy to consume package. It preys on our primal instincts to seek out these elements and covet them at any cost, behaviors burned into the core of our minds from a time when our ancestors had to fight to attain even tiny amounts of them. Add to that corporations whose sole purpose is to exploit that instinct, which pump untold amounts of money into research, refinement, and marketing, and we are nearly powerless in the face of it. Even compared to the realms of politics, science, and academia, there may be no entities on earth who understand human behavior better.

Now consider the idea of a corporation that has tapped into emotional desires just as deeply if you could exist as a dual consciousness, one that experienced the happy successes of life while the other existed in gray mediocrity, would you take it? If they promised to reshape your waking reality in order to increase your unconscious productivity, could you still enjoy it with the terrible knowledge that you are living a lie? In the newest novel from Shane Jones, Vincent and Alice and Alice from Tyrant Books, the titular Vincent is confronted with this very question. Rather than being offered a red pill or a blue pill, Vincent has a different choice: the unremarkable pain of real life, or the emotional equivalent of a cheeseburger and fries exploding in his brain every second of the day.

On the day I start reading the novel, my manager informs me that Im participating in an all-day seminar for Process Improvement and Collaborative Governance on Friday. Its mandatory. If I had the choice to minimize the time spent on it, I would, but I get a feeling I dont have a choice in the matter. I usually try to ignore coincidences and apophenia in my life, but I cant help but notice the parallels between the book and this inane task.

Shane Jones is a well-known name due to the success and controversy of his debut novel, Light Boxes, released in 2010 by Penguin Books. It follows the surrealist tale of a small towns war against February, who exists both as a season and a person, and which has cursed them with an endless winter. It is a cathartic story that blends a frontier landscape with sensual elements, tragedy highlighted by sharpness of mint, depression softened by the sweet lull of flowers. In Crystal Eaters (Two Dollar Radio, 2014), Jones creates a village being physically encroached on by a city, following the story of Remy and her family as they deal with the literally impending doom. The characters live their lives imprisoned by the properties of different colored crystals, some hewn from the earth in a desperate attempt to improve the crystal count inside them. What happens here are the choices of the individual: either to scratch, dig, and claw at an unyielding, inorganic surface, desperate to connect despite the damage to the physical body, or to remain frozen inside of a quartz-tinted life. Both action and inaction result in catastrophic consequences, and Jones paints this world for us in a mythological, yet utterly real, fashion.

While Light Boxes and Crystal Eaters could be set in the past, present, or distant future, Vincent and Alice and Alice takes place in a time that could be solidly defined as the present and near-future, much closer in relation to our own reality than his previous works. The timeline starts in 2017 and stretches to 2037, and Vincents world is a landscape dominated by Walmart rather than woodland. He has an office job with the State, a job that seems to involve the same trappings as our own, in which co-worker birthdays and reams of copier paper make up the minutiae of the day. There is Elderly, an old man who lives in a car on his street, who for all intents and purposes seems to be Vincents best friend. Between Vincents mediocrity and Elderlys eccentric nature, they seem to balance each other out, neither conflicting nor agreeing on anything in particular. In a bland existence, Elderly could be considered Vincents tether to reality, a reminder that chaos exists as a part of life. But of course, these are just ancillary details to the person that consumes Vincents mind, despite being physically absent: Alice.

When we meet Vincent, he is dominated (in every sense of the word) by thoughts of his ex-wife, Alice. No matter where he goes or whom he interacts with, he is followed by permutations of Alice, which drift back and forth from the melancholy to the obsessive. Apparently, this is a pattern of behavior that has always been a part of him:

Alice said I was incapable of living in reality. She said I spent too much time in my head, which is impossible because my reality was Alice, planning our days together. We spent weekends in bed eating sushi, reading the first ten pages of novels, binging shows, sleeping to no clock, no rules, no guidelines, no sense of time. If my imagination did wander, it always included her.

Jones writes Vincent as a man diving head first into just about anything, even adopting an old dog on a whim, to get away from the pain of Alices physical absence in his life. While outwardly composed, Vincent is flailing, searching for meaning in a life where its focal point has got up and left.

One of the people to reach out and steady Vincents hand comes from within his workplace, when he is scheduled to meet with an enigmatic figure named Dorian Blood. While the average person would already be sensing the ominous overtones, Vincent attends the meeting anyway. There, Dorian a square-jawed yet erratic executive type gives him the option of participating in PER, a new kind of mental strategy designed to increase worker productivity. Vincent is promised with the reward of the gate, which, when entered, will turn him into a split consciousness, physically toiling while mentally rejoicing. He will still be working at his dead-end job, but will experience a new simultaneous reality in which anything is possible. Even in the context of this review, you can probably guess that Vincent agrees to do this. With language clouded in the kind of obfuscation reserved for New Age seminars and corporate retreats, Vincent is given the instructions to reach the gate, as well as rules for engagement with it. I recognize this language from my own workplace, where I am pelted with acronyms and esoteric phrases as solutions to problems: Post Deltas, HRO, KANO, EBP, DMAIC. I am told to focus on innovation, to adhere to the white belt method, to identify problem statements and vision statements. I still dont understand how this fits into my job.

As Vincent works with the Patrick Batemanesque Dorian, he is told to learn and adhere to the rules of the gate at all costs:

1. Do not confront the gate about its plausibility.

2. Do not question the humans inside the gate.

3. Do not control the gate.

4. Let the gate guide you.

5. Do not attempt to escape from the gate.

6. Documenting the gate by video or photo is prohibited.

When Vincent asks, How will I know whats real and what isnt? Dorian replies, We get that one a lot. But at this stage in your life, does it matter? In our own lives, we have to make so many decisions and sacrifices, which the PER system is satirizing. Do we go out after work, or stare at a different screen at home? As we get older, the future begins to loom over us as a cold reality instead of a bright tomorrow. The days become obstacles to get through instead of opportunities, our precious lives poured into the forge of capitalism to create a solid plan a future we can have, hold, depend on in other words, an impossible thing. Every day we are confronted with news of climate change and the unrest that has resulted because of it. The picture only becomes grimmer with each passing day, as resources dwindle and small collapses nick away at the foundations of the world. Its enough to make fantasy seem like an attractive alternative, even compared to connecting with others. Vincent says of Alice, From her point of view the reason our marriage ended wasnt because I couldnt fulfill her sexually, but I stopped connecting. She said I wasnt there with her mentally because I was either commuting to work, at work, coming home from work, or dead-eyed from having sat for eight hours at work. How many of us, whether supporting the ever-increasing cost of rent, family, education, or costs of living, could not say we are the same?

Vincent follows the rules of PER, and engages with his work on a level he never has before. Ironically, all details of his work fall to the wayside there are no more pithy comments from co-workers, the state of his zone in the cubicle, or what he does in off-hours. Everything that creates the landscape of his day, and thus the story as we read it, falls away into a void. As his productivity increases, he starts to notice changes. He sleeps for 25 hours at a time. The days turn into one-sentence chapters, sitting at his desk and not saying a word. Dorian and his cronies monitor him, impressed by his progress, promising that he is rapidly approaching the gate.

Elderly and his car, which previously functioned as Vincents anchor to reality, have vanished.

In my own world, the instructor at the mandatory seminar tells us that in order to adhere to the Lean Six Sigma process (created by Toyota in the wake of their airbag failures) all projects must be formatted on an A3 sized sheet of paper. This is the size used on auto factory floors, and it is big enough to see while on the line. It is written in pencil so changes can be made easily and quickly. I ask how we are supposed to create these sheets when the companys printers only fit a maximum paper size of A4. They promise to get back to my question, and they never do.

After a day of work only marked by a co-worker conversation of what to get for lunch, Vincent returns to his apartment to find someone inside it. It is Alice, acting as if their separation has never happened. Vincent tests the reality several ways, but comes to the same conclusion: it is Alice, and she is real, and she is here. The gate has worked. But all this ignores an important fact: the book begins not with Vincents dialogue, but with an excerpt from Alice, in 2037. Is this Alice solely a creation of Vincents mind? If thats true, then when Vincent finds out that Dorian is an undercover cop and Elderly owns four houses with his own wife is that real? Or does it not matter, like Dorian says? The apex philosophical question of the novel remains, in A Scanner Darklytype psych-noir twist: what happens when Alice meets Alice?

In Vincent and Alice and Alice, Jones has created a sharp modern allegory, fueled with the issues so prevalent in society. The desperate coping mechanisms we turn to in the face of grief. The near-satirical level of process improvement in our workplaces, to the point where any real changes are moot in the face of bureaucracy. Our obsessive natures, tempered by the sterile drudgery of white-collar work, and the humor we find in trying to adapt to it. Most importantly, the novel addresses the nature of love how we love others and treat them in a society that values disposal over sentimentality, what we give and what we ask of those we love, and how this will change in a growing world that is constantly breaking apart and reforming itself into something new.

Is this really what our future will look like? A world dominated by productivity, distraction, and consumerism over the pitfalls of human connection? I think what Jones is saying is that it doesnt have to be. As the world changes, we will change with it, and the only way to create a sustainable future is to find greater empathy with each other. Vincents marriage failed because he lost sight of the actual Alice, he slipped into a pattern of complacency that is warm and familiar. Relationships cant thrive in stagnation. In a time when nothing is certain and entities try to guide us the way they want to, we need to remember that our human connection is what grounds us. The answers are not there yet, but the only way we can figure them out is together.

At the end of the meeting at my workplace, we are given a coupon to a fast food place for a discount when you buy a cheeseburger and fries. I leave mine on the desk.

Matt E. Lewis is the editor of Ayahuasca Publishing.

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A New Simultaneous Reality: On Shane Jones's Vincent and Alice and Alice - lareviewofbooks

Reading Time: 4 minutes

As technology became more affordable and started to integrate into our daily lives through smart devices, online stores, and numerous other technologies that facilitate and power businesses across the world, brand promotion shape-shifted and adapted to these new circumstances. Nowadays, digital marketing is the cornerstone of revenue growth and market expansion, providing business owners with a series of channels to interact with the audience.

Furthermore, digital marketing utilizes the analytical capabilities of modern software solutions to enhance the value of each dollar we invest in the promotion of our enterprises. The versatility of content, mobile and desktop platforms, audience targeting, and numerous marketing metrics are what makes digital marketing such a powerful tool thats steadily becoming the mainstream advertisement approach.

The evolution of digital marketing is a constant struggle to keep up with the development of current technology and market requirements, which is why we are going to let you in on the latest innovations in digital marketing that you should keep in mind for the year 2020.

AI predicting human behavior

Its one thing to have an AI-driven software taking care of your schedule, organizing traffic routes, or managing your storage, however, next year well have AI predicting consumer behavior to enhance the performance of your digital marketing strategy. Well no longer only know what our target audience is interested in but also how each of the followers reacts to different inputs.

The development of deep learning algorithm allows Artificial Intelligence to learn human languages, predict events based on previous trends, and thats just scratching the surface of possibilities of the latest tech. The benefits of this innovation include cost-efficiency, the potential for higher retention rate, and overall improvement of marketing strategy.

Well have the ability to contact an essay writing service and provide means to create marketing content that will provoke just the reaction we are looking for with our readers. If targeted ads were a jump to hyperspace of the advertisement industry, this innovation will transcend the future of digital marketing. The technology is already in use, however, for now, only the largest corporate entities have the infrastructure for it. Keeping in mind the pace in which technology is moving forward and the latest announcements of Google reaching quantum supremacy, we can expect 2020 to be the first year in which marketers can predict what youre going to say to their offer.

AR growing strong

The problem with online shopping is that you cant try on for size those shoes you found or test the firmness of the couch youre looking to buy for your living room. Still, the number of online shoppers is growing and is expected to reach a figure higher than 2 billion shoppers by 2021, according to research published on the Statista website. These numbers are high already, nevertheless, the issue at hand is how to battle through the unforgiving competition and you become the one that sells more products that the guy next to you?

Augmented reality (AR) is a technology that allows us to mix reality with digital content in real-time. Its the same technology that brought us Pokemon chasers a few years back if you remember that trend at all. Nowadays, AR evolved so much so that there are commercial real estate companies offering virtual tours of their assets during which you could change the furniture design and layout, change the paint, and add new features, all so that you could make the most informed purchasing decision.

Companies like Modiface are pushing forward AR implementation capabilities for digital marketing, providing customized commercial AR software that allows users to try on products in a mixed reality environment. Simply put, if you wanted to buy a piece of makeup, you could try it on even if youre on a bus, browsing the internet on your mobile while going to work.

Chatbots

Natural language processing and deep learning algorithms allowed software developers to improve chatbots effectiveness to an astonishing rate. Instead of supplying customers with predetermined answers to questions that include certain keywords, as it was the case in the old days, these new customer support software solutions can understand the client that interacts with them.

Moreover, the answers chatbots provide are not drawn from a database with previously set series of potential answers rather the result of analysis based on the question asked and the resources available online. Also, chatbots can serve multiple clients simultaneously, which we could expect, should render human customer service agents obsolete.

The benefits of these super-intelligent chatbots include increased quality of service at a lower price, which is a business model to which every business owner would subscribe to without a question.

Conclusion

Digital marketing, as well as any other software related industry is rapidly changing, bringing new potential for business scaling and customer satisfaction with each passing year. These are the innovations that will certainly plant deep roots next year and reshape the way we conduct online business. Its important to stay ahead of these events and implement every strategy that improves the cost-efficiency and effectiveness of our marketing endeavors.

Written by: Nicholas Smith, BOSS contributor

Nicholas Smith is a professional writer, editor, and essay reviewer engaged with a series of respectful online publishers. He is dedicated to his family, work and friends. He is keen on reading, playing the guitar and traveling. He is interested in educational, marketing and blogging issues. Feel free to connect with him by email: writernicholassmith5@gmail.com

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Digital Marketing: Innovations to Watch out for in 2020 - BOSS Magazine

Research out of the University of California, Berkeley has again emphasized the importance of restful nightly sleep with regards to emotions.

Woman in Deep Sleep

When a person is unable to sleep well at night, their anxiety levels can surge by up to 30 percent, according to the study. A night full of sleep, on the other hand, soothes the anxious brain.

Findings from the study appeared in Nature Human Behavior. They provide very strong evidence of the neural links of sleep to anxiety.

UC Berkeley researchers reported that the particular type of sleep that produced the most-restful effect was a deep sleep. This sleep state, also referred to as non-rapid eye movement (NREM) sleep, is described as one of behavioral and physiological quiescence. While in it, neural oscillations become well synchronized, with both blood pressure and heart rates falling.

Deep sleep seems to be a natural anxiolytic (anxiety inhibitor), so long as we get it each and every night, said Matthew Walker, study senior author and a professor of neuroscience and psychology at UC Berkeley.

The study suggests sleep as a natural alternative to drugs for managing anxiety disorders, cases of which are rising in America.

Read Also: Researchers May Have Found A New Cure For Anxiety

The researchers made their findings in a series of experiments involving a full night of sleep and a night of no sleep. They first recruited 18 young adults for their study. These subjects were made to view video clips that were emotionally moving after a full night of sleep and also after a wakeful night.

While the subjects view the clips, researchers scanned their brains. They also used the state-trait anxiety inventory, a questionnaire, to assess the anxiety levels of the participants after each session.

The sleepless night resulted in the failure of the medial prefrontal cortex, an area of the brain helping with anxiety control. There was also over-activity in the deeper emotional centers of the brain.

Walker described the effect of a sleepless night as almost as if the brain is too heavy on the emotional pedal, without enough brake.

A night of no sleep caused anxiety levels to spike by up to 30 percent, the researchers found.

The results showed, on the other hand, that a full night of sleep led to a considerable drop in anxiety levels. This effect was particularly marked in subjects who had better NREM sleep. The brain waves of the participants were evaluated with the aid of electrodes placed on their heads.

Deep sleep had restored the brains prefrontal mechanism that regulates our emotions, lowering emotional and physiological reactivity and preventing the escalation of anxiety, said Eti Ben Simon, study lead author and a postdoctoral fellow at UC Berkeleys Center for Human Sleep Science.

The scientists were also able to replicate their results in another study of 30 subjects. They observed that participants who had more deep sleep the previous night had the lowest anxiety levels during the day that followed.

Anxiety disorders are a big problem in the industrialized world. Around 40 million adults in the United States suffer from an anxiety disorder. The incidence of the conditions is rising among children and teenagers as well.

The UC Berkeley researchers also carried out an online study, in addition to their lab experiments. They assessed variations in sleep and anxiety levels of 280 people over a period of four days. Their findings showed that the amount of sleep participants got on any night determined their anxiety level the day after.

Slight changes in sleep still produced an effect on anxiety levels of the subjects.

According to Walker, the findings imply that the decimation of sleep throughout most industrialized nations is possibly a major contributor to the increasing incidence of anxiety disorders in those countries.

Yet, sleep is hardly considered a standard recommendation for combating anxiety, the researchers noted.

Simon said the study confirms the causal relationship between sleep and anxiety. Also, deep sleep appeared to be particularly useful for dealing with anxiety disorders.

Our study strongly suggests that insufficient sleep amplifies the levels of anxiety and, conversely, that deep sleep helps reduce such stress, he said.

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Deep Sleep Reduces Anxiety Levels Considerably During The Day, UC Berkeley Study Shows - Gilmore Health News

SALT LAKE CITY--(BUSINESS WIRE)--Franklin Covey Co. (NYSE:FC) is mourning the passing of Hyrum W. Smith, a renowned speaker, entrepreneur, author, and philanthropist, who co-founded the company nearly four decades ago. Smith died on Monday, after a courageous battle with terminal cancer. He was 76.

FranklinCovey CEO, Bob Whitman, said, We extend our deepest heartfelt sympathies and condolences to Gail and the family. The world lost a truly great and remarkable human being in Hyrum. He made significant contributions to our company, to our community, and to our lives. He truly achieved his deeply held desire to make a positive difference on this planet. His legacy will continue to influence the lives of millions around the world. And, his enduring impact will be missed, but not forgotten.

Of Smiths many successes and achievements, he counted his marriage to his loving wife Gail and his relationship with his six children, their spouses, and his 24 grandchildren as his greatest success in life.

A family reception will be held December 2, from 6-8 p.m. at The Tuacahn Center For The Arts, 1100 Tuacahn Dr., Ivins, Utah 84738 and the funeral will be held on December 3, at Noon at 260 East 1060 South, Ivins, Utah 84738. In lieu of flowers, please send donations to the Hyrum & Gail Smith Tuacahn Legacy Endowment. For additional details, visit http://www.metcalfmortuary.com.

ABOUT FRANKLIN COVEY CO.

Franklin Covey Co. (NYSE: FC) is a global, public company specializing in organizational performance improvement. We help organizations and individuals achieve results that require a change in human behavior. Our expertise is in seven areas: leadership, execution, productivity, trust, sales performance, customer loyalty and education. FranklinCovey clients have included 90 percent of the Fortune 100, more than 75 percent of the Fortune 500, thousands of small and mid-sized businesses, as well as numerous government entities and educational institutions. FranklinCovey has more than 100 direct and partner offices providing professional services in over 160 countries and territories.

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Franklin Covey Co. Announces the Passing of Hyrum W. Smith, Renowned Speaker, Entrepreneur, Author, and Philanthropist - Business Wire

Consumers are the cornerstone of any organizations existence. As an organization, you must work on devising solutions for issues that the consumers of tomorrow may run into in order to improve the lives of these future consumers. But what are these issues? I set off on a journey into the magical land of trend analysis and came across five trends in consumer behaviour that have a shadowy side. That shadowy side is something that we should shed a little light on. And when there is a shadowy side to something, then theres something that needs to be polished up. As in, something can actually be done to make sure that tomorrow is good.

Whoa, we humans are slaves to addiction. Although some people are more susceptible to addiction than others, almost every person is sensitive to some form of addiction. For instance, we are sensitive to an addiction to media. Media outlets like Netflix are so quick in delivering the next episode, that its much more difficult for the average consumer to stop their media consumption than it is to maintain their media usage. You become addicted as a result.

Our social media consumption has often been associated with addiction in recent years. It has already been scientifically mapped out which personal characteristics fuel social media addiction. How social media addiction affects your satisfaction with your life. Or what the negative impact of social media addiction is on (school) performance. I could go on and on. Consequently, there are calls for us to regulate media consumption and to protect consumers from excessive media consumption.

Although our online world is characterized by words like connection and connectedness, in reality we are gradually becoming more and more lonely. Instead of heading into town with your girlfriends to find a new dress, you simply browse through webshops on your own. You no longer venture out on a pub crawl anymore to find an exciting new love interest. You simply swipe through Tinder profiles. Loneliness caused by the impact of social media and the digital world is starting to surface to such an extent, that it is being referred to as a loneliness epidemic. There is an increasing need to reconnect by seeking out actual physical and offline contact with each other again.

Then there is one more trend that goes against our evolutionary roots as hunters and gatherers. While hunting and gathering may act as an impetus for more consumerism, we are now seeing more and more signs directed towards downsizing and minimalism. We build tiny houses, we reuse furniture and we hardly own any books, music albums or films. Minimalism has become a way of life for many.

Some minimalists not only filter their own consumer pattern in excessive ways, but also do that on behalf of others. And thats where the shadowy side comes in. We are not talking about the minimalists who simply consider minimalism more aesthetically pleasing (e.g. fans of Scandinavian design). Nor the minimalists who for practical reasons aspire to a minimalist existence (e.g. which makes it easier for them to travel). But rather about the minimalists who aspire to nonconsumerism based on moral conviction with a focus on sustainability. Although, of course, there is nothing wrong with that moral conviction.

Many people share that conviction in principle. However, one may have some reservations about those minimalists who act as activists in their approach to others where flight shame, plastic shame or meat shame are concerned. There appears to be a razor-thin line between raising awareness or instilling feelings of shame on others. We should honestly ask ourselves whether we are making our society more appealing when we step over that line. Guilt and shame can certainly change behaviors. Nevertheless, the question remains whether there are not more charming roads to the Rome in question.

A trend associated with that of minimalism is that of nonmaterialism. Nonmaterialistic consumers consume without any tangible consequence of that consumerism. On the one hand, nonmaterialism is the result of a changing pattern of consumerism. We prefer to spend our money on experiences and adventures rather than on products. On the other hand, we are replacing some products with subscriptions. We no longer buy a CD, but a subscription to Spotify instead.

Especially this second development is beginning to take on such significant proportions that we now speak of a subscription economy. Subscription models are penetrating markets, meaning that the relationship between provider and consumer is undergoing considerable change. Not only does this relationship become more long-term and stable, but is also characterized by a higher level of dependence. The more subscriptions, the less diversification in the consumer pattern and the greater the dependence on a number of behemoth corporations. From research carried out by McKinsey, it appears that consumers are indeed buying subscriptions en masse, yet only about 11% of them are fans of the subscription model.

When it comes to consumers, we mean people. Its almost time to change that mindset. As the consumer robot is gaining ground. For example, a study by Ericsson shows that 70% of consumers think that within three years virtual assistants will be making purchasing decisions for them. Some researchers have even gone a step further and claim that in a few years time, 85% of shopping behaviour will take place without human interaction. It is impossible to pin an exact number on this in the future, but the trend is very clear.

Personally I find this the one of most cool trends. I am a huge fan of a society where artificial intelligence provides human intelligence with support wherever possible. Of course, there is also a shadowy side to this trend. How do we integrate ethics into the purchasing decisions of a consumer robot? And how do we ensure that consumers are happy to entrust their wallets to a robot? Together with my research group, Im working hard on designing solutions to these questions.

Tomorrow is good for our customers if we work on the shadowy side of these developments. When we brighten up something that is shadowy, turn negatives into positives and turn anything thats a grey area into something that shines!

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Tomorrow is good: 5 trends in consumer behavior that have a shadowy side - Innovation Origins

Cross-cultural analysis of song

It is unclear whether there are universal patterns to music across cultures. Mehr et al. examined ethnographic data and observed music in every society sampled (see the Perspective by Fitch and Popescu). For songs specifically, three dimensions characterize more than 25% of the performances studied: formality of the performance, arousal level, and religiosity. There is more variation in musical behavior within societies than between societies, and societies show similar levels of within-society variation in musical behavior. At the same time, one-third of societies significantly differ from average for any given dimension, and half of all societies differ from average on at least one dimension, indicating variability across cultures.

Science, this issue p. eaax0868; see also p. 944

Music is often assumed to be a human universal, emerging from an evolutionary adaptation specific to music and/or a by-product of adaptations for affect, language, motor control, and auditory perception. But universality has never actually been systematically demonstrated, and it is challenged by the vast diversity of music across cultures. Hypotheses of the evolutionary function of music are also untestable without comprehensive and representative data on its forms and behavioral contexts across societies.

We conducted a natural history of song: a systematic analysis of the features of vocal music found worldwide. It consists of a corpus of ethnographic text on musical behavior from a representative sample of mostly small-scale societies, and a discography of audio recordings of the music itself. We then applied tools of computational social science, which minimize the influence of sampling error and other biases, to answer six questions. Does music appear universally? What kinds of behavior are associated with song, and how do they vary among societies? Are the musical features of a song indicative of its behavioral context (e.g., infant care)? Do the melodic and rhythmic patterns of songs vary systematically, like those patterns found in language? And how prevalent is tonality across musical idioms?

Analysis of the ethnography corpus shows that music appears in every society observed; that variation in song events is well characterized by three dimensions (formality, arousal, religiosity); that musical behavior varies more within societies than across them on these dimensions; and that music is regularly associated with behavioral contexts such as infant care, healing, dance, and love. Analysis of the discography corpus shows that identifiable acoustic features of songs (accent, tempo, pitch range, etc.) predict their primary behavioral context (love, healing, etc.); that musical forms vary along two dimensions (melodic and rhythmic complexity); that melodic and rhythmic bigrams fall into power-law distributions; and that tonality is widespread, perhaps universal.

Music is in fact universal: It exists in every society (both with and without words), varies more within than between societies, regularly supports certain types of behavior, and has acoustic features that are systematically related to the goals and responses of singers and listeners. But music is not a fixed biological response with a single prototypical adaptive function: It is produced worldwide in diverse behavioral contexts that vary in formality, arousal, and religiosity. Music does appear to be tied to specific perceptual, cognitive, and affective faculties, including language (all societies put words to their songs), motor control (people in all societies dance), auditory analysis (all musical systems have signatures of tonality), and aesthetics (their melodies and rhythms are balanced between monotony and chaos). These analyses show how applying the tools of computational social science to rich bodies of humanistic data can reveal both universal features and patterns of variability in culture, addressing long-standing debates about each.

We used primary ethnographic text and field recordings of song performances to build two richly annotated cross-cultural datasets: NHS Ethnography and NHS Discography. The original material in each dataset was annotated by humans (both amateur and expert) and by automated algorithms.

What is universal about music, and what varies? We built a corpus of ethnographic text on musical behavior from a representative sample of the worlds societies, as well as a discography of audio recordings. The ethnographic corpus reveals that music (including songs with words) appears in every society observed; that music varies along three dimensions (formality, arousal, religiosity), more within societies than across them; and that music is associated with certain behavioral contexts such as infant care, healing, dance, and love. The discographyanalyzed through machine summaries, amateur and expert listener ratings, and manual transcriptionsreveals that acoustic features of songs predict their primary behavioral context; that tonality is widespread, perhaps universal; that music varies in rhythmic and melodic complexity; and that elements of melodies and rhythms found worldwide follow power laws.

At least since Henry Wadsworth Longfellow declared in 1835 that music is the universal language of mankind (1), the conventional wisdom among many authors, scholars, and scientists is that music is a human universal, with profound similarities across societies (2). On this understanding, musicality is embedded in the biology of Homo sapiens (3), whether as one or more evolutionary adaptations for music (4, 5), the by-products of adaptations for auditory perception, motor control, language, and affect (69), or some amalgam of these.

Music certainly is widespread (1012), ancient (13), and appealing to almost everyone (14). Yet claims that it is universal or has universal features are commonly made without citation [e.g., (1517)], and those with the greatest expertise on the topic are skeptical. With a few exceptions (18), most music scholars suggest that few if any universals exist in music (1923). They point to variability in the interpretations of a given piece of music (2426), the importance of natural and social environments in shaping music (2729), the diverse forms of music that can share similar behavioral functions (30), and the methodological difficulty of comparing the music of different societies (12, 31, 32). Given these criticisms, along with a history of some scholars using comparative work to advance erroneous claims of cultural or racial superiority (33), the common view among music scholars today (34, 35) is summarized by the ethnomusicologist George List: The only universal aspect of music seems to be that most people make it. I could provide pages of examples of the non-universality of music. This is hardly worth the trouble (36).

Are there, in fact, meaningful universals in music? No one doubts that music varies across cultures, but diversity in behavior can shroud regularities emerging from common underlying psychological mechanisms. Beginning with Chomskys hypothesis that the worlds languages conform to an abstract Universal Grammar (37, 38), many anthropologists, psychologists, and cognitive scientists have shown that behavioral patterns once considered arbitrary cultural products may exhibit deeper, abstract similarities across societies emerging from universal features of human nature. These include religion (3941), mate preferences (42), kinship systems (43), social relationships (44, 45), morality (46, 47), violence and warfare (4850), and political and economic beliefs (51, 52).

Music may be another example, although it is perennially difficult to study. A recent analysis of the Garland Encyclopedia of World Music revealed that certain featuressuch as the use of words, chest voice, and an isochronous beatappear in a majority of songs recorded within each of nine world regions (53). But the corpus was sampled opportunistically, which made generalizations to all of humanity impossible; the musical features were ambiguous, leading to poor interrater reliability; and the analysis studied only the forms of the societies music, not the behavioral contexts in which it is performed, leaving open key questions about functions of music and their connection to its forms.

Music perception experiments have begun to address some of these issues. In one, internet users reliably discriminated dance songs, healing songs, and lullabies sampled from 86 mostly small-scale societies (54); in another, listeners from the Mafa of Cameroon rated happy, sad, and fearful examples of Western music somewhat similarly to Canadian listeners, despite having had limited exposure to Western music (55); in a third, Americans and Kreung listeners from a rural Cambodian village were asked to create music that sounded angry, happy, peaceful, sad, or scared and generated similar melodies to one another within these categories (56). These studies suggest that the form of music is systematically related to its affective and behavioral effects in similar ways across cultures. But they can only provide provisional clues about which aspects of music, if any, are universal, because the societies, genres, contexts, and judges are highly limited, and because they too contain little information about musics behavioral contexts across cultures.

A proper evaluation of claims of universality and variation requires a natural history of music: a systematic analysis of the features of musical behavior and musical forms across cultures, using scientific standards of objectivity, representativeness, quantification of variability, and controls for data integrity. We take up this challenge here. We focus on vocal music (hereafter, song) rather than instrumental music [see (57)] because it does not depend on technology, has well-defined physical correlates [i.e., pitched vocalizations (19)], and has been the primary focus of biological explanations for music (4, 5).

Leveraging more than a century of research from anthropology and ethnomusicology, we built two corpora, which collectively we call the Natural History of Song (NHS). The NHS Ethnography is a corpus of descriptions of song performances, including their context, lyrics, people present, and other details, systematically assembled from the ethnographic record to representatively sample diversity across societies. The NHS Discography is a corpus of field recordings of performances of four kinds of songdance, healing, love, and lullabyfrom an approximately representative sample of human societies, mostly small-scale.

We used the corpora to test five sets of hypotheses about universality and variability in musical behavior and musical forms:

1) We tested whether music is universal by examining the ethnographies of 315 societies, and then a geographically stratified pseudorandom sample of them.

2) We assessed how the behaviors associated with song differ among societies. We reduced the high-dimensional NHS Ethnography annotations to a small number of dimensions of variation while addressing challenges in the analysis of ethnographic data, such as selective nonreporting. This allowed us to assess how the variation in musical behavior across societies compares with the variation within a single society.

3) We tested which behaviors are universally or commonly associated with song. We cataloged 20 common but untested hypotheses about these associations, such as religious activity, dance, and infant care (4, 5, 40, 54, 5860), and tested them after adjusting for sampling error and ethnographer bias, problems that have bedeviled prior tests.

4) We analyzed the musical features of songs themselves, as documented in the NHS Discography. We derived four representations of each song, including blind human ratings and machine summaries. We then applied machine classifiers to these representations to test whether the musical features of a song predict its association with particular behavioral contexts.

5) In exploratory analyses, we assessed the prevalence of tonality in the worlds songs, found that variation in their annotations falls along a small number of dimensions, and plotted the statistical distributions of melodic and rhythmic patterns in them.

All data and materials are publicly available at http://osf.io/jmv3q. We also encourage readers to view and listen to the corpora interactively via the plots available at http://themusiclab.org/nhsplots.

Is music universal? We first addressed this question by examining the eHRAF World Cultures database (61, 62), developed and maintained by the Human Relations Area Files organization. It includes high-quality ethnographic documents from 315 societies, subject-indexed by paragraph. We searched for text that was tagged as including music (instrumental or vocal) or that contained at least one keyword identifying vocal music (e.g., singers).

Music was widespread: The eHRAF ethnographies describe music in 309 of the 315 societies. Moreover, the remaining six (the Turkmen, Dominican, Hazara, Pamir, Tajik, and Ghorbat peoples) do in fact have music, according to primary ethnographic documents available outside the database (6368). Thus, music is present in 100% of a large sample of societies, consistent with the claims of writers and scholars since Longfellow (1, 4, 5, 10, 12, 53, 54, 5860, 6973). Given these data, and assuming that the sample of human societies is representative, the Bayesian 95% posterior credible interval for the population proportion of human societies that have music, with a uniform prior, is [0.994, 1].

To examine what about music is universal and how music varies worldwide, we built the NHS Ethnography (Fig. 1 and Text S1.1), a corpus of 4709 descriptions of song performances drawn from the Probability Sample File (7476). This is a ~45-million-word subset of the 315-society database, comprising 60 traditionally living societies that were drawn pseudorandomly from each of Murdocks 60 cultural clusters (62), covering 30 distinct geographical regions and selected to be historically mostly independent of one another. Because the corpus representatively samples from the worlds societies, it has been used to test cross-cultural regularities in many domains (46, 7783), and these regularities may be generalized (with appropriate caution) to all societies.

The illustration depicts the sequence from acts of singing to the ethnography corpus. (A) People produce songs in conjunction with other behavior, which scholars observe and describe in text. These ethnographies are published in books, reports, and journal articles and then compiled, translated, cataloged, and digitized by the Human Relations Area Files organization. (B) We conduct searches of the online eHRAF corpus for all descriptions of songs in the 60 societies of the Probability Sample File and annotate them with a variety of behavioral features. The raw text, annotations, and metadata together form the NHS Ethnography. Codebooks listing all available data are in tables S1 to S6; a listing of societies and locations from which texts were gathered is in table S12.

The NHS Ethnography, it turns out, includes examples of songs in all 60 societies. Moreover, each society has songs with words, as opposed to just humming or nonsense syllables (which are reported in 22 societies). Because the societies were sampled independently of whether their people were known to produce music, in contrast to prior cross-cultural studies (10, 53, 54), the presence of music in each oneas recognized by the anthropologists who embedded themselves in the society and wrote their authoritative ethnographiesconstitutes the clearest evidence supporting the claim that song is a human universal. Readers interested in the nature of the ethnographers reports, which bear on what constitutes music in each society [see (27)], are encouraged to consult the interactive NHS Ethnography Explorer at http://themusiclab.org/nhsplots.

How do we reconcile the discovery that song is universal with the research from ethnomusicology showing radical variability? We propose that the music of a society is not a fixed inventory of cultural behaviors, but rather the product of underlying psychological faculties that make certain kinds of sound feel appropriate to certain social and emotional circumstances. These include entraining the body to acoustic and motoric rhythms, analyzing harmonically complex sounds, segregating and grouping sounds into perceptual streams (6, 7), parsing the prosody of speech, responding to emotional calls, and detecting ecologically salient sounds (8, 9). These faculties may interact with others that specifically evolved for music (4, 5). Musical idioms differ with respect to which acoustic features they use and which emotions they engage, but they all draw from a common suite of psychological responses to sound.

If so, what should be universal about music is not specific melodies or rhythms but clusters of correlated behaviors, such as slow soothing lullabies sung by a mother to a child or lively rhythmic songs sung in public by a group of dancers. We thus asked how musical behavior varies worldwide and how the variation within societies compares to the variation between them.

To determine whether the wide variation in the annotations of the behavioral context of songs in the database (Text S1.1) falls along a smaller number of dimensions capturing the principal ways that musical behavior varies worldwide, we used an extension of Bayesian principal components analysis (84), which, in addition to reducing dimensionality, handles missing data in a principled way and provides a credible interval for each observations coordinates in the resulting space. Each observation is a song event, namely, a description in the NHS Ethnography of a song performance, a characterization of how a society uses songs, or both.

We found that three latent dimensions is the optimum number, explaining 26.6% of variability in NHS Ethnography annotations. Figure 2 depicts the space and highlights examples from excerpts in the corpus; an interactive version is available at http://themusiclab.org/nhsplots. (See Text S2.1 for details of the model, including the dimension selection procedure, model diagnostics, a test of robustness, and tests of the potential influence of ethnographer characteristics on model results.) To interpret the space, we examined annotations that load highly on each dimension; to validate this interpretation, we searched for examples at extreme locations and examined their content. Loadings are presented in tables S13 to S15; a selection of extreme examples is given in table S16.

(A to E) Projection of a subset of the NHS Ethnography onto three principal components. Each point represents the posterior mean location of an excerpt, with points colored by which of four types (identified by a broad search for matching keywords and annotations) it falls into: dance (blue), lullaby (green), healing (red), or love (yellow). The geometric centroids of each song type are represented by the diamonds. Excerpts that do not match any single search are not plotted but can be viewed in the interactive version of this figure at http://themusiclab.org/nhsplots, along with all text and metadata. Selected examples of each song type are presented here [highlighted circles and (B) to (E)]. (F to H) Density plots show the differences between song types on each dimension. Criteria for classifying song types from the raw text and annotations are shown in table S17.

The first dimension (accounting for 15.5% of the variance, including error noise) captures variability in the Formality of a song: Excerpts high along this dimension describe ceremonial events involving adults, large audiences, and instruments; excerpts low on it describe informal events with small audiences and children. The second dimension (accounting for 6.2%) captures variability in Arousal: Excerpts high along this dimension describe lively events with many singers, large audiences, and dancing; excerpts low on it describe calmer events involving fewer people and less overt affect, such as people singing to themselves. The third dimension (4.9%) distinguishes Religious events from secular ones: Passages high along this dimension describe shamanic ceremonies, possession, and funerary songs; passages low on it describe communal events without spiritual content, such as community celebrations.

To validate whether this dimensional space captured behaviorally relevant differences among songs, we tested whether we could reliably recover clusters for four distinctive, easily identifiable, and regularly occurring song types: dance, lullaby, healing, and love (54). We searched the NHS Ethnography for keywords and human annotations that matched at least one of the four types (table S17).

Although each song type can appear throughout the space, clear structure is observable (Fig. 2): The excerpts falling into each type cluster together. On average, dance songs (1089 excerpts) occupy the high-Formality, high-Arousal, low-Religiosity region. Healing songs (289 excerpts) cluster in the high-Formality, high-Arousal, high-Religiosity region. Love songs (354 excerpts) cluster in the low-Formality, low-Arousal, low-Religiosity region. Lullabies (156 excerpts) are the sparsest category (although this was likely due to high missingness in variables associated with lullabies, such as one indicating the presence of infant-directed song; see Text S2.1.5) and are located mostly in the low-Formality and low-Arousal regions. An additional 2821 excerpts matched either more than one category or none of the four.

To specify the coherence of these clusters formally rather than just visually, we asked what proportion of song events are closer to the centroid of their own types location than to any other type (Text S2.1.6). Overall, 64.7% of the songs were located closest to the centroid of their own type; under a null hypothesis that song type is unrelated to location, simulated by randomly shuffling the song labels, only 23.2% would do so (P < 0.001 according to a permutation test). This result was statistically significant for three of the four song types (dance, 66.2%; healing, 74.0%; love, 63.6%; Ps < 0.001) although not for lullabies (39.7%, P = 0.92). The matrix showing how many songs of each type were near each centroid is in table S18. Note that these analyses eliminated variables with high missingness; a validation model that analyzed the entire corpus yielded similar dimensional structure and clustering (figs. S1 and S2 and Text S2.1.5).

We next examined whether this pattern of variation applies within all societies. Do all societies take advantage of the full spectrum of possibilities made available by the neural, cognitive, and cultural systems that underlie music? Alternatively, is there only a single, prototypical song type that is found in all societies, perhaps reflecting the evolutionary origin of music (love songs, say, if music evolved as a courtship display; or lullabies, if it evolved as an adaptation to infant care), with the other types haphazardly distributed or absent altogether, depending on whether the society extended the prototype through cultural evolution? As a third alternative, do societies fall into discrete typologies, such as a Dance Culture or a Lullaby Culture? As still another alternative, do they occupy sectors of the space, so that there are societies with only arousing songs or only religious songs, or societies whose songs are equally formal and vary only by arousal, or vice versa? The data in Fig. 2, which pool song events across societies, cannot answer such questions.

We estimated the variance of each societys scores on each dimension, aggregated across all ethnographies from that society. This revealed that the distributions of each societys observed musical behaviors are remarkably similar (Fig. 3), such that a song with average formality, average arousal, or average religiosity could appear in any society we studied. This finding is supported by comparing the global average along each dimension to each societys mean and standard deviation, which summarizes how unusual the average song event would appear to members of that society. We found that in every society, a song event at the global mean would not appear out of place: The global mean always falls within the 95% confidence interval of every societys distribution (fig. S3). These results do not appear to be driven by any bias stemming from ethnographer characteristics such as sex or academic field (fig. S4 and Text S2.1.7), nor are they artifacts of a society being related to other societies in the sample by region, subregion, language family, subsistence type, or location in the Old versus New World (fig. S5 and Text S2.1.8).

Density plots for each society show the distributions of musical performances on each of the three principal components (Formality, Arousal, Religiosity). Distributions are based on posterior samples aggregated from corresponding ethnographic observations. Societies are ordered by the number of available documents in the NHS Ethnography (the number of documents per society is displayed in parentheses). Distributions are color-coded according to their mean distance from the global mean (in z-scores; redder distributions are farther from 0). Although some societies means differ significantly from the global mean, the mean of each societys distribution is within 1.96 standard deviations of the global mean of 0. One society (Tzeltal) is not plotted because it has insufficient observations for a density plot. Asterisks denote society-level mean differences from the global mean. *P < 0.05, **P < 0.01, ***P < 0.001.

We also applied a comparison that is common in studies of genetic diversity (85) and that has been performed in a recent cultural-phylogenetic study of music (86). It revealed that typical within-society variation is approximately six times the between-society variation. Specifically, the ratios of within- to between-society variances were 5.58 for Formality [95% Bayesian credible interval, (4.11, 6.95)]; 6.39 (4.72, 8.34) for Arousal; and 6.21 (4.47, 7.94) for Religiosity. Moreover, none of the 180 mean values for the 60 societies over the three dimensions deviated from the global mean by more than 1.96 times the standard deviation of the principal components scores within that society (fig. S3 and Text S2.1.9).

These findings demonstrate global regularities in musical behavior, but they also reveal that behaviors vary quantitatively across societies, consistent with the long-standing conclusions of ethnomusicologists. For instance, the Kanuris musical behaviors are estimated to be less formal than those of any other society, whereas those of the Akan are estimated to be the most religious (in both cases, significantly different from the global mean on average). Some ethnomusicologists have attempted to explain such diversity, noting, for example, that more formal song performances tend to be found in more socially rigid societies (10).

Despite this variation, a song event of average formality would appear unremarkable in the Kanuris distribution of songs, as would a song event of average religiosity in the Akan. Overall, we find that for each dimension, approximately one-third of all societies means significantly differed from the global mean, and approximately half differed from the global mean on at least one dimension (Fig. 3). But despite variability in the societies means on each dimension, their distributions overlap substantially with one another and with the global mean. Moreover, even the outliers in Fig. 3 appear to represent not genuine idiosyncrasy in some cultures but sampling error: The societies that differ more from the global mean on some dimension are those with sparser documentation in the ethnographic record (fig. S6 and Text S2.1.10). To ensure that these results are not artifacts of the statistical techniques used, we applied them to a structurally analogous dataset whose latent dimensions are expected to vary across countries, namely climate features (for instance, temperature is related to elevation, which certainly is not universal); the results were entirely different from what we found when analyzing the NHS Ethnography (figs. S7 and S8 and Text S2.1.11).

The results suggest that societies musical behaviors are largely similar to one another, such that the variability within a society exceeds the variability between them (all societies have more soothing songs, such as lullabies; more rousing songs, such as dance tunes; more stirring songs, such as prayers; and other recognizable kinds of musical performance), and that the appearance of uniqueness in the ethnographic record may reflect underreporting.

Ethnographic descriptions of behavior are subject to several forms of selective nonreporting: Ethnographers may omit certain kinds of information because of their academic interests (e.g., the author focuses on farming and not shamanism), implicit or explicit biases (e.g., the author reports less information about the elderly), lack of knowledge (e.g., the author is unaware of food taboos), or inaccessibility (e.g., the author wants to report on infant care but is not granted access to infants). We cannot distinguish among these causes, but we can discern patterns of omission in the NHS Ethnography. For example, we found that when the singers age is reported, the singer is likely to be young, but when the singers age is not reported, cues that the singer is old are statistically present (such as the fact that a song is ceremonial). Such correlationsbetween the absence of certain values of one variable and the reporting of particular values of otherswere aggregated into a model of missingness (Text S2.1.12) that forms part of the Bayesian principal components analysis reported above. This allowed us to assess variation in musical behavior worldwide, while accounting for reporting biases.

Next, to test hypotheses about the contexts with which music is strongly associated worldwide, in a similarly robust fashion, we compared the frequency with which a particular behavior appears in text describing song with the estimated frequency with which it appears across the board, in all the text written by that ethnographer about that society, which can be treated as the null distribution for that behavior. If a behavior is systematically associated with song, then its frequency in ethnographic descriptions of songs should exceed its frequency in that null distribution, which we estimated by randomly drawing the same number of passages from the same documents [see Text S2.2 for full model details].

We generated a list of 20 hypotheses about universal or widespread contexts for music (Table 1) from published work in anthropology, ethnomusicology, and cognitive science (4, 5, 40, 54, 5860), together with a survey of nearly 1000 scholars that solicited opinions about which behaviors might be universally linked to music (Text S1.4.1). We then designed two sets of criteria for determining whether a given passage of ethnography represented a given behavior in this list. The first used human-annotated identifiers, capitalizing on the fact that every paragraph in the Probability Sample File comes tagged with one of more than 750 identifiers from the Outline of Cultural Materials (OCM), such as MOURNING, INFANT CARE, or WARFARE.

We tested 20 hypothesized associations between song and other behaviors by comparing the frequency of a behavior in song-related passages to that in comparably-sized samples of text from the same sources that are not about song. Behavior was identified with two methods: topic annotations from the Outline of Cultural Materials (OCM identifiers) and automatic detection of related keywords (WordNet seed words; see table S19). Significance tests compared the frequencies in the passages in the full Probability Sample File containing song-related keywords (Song freq.) with the frequencies in a simulated null distribution of passages randomly selected from the same documents (Null freq.). ***P < 0.001, **P < 0.01, *P < 0.05, using adjusted P values (88); 95% intervals for the null distribution are in parentheses.

The second set of criteria was needed because some hypotheses corresponded only loosely to the OCM identifiers (e.g., love songs is only a partial fit to ARRANGING A MARRIAGE and not an exact fit to any other identifier), and still others fit no identifier at all [e.g., music perceived as art or as a creation (59)]. So we designed a method that examined the text directly. Starting with a small set of seed words associated with each hypothesis (e.g., religious, spiritual, and ritual for the hypothesis that music is associated with religious activity), we used the WordNet lexical database (87) to automatically generate lists of conceptually related terms (e.g., rite and sacred). We manually filtered the lists to remove irrelevant words and homonyms and add relevant keywords that may have been missed, then conducted word stemming to fill out plurals and other grammatical variants (full lists are in table S19). Each method has limitations: Automated dictionary methods can erroneously flag a passage containing a word that is ambiguous, whereas the human-coded OCM identifiers may miss a relevant passage, misinterpret the original ethnography, or paint with too broad a brush, applying a tag to a whole paragraph or to several pages of text. Where the two methods converge, support for a hypothesis is particularly convincing.

After controlling for ethnographer bias via the method described above, and adjusting the P values for multiple hypotheses (88), we found support from both methods for 14 of the 20 hypothesized associations between music and a behavioral context, and support from one method for the remaining six (Table 1). To verify that these analyses specifically confirmed the hypotheses, as opposed to being an artifact of some other nonrandom patterning in this dataset, we reran them on a set of additional OCM identifiers matched in frequency to the ones used above [see Text S2.2.2 for a description of the selection procedure]. They covered a broad swath of topics, including DOMESTICATED ANIMALS, POLYGAMY, and LEGAL NORMS that were not hypothesized to be related to song (the full list is in table S20). We find that only one appeared more frequently in song-related paragraphs than in the simulated null distribution (CEREAL AGRICULTURE; see table S20 for full results). This contrasts sharply with the associations reported in Table 1, suggesting that they represent bona fide regularities in the behavioral contexts of music.

We now turn to the NHS Discography to examine the musical content of songs in four behavioral contexts (dance, lullaby, healing, and love; Fig. 4A), selected because each appears in the NHS Ethnography, is widespread in traditional cultures (59), and exhibits shared features across societies (54). Using predetermined criteria based on liner notes and supporting ethnographic text (table S21), and seeking recordings of each type from each of the 30 geographic regions, we found 118 songs of the 120 possibilities (4 contexts 30 regions) from 86 societies (Fig. 4B). This coverage underscores the universality of these four types; indeed, in the two possibilities we failed to find (healing songs from Scandinavia and from the British Isles), documentary evidence shows that both existed (89, 90) despite our failure to find audio recordings of the practice.The recordings may be unavailable because healing songs were rare by the early 1900s, roughly when portablefield recordingbecame feasible.

(A) Illustration depicting the sequence from acts of singing to the audio discography. People produce songs, which scholars record. We aggregate and analyze the recordings via four methods: automatic music information retrieval, annotations from expert listeners, annotations from nave listeners, and staff notation transcriptions (from which annotations are automatically generated). The raw audio, four types of annotations, transcriptions, and metadata together form the NHS Discography. (B) Plot of the locations of the 86 societies represented, with points colored by the song type in each recording (blue, dance; red, healing; yellow, love; green, lullaby). Codebooks listing all available data are in tables S1 and S7 to S11; a listing of societies and locations from which recordings were gathered is in table S22.

The data describing each song comprised (i) machine summaries of the raw audio using automatic music information retrieval techniques, particularly the audios spectral features (e.g., mean brightness and roughness, variability of spectral entropy) (Text S1.2.1); (ii) general impressions of musical features (e.g., whether its emotional valence was happy or sad) by untrained listeners recruited online from the United States and India (Text S1.2.2); (iii) ratings of additional music-theoretic features such as high-level rhythmic grouping structure [similar in concept to previous rating-scale approaches to analyzing world music (10, 53)] from a group of 30 expert musicians including Ph.D. ethnomusicologists and music theorists (Text S1.2.3); and (iv) detailed manual transcriptions, also by expert musicians, of musical features (e.g., note density of sung pitches) (Text S1.2.4). To ensure that classifications were driven only by the content of the music, we excluded any variables that carried explicit or implicit information about the context (54), such as the number of singers audible on a recording and a coding of polyphony (which indicates the same thing implicitly). This exclusion could be complete only in the manual transcriptions, which are restricted to data on vocalizations; the music information retrieval and nave listener data are practically inseparable from contextual information, and the expert listener ratings contain at least a small amount, because despite being told to ignore the context, the experts could still hear some of it, such as accompanying instruments. [See Text S2.3.1 for details about variable exclusion.]

In a previous study, people listened to recordings from the NHS Discography and rated their confidence in each of six possible behavioral contexts (e.g., used to soothe a baby). On average, the listeners successfully inferred a songs behavioral context from its musical forms: The songs that were actually used to soothe a baby (i.e., lullabies) were rated highest as used to soothe a baby; dance songs were rated highly as used for dancing, and so on (54).

We ran a massive conceptual replication (Text S1.4.2) where 29,357 visitors to the citizen-science website http://themusiclab.org listened to songs drawn at random from the NHS Discography and were asked to guess what kind of song they were listening to from among four alternatives (yielding 185,832 ratings, i.e., 118 songs rated about 1500 times each). Participants also reported their musical skill level and degree of familiarity with world music. Listeners guessed the behavioral contexts with a level of accuracy (42.4%) that is well above chance (25%), showing that the acoustic properties of a song performance reflect its behavioral context in ways that span human cultures.

The confusion matrix (Fig. 5A) shows that listeners identified dance songs most accurately (54.4%), followed by lullabies (45.6%), healing songs (43.3%), and love songs (26.2%), all significantly above chance (Ps < 0.001). Dance songs and lullabies were the least likely to be confused with each other, presumably because of their many contrasting features, such as tempo (a possibility we examine below; see Table 2). The column marginals suggest that the raters were biased toward identifying recordings as healing songs (32.6%, above their actual proportion of 23.7%) and away from identifying them as love songs (17.9%), possibly because healing songs are less familiar to Westernized listeners and they were overcompensating in identifying examples. As in previous research (54), love songs were least reliably identified, despite their ubiquity in Western popular music, possibly because they span a wide range of styles (for example, the vastly different Elvis Presley hit singles Love Me Tender and Burning Love). Nonetheless, d-prime scores (Fig. 5A), which capture the sensitivity to a signal independently of response bias, show that all behavioral contexts were identified at a rate higher than chance (d = 0).

(A) In a massive online experiment (N = 29,357), listeners categorized dance songs, lullabies, healing songs, and love songs at rates higher than chance level of 25%, but their responses to love songs were by far the most ambiguous (the heat map shows average percent correct, color-coded from lowest magnitude, in blue, to highest magnitude, in red). Note that the marginals (below the heat map) are not evenly distributed across behavioral contexts: Listeners guessed healing most often and love least often despite the equal number of each in the materials. The d-prime scores estimate listeners sensitivity to the song-type signal independent of this response bias. (B) Categorical classification of the behavioral contexts of songs, using each of the four representations in the NHS Discography, is substantially above the chance performance level of 25% (dotted red line) and is indistinguishable from the performance of human listeners, 42.4% (dotted blue line). The classifier that combines expert annotations with transcription features (the two representations that best ignore background sounds and other context) performs at 50.8% correct, above the level of human listeners. (C) Binary classifiers that use the expert annotation + transcription feature representations to distinguish pairs of behavioral contexts [e.g., dance from love songs, as opposed to the four-way classification in (B)] perform above the chance level of 50% (dotted red line). Error bars represent 95% confidence intervals from corrected resampled t tests (94).

The table reports the predictive influence of musical features in the NHS Discography in distinguishing song types across cultures, ordered by their overall influence across all behavioral contexts. The classifiers used the average rating for each feature across 30 annotators. The coefficients are from a penalized logistic regression with standardized features and are selected for inclusion using a LASSO for variable selection. For brevity, we only present the subset of features with notable influence on a pairwise comparison (coefficients greater than 0.1). Changes in the values of the coefficients produce changes in the predicted log-odds ratio, so the values in the table can be interpreted as in a logistic regression.

Are accurate identifications of the contexts of culturally unfamiliar songs restricted to listeners with musical training or exposure to world music? In a regression analysis, we found that participants categorization accuracy was statistically related to their self-reported musical skill [F(4,16245) = 2.57, P = 0.036] and their familiarity with world music [F(3,16167) = 36.9, P < 0.001; statistics from linear probability models], but with small effect sizes: The largest difference was a 4.7percentage point advantage for participants who reported that they were somewhat familiar with traditional music relative to those who reported that they had never heard it, and a 1.3percentage point advantage for participants who reported that they have a lot of skill relative to no skill at all. Moreover, when limiting the dataset to listeners with no skill at all or listeners who had never heard traditional music, mean accuracy was almost identical to the overall cohort. These findings suggest that although musical experience enhances the ability to detect the behavioral contexts of songs from unfamiliar cultures, it is not necessary.

If listeners can accurately identify the behavioral contexts of songs from unfamiliar cultures, there must be acoustic features that universally tend to be associated with these contexts. To identify them, we evaluated the relationship between a songs musical forms [measured in four ways; see Text S1.2.5 and (12, 31, 32, 9193) for discussion of how difficult it is to represent music quantitatively] and its behavioral context. We used a cross-validation procedure that determined whether the pattern of correlation between musical forms and context computed from a subset of the regions could be generalized to predict a songs context in the other regions (as opposed to being overfitted to arbitrary correlations within that subsample). Specifically, we trained a least absolute shrinkage and selection operator (LASSO) multinomial logistic classifier (94) on the behavioral context of all the songs in 29 of the 30 regions in the NHS Discography, and used it to predict the context of the unseen songs in the 30th. We ran this procedure 30 times, omitting a different region each time (table S23 and Text S2.3.2). We compared the accuracy of these predictions to two baselines: pure chance (25%) and the accuracy of listeners in the massive online experiment (see above) when guessing the behavioral context from among four alternatives (42.4%).

We found that with each of the four representations, the musical forms of a song can predict its behavioral context (Fig. 5B) at high rates, comparable to those of the human listeners in the online experiment. This finding was not attributable to information in the recordings other than the singing, which could be problematic if, for example, the presence of a musical instrument on a recording indicated that it was likelier to be a dance song than a lullaby (54), artificially improving classification. Representations with the least extraneous influencethe expert annotators and the summary features extracted from transcriptionshad no lower classification accuracy than the other representations. And a classifier run on combined expert + transcription data had the best performance of all, 50.8% [95% CI (40.4%, 61.3%), computed by corrected resampled t test (95)].

To ensure that this accuracy did not merely consist of patterns in one society predicting patterns in historically or geographically related ones, we repeated the analyses, cross-validating across groupings of societies, including superordinate world region (e.g., Asia), subsistence type (e.g., hunter-gatherers), and Old versus New World. In many cases, the classifier performed comparably to the main model (table S24), although low power in some cases (i.e., training on less than half the corpus) substantially reduced precision.

In sum, the acoustic form of vocal music predicts its behavioral contexts worldwide (54), at least in the contexts of dance, lullaby, healing, and love: All classifiers performed above chance and within 1.96 standard errors of the performance of human listeners.

Showing that the musical features of songs predict their behavioral context provides no information about which musical features those are. To help identify them, we determined how well the combined expert + transcription data distinguished between specific pairs of behavioral contexts rather than among all four, using a simplified form of the classifiers described above, which not only distinguished the contexts but also identified the most reliable predictors of each contrast, without overfitting (96). This can reveal whether tempo, for example, helps distinguish dance songs from lullabies while failing to distinguish lullabies from love songs.

Performance once again significantly exceeded chance (in this case, 50%) for all six comparisons (Ps < 0.05; Fig. 5C). Table 2 lays out the musical features that drive these successful predictions and thereby characterize the four song types across cultures. Some are consistent with common sense; for instance, dance songs differ from lullabies in tempo, accent, and the consistency of their macrometer (i.e., the superordinate grouping of rhythmic notes). Other distinguishers are subtler: The most common interval of a song occurs a smaller proportion of the time in a dance song than in a healing song, which suggests that dance songs are more melodically variable than healing songs (for explanations of musical terminology, see Table 2). Similarly, it is unsurprising that lullabies and love songs are more difficult to distinguish than lullabies and dance songs (97); nonetheless, they may be distinguished by two features: the strength of metrical accents and the size of the pitch range (both larger in love songs).

In sum, four common song categories, distinguished by their contexts and goals, tend to have distinctive musical qualities worldwide. These results suggest that universal features of human psychology bias people to produce and enjoy songs with certain kinds of rhythmic or melodic patterning that naturally go with certain moods, desires, and themes. These patterns do not consist of concrete acoustic features, such as a specific melody or rhythm, but rather of relational properties such as accent, meter, and interval structure.

Of course, classification accuracy that is twice the level of chance still falls well short of perfect prediction; hence, many aspects of music cannot be manifestations of universal psychological reactions. Although musical features can predict differences between songs from these four behavioral contexts, a given song may be sung in a particular context for other reasons, including its lyrics, its history, the style and instrumentation of its performance, its association with mythical or religious themes, and constraints of the cultures musical idiom. And although we have shown that Western listeners, who have been exposed to a vast range of musical styles and idioms, can distinguish the behavioral contexts of songs from non-Western societies, we do not know whether non-Western listeners can do the same. To reinforce the hypothesis of universal associations between musical form and context, similar methods should be tested with non-Western listeners.

The NHS Discography can be used to explore world music in many other ways. We present three exploratory analyses here, mindful of the limitation that they may apply only to the four genres the corpus includes.

A basic feature of many styles of music is tonality, in which a melody is composed of a fixed set of discrete tones [perceived pitches as opposed to actual pitches, a distinction dating to Aristoxenuss Elementa Harmonica (98)], and some tones are psychologically dependent on others, with one tone felt to be central or stable (99101). This tone (more accurately, perceived pitch class, embracing all the tones one or more octaves apart) is called the tonal center or tonic, and listeners characterize it as a reference point, point of stability, basis tone, home, or tone that the melody is built around and where it should end. For example, the tonal center of Row Your Boat is found in each of the rows, the last merrily, and the songs last note, dream.

Although tonality has been studied in a few non-Western societies (102, 103), its cross-cultural distribution is unknown. Indeed, the ethnomusicologists who responded to our survey (Text S1.4.1) were split over whether the music of all societies should be expected to have a tonal center: 48% responded probably not universal or definitely not universal. The issue is important because a tonal system is a likely prerequisite for analyzing music, in all its diversity, as the product of an abstract musical grammar (73). Tonality also motivates the hypothesis that melody is rooted in the brains analysis of harmonically complex tones (104). In this theory, a melody can be considered a set of serialized overtones, the harmonically related frequencies ordinarily superimposed in the rich tone produced by an elongated resonator such as the human vocal tract. In tonal melodies, the tonic corresponds to the fundamental frequency of the disassembled complex tone, and listeners tend to favor tones in the same pitch class as harmonics of the fundamental (105).

To explore tonality in the NHS Discography, we analyzed the expert listener annotations and the transcriptions (Text S2.4.1). Each of the 30 expert listeners was asked, for each song, whether or not they heard at least one tonal center, defined subjectively as above. The results were unambiguous: 97.8% of ratings were in the affirmative. More than two-thirds of songs were rated as tonal by all 30 expert listeners, and 113 of the 118 were rated as tonal by more than 90% of them. The song with the most ambiguous tonality (the Kwakwakawakw healing song) still had a majority of raters respond in the affirmative (60%).

If listeners heard a tonal center, they were asked to name its pitch class. Here too, listeners were highly consistent: Either there was widespread agreement on a single tonal center or the responses fell into two or three tonal centers (Fig. 6A; the distributions of tonality ratings for all 118 songs are in fig. S10). We used Hartigans dip test (106) to measure the multimodality of the ratings. In the 73 songs that the test classified as unimodal, 85.3% of ratings were in agreement with the modal pitch class. In the remaining 45 songs, 81.7% of ratings were in agreement with the two most popular pitch classes, and 90.4% were in agreement with the three most popular. The expert listeners included six Ph.D. ethnomusicologists and six Ph.D. music theorists; when restricting the ratings to this group alone, the levels of consistency were comparable.

(A) Histograms representing 30 expert listeners' ratings of tonal centers in all 118 songs, each song corresponding to a different color, show two main findings: (i) Most songs distributions are unimodal, such that most listeners agreed on a single tonal center (represented by the value 0). (ii) When listeners disagree, they are multimodal, with the most popular second mode (in absolute distance) five semitones away from the overall mode, a perfect fourth. The music notation is provided as a hypothetical example only, with C as a reference tonal center; note that the ratings of tonal centers could be at any pitch level. (B) The scatterplot shows the correspondence between modal ratings of expert listeners with the first-rank predictions from the Krumhansl-Schmuckler key-finding algorithm. Points are jittered to avoid overlap. Note that pitch classes are circular (i.e., C is one semitone away from C# and from B) but the plot is not; distances on the axes of (B) should be interpreted accordingly.

In songs where the ratings were multimodally distributed, the modal tones were often hierarchically related; for instance, ratings for the Ojibwa healing song were evenly split between B (pitch class 11) and E (pitch class 4), which are a perfect fourth (five semitones) apart. The most common intervals between the two modal tones were the perfect fourth (in 15 songs), a half-step (one semitone, in nine songs), a whole step (two semitones, in eight songs), a major third (four semitones, in seven songs), and a minor third (three semitones, in six songs).

We cannot know which features of a given recording our listeners were responding to in attributing a tonal center to it, nor whether their attributions depended on expertise that ordinary listeners lack. We thus sought converging, objective evidence for the prevalence of tonality in the worlds music by submitting NHS Discography transcriptions to the Krumhansl-Schmuckler key-finding algorithm (107). This algorithm sums the durations of the tones in a piece of music and correlates this vector with each of a family of candidate vectors, one for each key, consisting of the relative centralities of those pitch classes in that key. The algorithms first guess (i.e., the key corresponding to the most highly correlated vector) matched the expert listeners ratings of the tonal center 85.6% of the time (measured via a weighted average of its hit rate for the most common expert rating when the ratings were unimodal and either of the two most common ratings when they were multimodal). When we relaxed the criterion for a match to the algorithms first- and second-ranked guesses, it matched the listeners ratings on 94.1% of songs; adding its third-ranked estimate resulted in matches 97.5% of the time, and adding the fourth resulted in matches with 98.3% [all Ps < 0.0001 above the chance level of 9.1%, using a permutation test (Text S2.4.1)]. These results provide convergent evidence for the presence of tonality in the NHS Discography songs (Fig. 6B).

These conclusions are limited in several ways. First, they are based on songs from only four behavioral contexts, omitting others such as mourning, storytelling, play, war, and celebration. Second, the transcriptions were created manually and could have been influenced by the musical ears and knowledge of the expert transcribers. (Current music information retrieval algorithms are not robust enough to transcribe melodies accurately, especially from noisy field recordings, but improved ones could address this issue.) The same limitation may apply to the ratings of our expert listeners. Finally, the findings do not show how the people from the societies in which NHS Discography songs were recorded hear the tonality in their own music. To test the universality of tonality perception, one would need to conduct field experiments in diverse populations.

To examine patterns of variation among the songs in the NHS Discography, we applied the same kind of Bayesian principal components analysis used for the NHS Ethnography to the combination of expert annotations and transcription features (i.e., the representations that focus most on the singing, excluding context). The results yielded two dimensions, which together explain 23.9% of the variability in musical features. The first, which we call Melodic Complexity, accounts for 13.1% of the variance (including error noise); heavily loading variables included the number of common intervals, pitch range, and ornamentation (all positively) and the predominance of the most common pitch class, the predominance of the most common interval, and the distance between the most common intervals (all negatively; see table S25). The second, which we call Rhythmic Complexity, accounts for 10.8% of the variance; heavily loading variables included tempo, note density, syncopation, accent, and consistency of macrometer (all positively) and the average note duration and duration of melodic arcs (all negatively; see table S26). The interpretation of the dimensions is further supported in Fig. 7, which shows excerpts of transcriptions at the extremes of each dimension; an interactive version is at http://themusiclab.org/nhsplots.

(A) A Bayesian principal components analysis reduction of expert annotations and transcription features (the representations least contaminated by contextual features) shows that these measurements fall along two dimensions that may be interpreted as rhythmic complexity and melodic complexity. (B and C) Histograms for each dimension show the differencesor lack thereofbetween behavioral contexts. (D to G) Excerpts of transcriptions from songs at extremes from each of the four quadrants, to validate the dimension reduction visually. The two songs at the highrhythmic complexity quadrants are dance songs (in blue); the two songs at the lowrhythmic complexity quadrants are lullabies (in green). Healing songs are depicted in red and love songs in yellow. Readers can listen to excerpts from all songs in the corpus at http://osf.io/jmv3q; an interactive version of this plot is available at http://themusiclab.org/nhsplots.

In contrast to the NHS Ethnography, the principal components space for the NHS Discography does not distinguish the four behavioral contexts of songs in the corpus. We found that only 39.8% of songs matched their nearest centroid (overall P = 0.063 from a permutation test; dance: 56.7%, P = 0.12; healing: 7.14%, P > 0.99; love: 43.3%, P = 0.62; lullaby: 50.0%, P = 0.37; a confusion matrix is in table S27). Similarly, k-means clustering on the principal components space, asserting k = 4 (because there are four known clusters), failed to reliably capture any of the behavioral contexts. Finally, given the lack of predictive accuracy of songs location in the two-dimensional space, we explored each dimensions predictive accuracy individually, using t tests of each context against the other three, adjusted for multiple comparisons (88). Melodic complexity did not predict context (dance, P = 0.79; healing, P = 0.96; love, P = 0.13; lullaby, P = 0.35). However, rhythmic complexity did distinguish dance songs (which were more rhythmically complex, P = 0.01) and lullabies (which were less rhythmically complex, P = 0.03) from other songs; it did not distinguish healing or love songs (Ps > 0.99). When we adjusted these analyses to account for across-region variability, the results were comparable (Text S2.4.2). Thus, although musical content systematically varies in two ways across cultures, this variation is mostly unrelated to the behavioral contexts of the songs, perhaps because complexity captures distinctions that are salient to music analysts but not strongly evocative of particular moods or themes among the singers and listeners themselves.

Many phenomena in the social and biological sciences are characterized by Zipfs law (108), in which the probability of an event is inversely proportional to its rank in frequency, an example of a power-law distribution (in the Zipfian case, the exponent is 1). Power-law distributions (as opposed to, say, the geometric distribution) have two key properties: A small number of highly frequent events account for the majority of observations, and there are a large number of individually improbable events whose probability falls off slowly in a thick tail (109).

In language, for example, a few words appear with very high frequency, such as pronouns, while a great many are rare, such as the names of species of trees, but any sample will nonetheless tend to contain several rare words (110). A similar pattern is found in the distribution of colors among paintings in a given period of art history (111). In music, Zipfs law has been observed in the melodic intervals of Bach, Chopin, Debussy, Mendelssohn, Mozart, and Schoenberg (112116); in the loudness and pitch fluctuations in Scott Joplin piano rags (117); in the harmonies (118120) and rhythms of classical music (121); and, as Zipf himself noted, in melodies composed by Mozart, Chopin, Irving Berlin, and Jerome Kern (108).

We tested whether the presence of power-law distributions is a property of music worldwide by tallying relative melodic bigrams (the number of semitones separating each pair of successive notes) and relative rhythmic bigrams (the ratio of the durations of each pair of successive notes) for all NHS Discography transcriptions (Text S2.4.3). The bigrams overlapped, with the second note of one bigram also serving as the first note of the next.

We found that both the melodic and rhythmic bigram distributions followed power laws (Fig. 8), and this finding held worldwide: The fit between the observed bigrams and the best-fitting power function was high within each region (melodic bigrams: median R2 = 0.97, range 0.92 to 0.99; rhythmic bigrams: median R2 = 0.98, range 0.88 to 0.99). The most prevalent bigrams were the simplest. Among the melodic bigrams (Fig. 8A), three small intervals (unison, major second, and minor third) accounted for 73% of the bigrams; the tritone (six semitones) was the rarest, accounting for only 0.2%. The prevalence of these bigrams is significant: Using only unisons, major seconds, and minor thirds, one can construct any melody in a pentatonic scale, a scale found in many cultures (122). Among the rhythmic bigrams (Fig. 8B), three patterns with simple integer ratios (1:1, 2:1, and 3:1) accounted for 86% of observed bigrams, whereas a large and eclectic group of ratios (e.g., 7:3, 11:2) accounted for fewer than 1%. The distribution is thus consistent with earlier findings that rhythmic patterns with simple integer ratios appear to be universal (123). The full lists of bigrams, with their cumulative frequencies, are in tables S28 and S29.

(A and B) We computed relative melodic (A) and rhythmic (B) bigrams and examined their distributions in the corpus. Both distributions followed a power law; the parameter estimates in the inset correspond to those from the generalized Zipf-Mandelbrot law, where s refers to the exponent of the power law and refers to the Mandelbrot offset. Note that in both plots, the axes are on logarithmic scales. The full lists of bigrams are in tables S28 and S29.

These results suggest that power-law distributions in music are a human universal (at least in the four genres studied here), with songs dominated by small melodic intervals and simple rhythmic ratios and enriched with many rare but larger and more complex ones. Because the specification of a power law is sensitive to sampling error in the tail of the distribution (124), and because many generative processes can give rise to a power-law distribution (125), we cannot identify a single explanation. Among the possibilities are that control of the vocal tract is biased toward small jumps in pitch that minimize effort, that auditory analysis is biased toward tracking similar sounds that are likely to be emitted by a single sound-maker, that composers tend to add notes to a melody that are similar to ones already contained in it, and that human aesthetic reactions are engaged by stimuli that are power lawdistributed, which makes them neither too monotonous nor too chaotic (116, 126, 127)inevitable and yet surprising, as the music of Bach has been described (128).

The challenge in understanding music has always been to reconcile its universality with its diversity. Even Longfellow, who declared music to be humanitys universal language, celebrated the many forms it could take: The peasant of the North sings the traditionary ballad to his children the muleteer of Spain carols with the early lark The vintager of Sicily has his evening hymn; the fisherman of Naples his boat-song; the gondolier of Venice his midnight serenade (1). Conversely, even an ethnomusicologist skeptical of universals in music conceded that most people make it (36). Music is universal but clearly takes on different forms in different cultures. To go beyond these unexceptionable observations and understand exactly what is universal about music, while circumventing the biases inherent in opportunistic observations, we assembled databases that combine the empirical richness of the ethnographic and musicological record with the tools of computational social science.

The findings allow the following conclusions: Music exists in every society, varies more within than between societies, and has acoustic features that are systematically (albeit probabilistically) related to the behaviors of singers and listeners. At the same time, music is not a fixed biological response with a single, prototypical adaptive function such as mating, group bonding, or infant care: It varies substantially in melodic and rhythmic complexity and is produced worldwide in at least 14 behavioral contexts that vary in formality, arousal, and religiosity. But music does appear to be tied to identifiable perceptual, cognitive, and affective faculties, including language (all societies put words to their songs), motor control (people in all societies dance), auditory analysis (all musical systems have some signatures of tonality), and aesthetics (their melodies and rhythms are balanced between monotony and chaos).

To build the NHS Ethnography, we extracted descriptions of singing from the Probability Sample File by searching the database for text that was tagged with the topic MUSIC and that included at least one of 10 keywords that singled out vocal music (e.g., singers, song, lullaby) (Text S1.1). This search yielded 4709 descriptions of singing (490,615 words) drawn from 493 documents (median 49 descriptions per society). We manually annotated each description with 66 variables to comprehensively capture the behaviors reported by ethnographers (e.g., age of the singer, duration of the song). We also attached metadata about each paragraph (e.g., document publication data; tagged nonmusical topics) using a matching algorithm that located the source paragraphs from which the description of the song was extracted. See Text S1.1 for full details on corpus construction, tables S1 to S6 for annotation types, and table S12 for a list of societies and locations.

Song events from all the societies were aggregated into a single dataset, without indicators of the society they came from. The range of possible missing values was filled in using a Markov chain Monte Carlo procedure that assumes that their absence reflects conditionally random omission with probabilities related to the features that the ethnographer did record, such as the age and sex of the singer or the size of the audience (Text S2.1). For the dimensionality reduction, we used an optimal singular value thresholding criterion (129) to determine the number of dimensions to analyze, which we then interpreted by three techniques: examining annotations that load highly on each dimension; searching for examples at extreme locations in the space and examining their content; and testing whether known song types formed distinct clusters in the latent space (e.g., dance songs versus healing songs; see Fig. 2).

To build the NHS Discography, and to ensure that the sample of recordings from each genre is representative of human societies, we located field recordings of dance songs, lullabies, healing songs, and love songs using a geographic stratification approach similar to that of the NHS Ethnographynamely, by drawing one recording representing each behavioral context from each of 30 regions. We chose songs according to predetermined criteria (table S21), studying recordings liner notes and the supporting ethnographic text without listening to the recordings. When more than one suitable recording was available, we selected one at random. See Text S1.1 for details on corpus construction, tables S1 and S7 to S11 for annotation types, and table S22 for a list of societies and locations.

For analyses of the universality of musical forms, we studied each of the four representations individually (machine summaries, nave listener ratings, expert listener ratings, and features extracted from manual transcriptions), along with a combination of the expert listener and manual transcription data, which excluded many contextual features of the audio recordings (e.g., the sound of an infant crying during a lullaby). For the explorations of the structure of musical forms, we studied the manual transcriptions of songs and also used the Bayesian principal components analysis technique (described above) on the combined expert + transcription data summarizing NHS Discography songs.

Both the NHS Ethnography and NHS Discography can be explored interactively at http://themusiclab.org/nhsplots.

H. W. Longfellow, Outre-mer: A Pilgrimage Beyond the Sea (Harper, 1835).

L. Bernstein, The Unanswered Question: Six Talks at Harvard (Harvard Univ. Press, 2002).

A. S. Bregman, Auditory Scene Analysis: The Perceptual Organization of Sound (MIT Press, 1990).

S. Pinker, How the Mind Works (Norton, 1997).

A. Lomax, Folk Song Style and Culture (American Association for the Advancement of Science, 1968).

A. P. Merriam, The Anthropology of Music (Northwestern Univ. Press, 1964).

B. Nettl, The Study of Ethnomusicology: Thirty-Three Discussions (Univ. of Illinois Press, 2015).

B. Nettl, in The Origins of Music (MIT Press, 2000), pp. 463472.

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