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Nicholas Christakis

From Wikipedia, the free encyclopedia

Nicholas Christakis
Born (1962-05-07) May 7, 1962 (age 62)
EducationYale University (BS)
Harvard University (MD, MPH)
University of Pennsylvania (PhD)
SpouseErika Christakis
Scientific career
Fields
InstitutionsUniversity of Pennsylvania
University of Chicago
Harvard University
Yale University
Doctoral advisorRenée Fox
Websitenicholaschristakis.net

Nicholas A. Christakis (born May 7, 1962) is a Greek-American[1] sociologist and physician known for his research on social networks and on the socioeconomic, biosocial, and evolutionary determinants of human welfare (including the behavior, health, and capability of individuals and groups). He is the Sterling Professor of Social and Natural Science at Yale University, where he directs the Human Nature Lab. He is also the co-director of the Yale Institute for Network Science.[2][3]

Christakis was elected a Fellow of the National Academy of Sciences in 2024.[4] Previously, he had been a Fellow of the National Academy of Medicine in 2006; of the American Association for the Advancement of Science in 2010; and of the American Academy of Arts and Sciences in 2017.[5] In 2021, he received an honorary degree from the University of Athens, Greece.[6]

In 2009, Christakis was named to the Time 100, Time magazine's list of the 100 most influential people in the world.[7] In 2009 and again in 2010, he was named by Foreign Policy magazine to its list of top global thinkers.[8]

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Transcription

Hi, my name is Nicholas Christakis and I'm a physician and a social scientist and the discipline I'm going to be speaking about to you today is sociology.  Sociology is the field in which you study human behavior and human experience and how it relates to the fact that individuals are embedded within larger groups and collections of individuals.  When you see an individual as a member of a group or the collectivity you get a completely different perspective on that person and on the groups of which they are a member and in fact, in sociology we explore a fundamental tension and that tension arises because of two facts.  On the one hand you yourself have your own identity and your own agency and your own ability to make choices that affect your life, but on the other hand there is a collective responsibility for your life as well and it turns out that collective supra-individual factors can have as much to do with all kinds of aspects of your life, including whether you live or die as your own genes or your own choices and it turns out that supra-individual collective factors can have as much to do with what happens to you in your life and even with whether you live or die as things within you, your own genes or your own choices.

Now supra-individual factors such as where you live, what kind of networks you are a part of, social interactions you are a part of, what kind of institutions are nearby, for instance governments or hospitals, all of these are critical in shaping your life and all of our lives and these supra-individual factors can include things like inequality, culture and religion as well.

Supra-individual factors like where you live or where you are located in these vast face-to-face networks that we human beings assemble or what kinds of formal institutions are near you like governments or hospitals for example can have as much to do with what happens to you in your life as your own decisions and your own actions.  Other sorts of things are important too, like inequality or culture or religion and those sorts of supra-individual factors have a similar importance.

This is the difference between what we want to understand as structure and agency between social constraints and opportunities on the one hand and individual choices and actions on the other hand and a second key idea beyond that first one-
This the difference between structure and agency, between collective constraints and opportunities that constrain and permit you to do certain kinds of things in your life on the one hand and your own individual choices and actions that permit you to do other sorts of things on the other hand.  That is the first big idea that I’d like to communicate today.  

The second big idea that sociology explores and that I would like to communicate today is that collective phenomena are not mere aggregations of individual phenomena.  There is something different, something special about groups of people, about collectivities that does not reside within the individuals themselves, something that emerges, something that transcends, something that is above and not a part of solely individual kinds of things that you might think of.  

A second key idea in sociology is that collective phenomena are not mere aggregations of individual phenomena.  There is something special, something weird almost about groups of individuals, about collectivities, something weird that you cannot see if you just study individuals, but that you must study whole groups of people in order to really understand.

So how did I become interested in these crazy ideas?  Actually I started my career as a physician and I went to medical school and at the time I wanted to be a reconstructive surgeon and I wanted to operate on people who had cranial facial abnormalities or people whose extremities had been cut off and reattach these extremities and I used to cut class my first year of medical school and go operate with some of the surgeons at Children’s Hospital in Boston and I did this for quite awhile and eventually as we would operate on these kids they were primarily kids, one after another, day after day, I came to the realization that the kind of healthcare that I wanted to practice was not the kind that took care of people one at a time, but rather, the kind that tried to take care of whole populations of people.  I mean I wanted to understand why do groups of people become sick, not just why do individuals become sick and how can we make groups become well, not just individuals become well one at a time and part of this was prompted by my realization that I was running around putting my fingers in the dike.  One hole after another was springing water and we were running around, all of us, trying to plug these holes and I was interested in how can we make a better dike, how can make a situation in which fewer people become sick to begin with, in which we spring fewer holes to begin with, in the dike as it were and in fact I began to ask what I came eventually to see as sociological questions about the origins of illness and disease and suffering and death in our society and I wanted to understand how we could have a sociological response, a collective response to these sorts of problems and in fact this dovetails to some extent with an interest in public health, which can be contrasted with a kind of interest in clinical medicine which takes care of patients one at a time.   So let’s start by taking a look at a personal testament, a very seemingly individualistic statement that a human being is making about their own life, about what would seem to be a quintessentially private individualistic decision, namely whether to take your own life and to commit suicide.  This is Charlotte Perkin Gilman’s suicide note.  She was 75 years-old when she took her life and the note says:  “The time is approaching when we shall consider it abhorrent to our civilization to allow a human being to die in prolonged agony which we should mercifully end in any other creature.  Believing this choice to be of social service in promoting wiser views on this question, I have preferred chloroform to cancer.” 

And the note said:  The time is approaching when we shall consider it abhorrent to our civilization to allow a human being to die in prolonged agony which we should mercifully end in any other creature.  Believing this choice to be a social service in promoting wiser views on this question, I have preferred chloroform to cancer.”  

So despite the fact that this woman is taking her life and despite the fact that she is writing a suicide note notice that the note contains or eludes to kind of connections to others even as she was ending her own life.  She bemoans the fact that society is not sensitive to her pain and even while dying she is trying to make a contribution to society.  She is trying to be connected to other individuals.  

Here is another note:  “Dear God, please have mercy on my soul.  Please forgive me.  I can’t stand the pain anymore.”  And that note was written by a 76 year-old grandmother who isolated by depression and disability crawled into her basement freezer to kill herself by the cold and you might ask what kind of a social system permits this to happen, permits one of its members to be so alone, to feel so isolated that this is the choice that they would make and in fact you might ask was this suicide truly an individual act, was it really purely an individual choice. 

Another one, Ron Berst jumped off the Golden Gate Bridge and in his will he donated $10,000 to AIDS research.  This is his note:  “To the San Francisco Police Department or equivalent jurisdiction.  This is to state that I, Ron R. Burst did take my own life due to the fact that I have the disease AIDS and it has progressed both rapidly and to the point where number, I constantly feel ill and have almost no energy and number two, I very soon expect to become a burden to my friends and family and I do not want to put any of them through such an ordeal.  I sincerely regret any inconvenience that this may have caused anyone involved.  I honestly believe that a fast end such as this while one is still able, yet ill enough to justify it is easier on my close friends who have been so unbelievably supportive emotionally for me and my family who have been no less so than to drag this out.  I did not give up.”

So again in Mr. Berst’s note notice the social concern.  His death is not an individual act at all.  First of all, it was public.  He jumped off the Golden Gate Bridge.  People saw him.  Second, it was guided by a concern for others.  He is worried about his friends and family and third, it is infused with the social ties that connect him to his family and his friends.  

Now there is another way that suicide is social as well.  It is not just the connection the individual has to others.  It is the responsibility that others have to the individual.  It is about how social and structural factors constrain or permit individual acts even like suicide.  For example, this is an image of the Golden Gate Bridge from which Ron Berst jumped and this bridge is unusual in its design because the sidewalk as you can see is directly next to the edge of the image.  He walked along the sidewalk and then just jumped over that railing, stood there and jumped right over.

And this is a picture of Kevin Hines who almost met the same fate as Mr. Berst.  In September of 2000 at the age of 19 suffering from depression he went to the Golden Gate Bridge and he stood there for 40 minutes crying.  No one approached him to ask what was wrong and then eventually a tourist came up and asked him if he could take her photograph.  Hines interpreted this as a clear sign that no one cared.  He took the picture and then when she walked away he turned around and he jumped right over the railing, but instantly he says he realized that he had made a mistake.  He changed his mind.  “Oh shit,” he thought, “I don’t want to die.”  “What am I going to do?” he later recalled.  In midair he came up with a plan to save his life as he described as follows:  “It was simply this.  “A; God save me, B; throw your head back and C; hit feet first.”  And it takes four seconds to drop the 220 feet from the height of the Golden Gate Bridge to the water and you eventually reach a speed of 75 miles per hour and among the over 1,200 people who have jumped off the bridge since 1937 only 26 are believed to have survived and interestingly a large percentage of those who attempt the jump when they are interviewed afterwards say that they regretted the decision as soon as they jumped.  

For example, another jumper, Kevin Baldwin was 28 and also severely depressed in August of 1985 when he jumped and he later said the following thing:  “I still see my hands coming off the railing.  I instantly realized that everything in my life that I thought was unfixable was totally fixable except for having just jumped.”

It is 220 feet from the deck of the bridge to the water and it takes just four seconds to reach the bottom and by which point you are traveling at 75 miles per hour.

Even allowing for the fact that we cannot know what all the successful suicides would have said had we been able to interview them these kinds of reports by people who jumped and survived beg the question of how to prevent these kinds of supposedly purely individual acts.  What would happen to these people if somehow society could have prevented them from jumping, if there somehow had been a structure in place which had constrained the agency of these individuals?  One landmark study conducted in 1978 of 515 people who were removed from the Golden Gate Bridge before they had jumped and followed them for an average of about 26 years afterwards found that 94% were still alive or had died of natural causes many years later, so suicidal behavior is acute and crisis driven and if the individual is prevented from acting on their suicidal impulses by those around him it might not be repeated.

There are quite a number of remarkable things about such stories.  No doubt these individuals and their illnesses are central actors in the experience of the individual, but I want to highlight two other observations.  One is the role of the perceived indifference expressed by the person that Kevin encountered.  This point points to an important theme in sociology, the rule of social connection in our personal experience and the role of our embededness in the lives of others.  So one thing I would like to highlight is the perceived indifference on the part of the person that approached Kevin.  One thing that I would like to highlight is the perceived indifference on the part of the person, the tourist that approached Kevin because this highlights an important theme or an important idea in sociology, namely the idea that we are all connected to each other.  The role of connection in our experience of the world and the role of our embededness in others is in fact a key consideration or a key point that sociologists are interested in.  

The other important thing to realize from these stories is the importance of extra individual factors that help determine individual outcomes as I alluded to the role of structure versus the role of agency.  Now the Golden Gate Bridge has a foot path adjacent to the railing unlike most bridges and people still regularly kill themselves from it and if you look at the Golden Gate Bridge you can see some ideas about how we might constrain individual agency, how we might as a society respond to prevent people from jumping.  For example, suicide barriers such as this one at other sites have drastically reduced and often even eliminated suicides such as at the Eifel Tower, the Empire State Building or the Sydney Harbor Bridge, but a barrier has not been put at the Golden Gate Bridge for reasons that many, myself included find a bit silly.  Namely, that it would somehow ruin the aesthetics of the bridge, but here is an artist rendering of one possible solutions and it doesn’t look so bad.  This argument it turns out has been around for years, but finally in February of 2010 the Golden Gate Bridge Board after many years of lobbying agreed to put some suicide nets under the bridge to catch jumpers, but they did not agree to assign the use of any toll revenue for this purpose, so still there is nothing there to prevent suicide.

So this is a particularly specific and dramatic illustration of the interplay between structure and agency, between policy decisions made at the collective level and the ability of an individual even to stay alive.  Moreover, this is a particularly powerful illustration not only of the issue of structure versus agency, but also of more complicated ideas, namely, the issue of group level phenomena or of emergence which is the second big idea I would like to talk to you about today.

Now suicide has been used as an example to illustrate this idea ever since 1897 by a very famous sociologist by the name of Emile Durkheim who wrote about this topic and Durkheim had a number of arguments including the following.  He said or he wrote—so Durkheim had a number of arguments about suicide including the following.  He wrote:  “The individual is dominated by a moral reality greater than himself, namely, collective reality.  When each people is seen to have its own suicide rate more constant than that of general mortality, that its growth is in accordance with a coefficient of acceleration characteristic of each society, when it appears that the variations through which it passes at different times reflect the rhythm of social life and that marriage, divorce, the family, religious society, the army, etcetera affect it in accordance with definite laws then these states and institutions will no longer be regarded simply as characterless, ineffective ideological arrangements.  Rather they will felt to be real, living, active forces which because of the way they determine the individual prove their independence of him, which if the individual enters as an element in the combination whence these forces ensue at least control him once they are formed.”

So the individuals come and go in Durkheim’s analysis.  People come and go, but the rates of suicide stay the same, so he was looking at suicide rates in different religious groups in different periods in France and he found that these rates are constant across time and vary across religious groups even though the individual members of those groups in those particular times changed dramatically, so the Protestants in 1800 France are completely different than the human beings who are the Protestants in 1850 France and yet the suicide rate let’s say is the same.  Hence this constancy of rates and this variation across societies is indicative of something else going on beyond individual choice or brain biology.  It is as if the society determines this—it is as if the society determines this seemingly purely individual act, suicide.  Hence this constancy of rates and this variation across societies is indicative of something else going on beyond individual choice or individual biology.  It is as if society determines this seemingly purely individual act, this seemingly purely individual choice.  So you see groups can have properties of their own and the individuals within them are affected by those properties. Sociologist have been studying social networks beginning with the pioneering work of Georg Simmel in the 1890s and they have been doing this, studying networks for well over 100 years and social networks are one particular kind of supra-individual factor that can affect individual choices, that can shape your destiny and shape what happens to you in your life.  Now by social networks I don’t mean Facebook or MySpace of the kinds of recent networks that many of you might be thinking about.  I actually mean the kind of face-to-face networks that human beings have been making for tens of thousands of years.  In fact, ever since we lived on the African Savannah. 

Now each of us forms or inherits certain kinds of connections to friends, to coworkers, to our relatives, to our neighbors and each of those individuals in turn also has friends and coworkers and relatives and neighbors and as a result of this we form this incredibly ornate, almost baroque structure known as social networks and we precede to live out our lives embedded within these networks.

Now what is the difference between a group and a network?  Here is a picture of a group and a group maybe of 100 people.  Each dot represents a person, but a network in addition to the 100 people also has ties, the ties that connect the people to each other and it has specific ties at that and there are two kinds of networks, artificial networks and natural networks.  So for example, here is an example of one of the simplest type of artificial networks you can imagine, a bucket brigade.  It is a simple linear network.  It has 100 people to which we have added 99 ties.  

Everyone is connected to the guy on the right and to the guy on the left and assembling the people in this fashion gives this group of people properties it didn’t have before like the ability to efficiently transport debris or the ability to put out a fire.  If these people weren’t assembled in the network in this fashion, this linear network they couldn’t do it as well as they otherwise might or you could take the same 100 people and the same number of ties and organize them in the form of a telephone tree.  This was an old fashioned technology to efficiently transmit information before we had the internet, so the person in the middle indicated by the arrow he would have a list of two people that he was supposed to call let’s say to notify everyone about the closure of a school because of a snow day or something.  He would call two people.  Each of those people would call two people and the information about the school closure would rapidly and efficiently and accurately be transmitted throughout this group.

So you take the same number of people, the same number of ties.  You have a different kind of organization like in this form and now this group of people has totally different properties than the bucket brigade.  

A bucket brigade is an arrangement in which you line people up and you have a bucket that moves from one end to the other.  People pass the bucket along and this can be done either to transport water for example to put out a fire.  This was an old fashioned technology that people used or it can also be used to transport debris.  If you want to transport debris a great distance instead of having people running haphazardly transporting buckets one at a time you can have a series of buckets that are run to the front and the full buckets are moved to the rear of the line.

Or we could take the same number of people, 100 people, but now a different number of ties and assemble them into a completely different organization, for example, into military companies.  Here we have 100 men and women composed into 10 squads of 10 people and within each squad everyone knows each other very well.  There is a dense interconnection of ties and this kind of organization, this kind of structural organization is able to elicit from these individuals something that wasn’t present there before, namely, a willingness to die for each other, so this structural form of organizing people is able to call forth from the individual people or foster the emergence of new properties that weren’t necessarily there before.

But real social networks differ and don’t look anything like or natural—but natural social networks look nothing like the artificial networks we just saw.  They look more like this network.  Here is a slide in fact of such a natural network illustrating one of our own studies and this image was one that we made in order to help understand the role of social networks in the obesity epidemic.  

This image helped us to understand the role of social networks in obesity.  Beginning a few years ago, maybe 10 or 20 years ago it had become fashionable to speak about the obesity epidemic and it was clear that obesity was epidemic in one meaning of the word, meaning that there is more of it than there was before.  For example, just in the last 10 years the prevalence of obesity has gone from about 20% to about 30% and fully two-thirds of Americans are now overweight or obese, so something is going on that has given rise to an increasing amount of obesity and there are a number of structural factors that have been suggested as causing the obesity epidemic because we don’t really believe that there is something biological going on here even though the individual’s biology can explain variation between people and how big they are our biology hasn’t changed that much over the last 30 years.  So something social, something else must be going on to help explain why obesity has been rising so much and people have offered a number of structural explanations.  Maybe there is a declining real price of food.  Food is cheaper than it used to be, so by basic economics you’re going to buy more of it.  Maybe it is the marketing of food, the way food is marketed to us or the fat composition of food or there have been other sorts of changes that affect how many calories we use up every day in the course of our lives.  We have more sedentary lifestyles.  There has been a change in occupations.  We have a more service oriented economy than a labor oriented economy.  There is a changing pace of life in our society.  The design of our cities, urban design and suburban design, people don’t move around as much anymore and people had offered all of these kinds of explanations for the obesity epidemic, but we wondered whether we could add an explanation, whether we could understand obesity as being truly epidemic, as if something were spreading from person to person.  It wasn’t just a metaphoric epidemic.  It was a literal epidemic.  

Could we find evidence for a kind of social contagion whereby weight gain in one person could affect weight gain in other people to whom they were connected and in fact like the collective rates of suicide we can understand obesity as being a collective phenomenon as well and we live environment—and in fact we began to think about obesity in a sociological way.  Could we think about obesity and the epidemic of obesity as being somehow related to the suicide example I was discussing earlier where something collective seems to be determining individual’s likelihood of killing themselves?  Could something collective be contributing to individuals changing their body size?  

So we needed a special kind of data to do this and this image shows 2,200 people drawn from the very famous Framingham Heart Study in the year 2000.  Once again every dot is a person and every line between them represents a relationship between the two people and here we make bigger dots are bigger people and in addition we color the dots yellow if people are properly obese.  There are 2,200 people shown on this image and these people were taken from the very famous Framingham Heart Study and this image shows them in the year 2000 and if you look at this image you can see clustering of obese and non obese individuals within the image.  It is still a very complicated image, but if you study it mathematically you can find evidence of these clusters, clusters of yellow and red dots, so that people’s body size seems to be related to the body size of other people to whom they are connected and we were able to analyze these data and discern evidence for the clustering and interpersonal influence such that if people around you gained or lost weight it affected you as well and it seemed to spread from person to person and from person to person to person and even from person to person to person to person, so that weight gain seemed to—and weight loss seemed to spread within the network and one uses various kinds of statistical methods to analyze such data ranging from all kinds of statistical models to social network analysis to actual experiments that one can do.

All right, now in the process of studying the obesity epidemic we did something else as well because we also made movies about how social networks change across time and our initial motivation was to see if we could literally visualize the spread of obesity from person to person to person to person within the network.  Now getting the data and getting the data into shape and analyzing it statistically and making this movie took five years of my colleague James Fowler and my life and cost about a million dollars, so this little video I'm about to show you is a 30 second animation of a real social network, real data that took that long and that much money to make and my children joke that actually on a per-second basis it was more expensive than Avatar, but much less interesting, but the reason we made this image was that we had in our minds the following kind of metaphor.  

Many of you may have done an experiment in high school in which you took a water table and your dropped a pebble on the water and then you had these waves that emerged from where the pebble hit the water and these waves would hit the perimeter of the table and bounce back and if you did it just right you would get a standing wave on the surface of the water and if you didn’t do that experiment you probably had another experience as a kid which was sloshing around in your bathtub and probably remember that if you sloshed just right in your bathtub you can get your body into sync with a wave and get a big wave that will come out of the bathtub and splash onto the floor and make a big mess and that is a kind of a standing wave as well and what we thought we might be able to do was to see waves of obesity within the social network—and what we thought we would be able to do would be to see waves of obesity within the social network because you can imagine networks as a kind of socio-topological surface, a kind of hyper dimensional surface and that it might be possible to see waves within this network so that as I gain weight it makes my friends gain weight and as my friends gain weight it makes their friends gain weight and you literally could get a wave within the surface.

So this little video animation I'm about to show you was both the most exciting and the most depressing moment of my scientific career.  Okay, again, so every dot is a person.  Every line between them is a relationship.  Again we make the dot size proportional to people’s body mass index, so bigger dots are bigger people and we color the dots yellow if they are properly obese, if their BMI is above 30.  The red perimeter dots are woman and the blue perimeter dots are men, but you can ignore that for now and on this image we only show two kinds of relationships.  The gray lines indicate spousal connections and the purple lines indicate friendship connections, so two people connected by a line who have the same body size it’s not because are brother and sister or father and child and they share genes in common.  These are purely volitional social relationships and so in a minute we’re going to take—put this network into motion.  We’re going to take daily cuts through the network for 32 years, every single day, evaluating the structure and status of the network and what you’re going to see across time is you’re going to see people be born and die.  Image nodes are going to appear and disappear.  You’re going to see relationships form and break.  You’re going to see marriages and divorces, friendings and de-friendings, the real old fashioned kind of de-friending, not the Facebook kind of de-friending and you’re going to see people, dots get bigger and smaller as people gain and lose weight.  Mostly you’re going to see the dots getting bigger and you’re going to see a sea of yellow because this period of time from 1971 to 2003 includes the period of the obesity epidemic and when you look at this image I want you to tell me or I want you to—and when you look at this image I want you to think about, as we were thinking about, could we see a wave, evidence of spread in the image.

So here you go.  

Okay, so as you see this image we begin in 1971.  You’re going to see the network evolve across time.  You’re going to see lots of relationships form.  The epidemic is going to begin to peak in the sort of late 1980s, 1990s.  You’re going to see more and more people become yellow.  You’re going to see people move around.  At some point you’ll see some particular individuals get bigger and sort of move to the center of the network and by the end you’re going to see mostly yellow, but you’re going to see clusters of yellow and green nodes within the network indicating clusters of obese and non obese individuals.

Okay, so if you look at this little movie what you can see is, is that every dot is a person.  Every line between them is a relationship between the two people and here we only show two kinds of relationships, not genetic relationships.  The gray lines show spousal connections and the purple lines show friendship connections and we make the dot size-

So here we begin in 1971.  You can see a lot of people.  The relationships are changing.  People are marrying and divorcing each other, friending and de-friending each other, real de-friendings, the old fashioned kind again and you can see people are gaining and losing weight.  You’re going to see a sea of yellow.  We’re approaching now the growth of the epidemic.  You saw that one person gained a lot of weight and moved to the middle of the network there.  Now we’re in 1991, 1993.  We’re looking at the network as it changes.  Most of the people are gaining weight.

Okay, so now you’re seeing the network evolve.  People are marrying and divorcing each other, friending and de-friending each other.  You’re going to see people gain weight and lose weight.  Mostly they are going to gain weight.  You’re going to see a sea of yellow.  That woman up at the top there at 12:00 she is gaining a lot of weight now.  She is moving right to the middle of the network.  Now you’re going to see the growth of the epidemic.  You’re going to see mostly a sea of yellow at this point in time as the epidemic is really kicking off and we’re approaching the end of the animation now in just a moment and by the end you can see that there are clusters of obese and non obese yellow and green sectors within the network.

But when you look at this the question is did you see this wave or not and we didn’t’ see it.  Like I said this was both the most exciting and the most depressing moments of our scientific careers because we were convinced that if we went to the trouble to collect these data and make this type of image after five and a half years of effort we would be able to see this wave, but when we looked at this we didn’t’ see it and it took us a whole day to figure out why and the reason is that obesity is not a uni-centric epidemic.  It doesn’t have a point source.  It is a multi-centric epidemic.  It has many sources and the proper analogy is not a single pebble being dropped on the surface of a pond, but a whole handful of rocks being thrown on the surface.  Every rock falling plunk, plunk, plunk makes these little concentric waves, but the waves interfere with each other and you get this choppy surface, this chop on this socio-topological surface, this hyper dimensional object that is a social network.

So there are kinds of statistical and mathematical tools are required to discover or uncover the extent to which there is a wave and using these tools we were eventually able to show just the—and using these tools we were eventually able to show this type of influence from person to person within the network.

But the interesting thing as we made this image was that it totally shifted my perspective on what was happening here because I came to see the world differently.  This network when you look at it, it moves.  Things flow within it.  It changes and evolves.  It is resilient to injury.  It has a memory.  It has a kind of a coherence and an endurance across time.  I came to see social networks as living things, as a kind of human super organism.  They have a life of their own of which we are all a part and you and you can think of human beings in this way as having these kinds of properties, these emergent properties because we partake of this bigger whole.  Because we are a part of this other living thing you can think of us as being constituent parts of it and our membership in this bigger thing affects us just like the point Durkheim was making earlier about the suicide rates in France in the 19th century.

Now what might be a possible mechanism of the spread?  How might we be affected or how might obesity be spreading from person to person?  One possibility is that the alter, the other person, the alter’s appearance or behavior could change the ego, that would be me, the ego’s behavior.  So the alter is over there and I'm the ego.  They change their appearance or behavior and that spreads and affects my appearance or behavior and an alternative idea is that the alter’s appearance or behavior changes my expectations or perceptions of norms, so here what spreads from person to person is not a behavior, but rather an idea.  

So now what might be some possible mechanisms that might explain the spread of obesity?  One possibility is that the alter’s appearance or behavior could change the ego’s behavior.  So here the idea is that your friend, the alter says let’s go have muffins and beer, which is a terrible combination, but your friend suggested it, so you agree and you adopt your friend’s muffin and beer eating behavior and this contributes to your obesity.  

A second possibility is that the alter’s appearance or behavior changes the ego, that’s you—a second possibility is that the alter’s appearance or behavior changes the ego’s expectations or norms.  Here what spreads from person to person is not an actual behavior, but rather an idea.  So as your friends gain weight it changes your idea about what an acceptable body size is and so willy-nilly you follow suit and you gain weight as well.

So now what might be some possible mechanisms or explanations of the spread of obesity?  So here we might think of the alter, that is the other person and the ego, that is you.  So one possibility is that the alter’s appearance or behavior could change the ego’s appearance or behavior, so for example, your friends say let’s go have muffins and beer.  That is a terrible combination, but your friend suggested it, so you copy your friend’s behavior and you gain weight as a result of the muffin and beer diet that you have assumed.

A second possibility is that the alter’s appearance or behavior changes your expectations or perceptions of norms.  Here what spreads from person to person is not a behavior, but rather an idea and when we analyzed our data we found evidence for both sorts of phenomena.  We found some suggestive evidence that as the people around you change their body size it resets your expectations about what an acceptable body size is and so you go on to gain weight or lose weight accordingly as well.

Now many social sciences take people’s tastes and desires as a given and they try to figure out why people do what they do given that they have particular tastes or desires.  How do they maximize their utility?  But one of the distinctive ideas of sociology is that it seeks to understand where do these tastes and desires come from in the first place.  Why do you want what you want?  Why do you desire what you desire?  And in part it turns out that our desires and our wants are determined by the collective, are determined by the groups of which we are members and longshoreman and social critic Eric Hoffer once opined, “When people are free to do as they please they usually imitate each other.”  Our choices and experiences depend on what other around us are doing and feeling from obesity to smoking to voting or even to our emotions and in a sense this means that we have less free will than we think we might have.

Now this sort of interpersonal influence and these sorts of network affects can be shown experimentally too, not just using the kinds of observational data I have shown you so far.  To give another illustration of how we are affected by those around us and to get around some of the potential problems of using observational data to study social processes and try to make causal claims to try to really nail down what is happening here it’s very helpful to also do experiments where you randomly assign people to interact with each other in controlled environments to see can you find evidence that we are actually affected by other people even in potentially important and counterintuitive ways.

So one experiment that I'm going to who you involved taking 240 college students and having them play a game in which they were each given a little bit of money and if they contributed the money to the group, they were randomly assigned to interact with three strangers in groups of four, if they gave a little money to the group the experimenter would multiply the money so the group would be better off even though the individual paid a price and the question was could we find evidence that people were affected by the behavior by the altruism of other people to whom they were connected.

So here is an illustration of how the experiment is set up.  So at period one, which is shown in the far left column there are six groups of people shown here and person A plays with persons B, C and D and person E plays with persons F, G and H and so forth on down the column.  Then a bell will—they play this contribution game.  Then a bell rings and they are randomly assigned to play with new people and then a bell rings and they are randomly assigned to play with new people and so it keeps going for a number of rounds and what can happen is if you can take these data and you can reconfigure them to be a kind of social network.  

So for example, you can see that the ego, person A on the far right there previously had played with individuals E, I and M, the alters and those individuals had previously played with the alter’s alters F, G and H, J, K and L and N, O and P, so you can ask yourself the question how does F’s treatment of E affect E’s treatment of A.  Do people learn if I'm kind to you, I'm not asking do you reciprocate the kindness and are kind back to me.  I'm asking if I'm kind to you do you then go onto be kind to others?  Can there be a kind of pay it forward phenomena within social networks?  Do people’s altruistic impulses, do they depend in part on the behavior of other people around them with whom they are interacting and in fact they do.  

It turns out that if you take this kind of network data you can map it and get this kind of an image here, so for example, what you can see is that Eleni [ph] in period one, if she is kind to Lucas, Lucas learns to be kind and then goes onto be kind to Erica and Erica is kind to Jay and Jay is kind to Breckon [ph].  You have a spread to three degrees of separation in this experimental network of altruistic behavior.  You can see the signature of Eleni’s kindness to Lucas, in Jay’s interactions with Breckon even though neither Jay nor Breckon ever saw or interacted with Eleni or Lucas.  Things have literally—you can literally show the spread of this kind of altruistic behavior through the network and that is different than the persistence across time.  There is the spread across people shown in the red outline and there is then a persistence across time shown in the yellow outline, which is that if Eleni is kind to Lucas, Lucas learns to be kind and he goes onto be kind to Erica in period two and to Lisander [ph] in period three and to Bemi [ph] in period four and to Sebastian in period five and to Nicholas in period six.  So Lucas learns to be kind and continues to be kind with other people because Eleni treated him kindly initially and it turns out if you compute all the downstream kindness that arose because of Eleni’s kindness to Lucas the network functions like a kind of matching grant doubling the net benefits for Eleni’s initial altruistic behavior with respect to Lucas.

So this affect thus spreads across people and also as a separate matter persists across time and when all the ripples through this network are added together you get much more benefit to the collective than the sum of the—of then the consequence of the individual benefits from the first person’s behavior.

And when all these ripples are added together it is clear that the network—I already said that.  This affect thus spreads across people and also as a separate matter persists across time and you can see that the group as a whole benefits out of proportion to the individual behaviors or individual contributions of the constituent people. Okay, now one can also ask other deeper questions like why do social networks look the way that they do.  They always kind of look like the image I showed you earlier of the obesity network, but they never look like this picture.  They never look like a regular lattice.  Why don’t we live our lives in this kind of a structure?  Why don’t we make networks that look like this?  Well the striking patterns of human social networks their ubiquity and their apparent purpose beg the question of whether we have evolved to have them and to have particular kinds of networks in the first place.  So now the question has become why do we form networks in the first place—and so now the question has become why do we form social networks in the first place and why do they have the structure that they do and to understand this we need to dissect network structure a little bit first.

So first of all, notice that in this network every position is the same as every other position.  Everyone has eight friends.  Every one of their friends in turn has eight friends and if you took this surface and you wrapped it around the surface of a donut, or a **** there would be nobody that was anymore towards the edge or towards the middle of the network.  Everyone would be equally distant from the edge, but real social networks look entirely different.  They look kind of like this image of 105 college students at a diverse American university and so in fact if you look at this image you can see the two nodes B in the upper left and D in the far right you can see that they are different because they have a different number of connections.  B has four friends and D has six friends and if you talked to them they would be aware of this difference.  You could see the difference between the two people and they themselves would be aware of this difference, but there are other aspects of the network and the location within the network that are less obvious.  

Okay, but that is not the case with natural social networks.  Natural social networks are very different, so for example, if you look at this network you can see that different individuals have different kinds of locations within the network.  Consider for example individuals B and D, B in the upper left and D on the far right.  So B has four connections and D has six connections and if you talked to those individuals they would know this about themselves.  I have four friends.  I have six friends.  I have no friends.  I have 10 friends.  People know this about themselves and that is obvious, but there are other aspects of our network that are less obvious.  For example, compare, contrast nodes A and B.  They are different.  They both have four friends, but A’s friends are by and large friends with each other and B’s friends are not friends with each other.  This is known as transitivity.  The friend of a friend of A’s is back again a friend of A’s, but the friend of a friend of B’s is not a friend of B’s.  It reaches further within the network.  And finally look at C and D.  C is in the middle and D is on the far right.  They both have six friends, but you can see that there is something different between the two of them.  C is in the center of the network and D is to the edge of the network and the bird’s eye view of this sort makes these differences apparent and it turns out that where you are located within a social network depends—Scratch that.  I'm going to go back to C and D.

And if you look at C and D you can see that they are different.  They both have six friends, but there is something different about C compared to D and I can cultivate this intuition in you by asking you who would you rather be if a deadly germ was spreading through the network.  You would rather be D.  You should have the intuition that it is better to be on the edge of the network because that person would be less likely to get what is spreading and if they get it are more likely to get it later in the course of the epidemic.

Now let me ask you who would rather be if a juicy piece of gossip were spreading through the network?  Now you would rather be C, be in the middle of the network and get it and this can be formulized mathematically the difference between these individuals and it is known as I said as their centrality and this bird’s eye view of the network makes these sorts of differences apparent and it turns out that where you’re located within the network whether you are A, B, C or D or types of individuals like that depends in part on your genes.  Again depending on the circumstances faced different positions are different, so people often say, “Well what is the best location in the network?”  The answer is it depends.  If a germ is spreading through the network it is better to be in one place, if information about where to find a job is spreading through the network it is better to be in another place.  

So you can think of networks as a kind of vast fabric of humanity and we all occupy particular spots within the network.

There is another way that social networks affect us.  It is not just what is happening to the people around us that might ripple through the network and affect us.  It is the actual structure of the network itself.  Now think about these two objects.  They are both made of carbon, but if you look at the structure of the objects the graphite on the left is made of carbon atoms assembled and connected one way and the diamond on the right is made of carbon atoms assembled and connected another way.  So you connect the carbon atoms one way and you get graphite, which is soft and dark and you connect the carbon atoms another way you get diamond, which is hard and clear and there are two key intellectual ideas from this observation.  First, these properties of softness and darkness and hardness and clearness do not adhere in the carbon atoms.  They are not properties of the carbon atoms.  They are properties of the collection of carbon atoms.  Second, which properties you get depends on how you connect the carbon atoms to each other.

 Connect them one way you get one set of properties.  Connect them another way you get a different set of properties and similarly the pattern of our connections with each other affects the properties of groups.  It is the ties between people that make the whole greater than the sum of its parts.  New properties emerge because of the connections between people, because of the ties between people and not necessarily because of the people themselves and in fact our experience of the world depends in part on the actual structure of the social network ties around us and this is like the artificial networks we saw at the beginning of the bucket brigade and the telephone tree.  You take human beings and you assemble them one way.  You get one set of properties.  You assemble them another way.  You get a different set of properties just like the carbon example.

Now there is another example, a real life example now of how network structure might matter distinct from what is flowing through the network and this is some work that was done by Brian Uzzi and North—so here is a more specific human example of how social network can affect the constituent individuals.  This is some work done by Brian Uzzi, a sociologist at Northwestern University.  He became very interested in Broadway musicals and why some Broadway musicals are a big success and other Broadway musicals are a total disaster and what did is he put together a sample of over 300 Broadway musical production companies and he looked at the structure of the production company, the network structure and assessed how it was associated with the financial success and the critical acclaim of the Broadway shows that those companies put on and if you look at this on the far left, imagine we have a production company of one person in the middle and five people surrounding that individual and we look at the social network ties and this individual in the middle is connected to five other people. 

So here you see three cartoon images of how the networks might be assembled.  On the far left you see that there is a central individual connected to five other people and amongst those people there can be five times four divided by two, ten possible connections and in there cartoon on the left you see there are none of those connections.  Zero of ten of the ties are present and we would say that there is zero percent density in this network.  On the cartoon on the far right you might see that all 10 of the ties are present, so you have 10 out of 10, 100% density and density is sort of like transitivity that we were talking about earlier and in the middle you see that 4 of the 10 ties are present, so you have 40% density and what Uzzi did was he plotted on the graph shown with a parabola he plotted on the X axis the density of the Broadway musical production company and on the Y axis how successful the Broadway musical was, how much money did it make and how many favorable reviews did it get and as you see by the parabolic shape on the left if you have a network in which nobody knew each other from before the show was a flop and at the other extreme if you see that everybody knew each other from before the show was a flop, but in the middle if some of the people knew each other from before and some of the people didn’t know each other from before, if there was intermediate density the show was a big success, so what seems to matter here is it is not just the individuals putting on the show.  It is the structure of the network that affects the likely success of the show and Uzzi has gone on to show that there are similar work or similar findings with respect to scientific collaborations in other sorts of groups that people can assemble.

Okay, now it turns out we’re not the only species that assembles ourselves into networks and gives rise to others sorts of special properties and so to push this point home, this point about emergence, this idea that collectivities can have properties that are not present in the individuals themselves let’s consider a further example.  This is a slime mold.  It is a primitive amoeboid fungus and all this fungus does I digest wood, so this thing lives on the forest floor and if you have ever lifted up like a pile of leaves in the fall and they are wet and soggy and you see those little white tubes under that is what this thing is doing.  The little fungus forms connections to other nearby fungi.  They fuse and they make these long tubes and they digest wood and they distribute the waste from their digestion through these tubes.  But it turns out individuals of this species in connecting to each other form a kind of super organism with unexpected properties.  

For example, they can solve mazes.

So if you take a maze and you put it on a kind of **** plate and you put food at two different spots, the entrance and the exit to the maze and by food here I mean something like wood or like an oat flake.  If you put oat flakes at the entrance or the exit of the maze this simple organism will change its shape and connect to the two sources of food by finding the minimum path length solution between the two points.  If parts of the organism are spread out on the gel they will reassemble to form a kind of single super organism and so it **** a kind of maze solving property, a kind of primitive intelligence that is not present in the individual organisms themselves and this work was done by a Japanese mycologist by the name of Toshi Nagagaki [ph].

So here you are.  Here is the maze.  The amoeboid fungus is bubbling up and connecting to each other.  There is the oat flakes at the entrance and the exit.  It is surrounding the whole plate and you’re going to see that all the paths are going to die back except for the one shortest path through the maze.  In fact, this amoeboid fungus is better able to solve mazes then Toshi’s graduate students, not better than my graduate students thank goodness.  It is able to find the shortest, most efficient path through the maze.  It is able to find the shortest, most efficient path through the maze.  This maze solving ability is an emergent property of the amoeboid fungus.

So it is obviously not a single amoeboid fungus that is solving this maze.  It is the fungi working collectively that give rise to this property, this maze solving ability that emerges from their interactions.  Obviously if you ask can this amoeboid fungus solve a maze the answer is no, but the maze solving ability emerges as a result of the interactions.  In fact, you can use this kind of maze solving ability or this ability to find the optimal paths to do other sorts of things like here we show an image on the left is the rail network designed by human beings in England and on the right is some work done by my colleague Mark Fricker [ph] at Oxford University.  He took the map of England and he put little oat flakes at every city and he plated the amoeboid fungus and the amoeboid fungus gave rise to a path connecting or a set of paths connecting the oat flakes that actually imitated and in many ways was better than the rail network the human beings had designed over 200 years, so if you look at these two things side by side you see that the fungus is able to design a railway system for England, in fact, a better system than the one that they have.

Still what is the point of a connected life?  How does it help us as an individual or as a species?  It turns out that social networks are a resource that we can all use.  They are a kind of social capital.  Now most people when they think about capital think about money, but really capital is any stock of resources that can be put to productive use.  Two further key ideas, one of which is quite subtle—two further key ideas about capital are that in order to create capital you have to invest skill and effort.  You have to know something and do something in order to acquire capital and second and more subtle you have to work upon the world and transmute it.  You have the change the world.  You have to introduce changes in a substance that makes it more productive than it was before, that makes it capable of yielding a higher rate of return than it was able to do before.

So for example, think about this.  You can have a forest.  You can invest skill and effort.  You can clear the forest and you can make a farm and this farm is a stock of capital.  It is more productive at least in terms of fruits and vegetables and grains than the forest was and by investing skill and effort and working upon the land and changing the land you have created a reservoir of wealth, something that is capable of doing something that wasn’t—you have created a reservoir of wealth, something that is capable of being used in a fashion that wasn’t possible before, so land and especially improved land is a form of capital.

Or think about this idea.  You can take this tree.  You can invest skill and effort and you can transmute the substance of the tree and mill it into lumber and the lumber is more valuable than the tree.  It is a reservoir of wealth.  It is a stock of capital and you can do things with the lumber that you couldn’t do with the tree like make a violin.  You can invest still more skill and effort and convert the lumber into a violin, which is more valuable than the tree because it reflects this additional investment of skill and effort and because in having changed the wood even more you’re now capable of doing things with the violin you couldn’t do with the lumber like make music.  So capital is a change that allows a substance to act in new ways and this is part of what makes it a store of wealth and a source of productive power.  

Now in the 1960s a key innovation in thinking took place spearheaded primarily by economist Gary—so a key—now a key innovation in thinking—now a key innovation in thinking among social scientists took place in the 1960s spearheaded primarily by economist Gary Becker to begin to think about human beings as a form of capital, as a form of human capital and the chief example of this is education.  If we endow someone with skills and knowledge we have changed them and they have become more productive.  So if you look at this sort of dissolute graduate student of mine on the far left you can invest skill and effort.  You can clean him up so that he is no longer a drunkard and now he is capable of doing things he wasn’t capable of doing before or you can invest still more skill and effort and give him an education and now he is even more able to do things he wasn’t able to do before.  So you have changed the substance of his mind.  You have reworked the real world.  You have taught him things.  You have changed his brain and made him more productive and more capable of doing things that he wasn’t previously able to do.

Now just like physical capital is created by a change in the material world and human capital is created by a change in persons social capital is a change in the relations among persons, a change the renders the group more productive and capable of doing things it wasn’t previously able to do, so social capital can arise in at least two senses when we think about social organization.  First we can think in terms of what is flowing through the group and across these connections.  Is information flowing?  Is germs flowing?  Is information flowing?  Are germs flowing?  Are emotions flowing?  Is altruism flowing?  Is this the kind of network in which desirable things are flowing through the system?  Is this the kind of group in which positive things are primarily moving first?

Second, social capital can arise in a second sense, which is how the groups of individuals are organized or connected in the first place.  This idea or the idea is that social capital is a property of a collection of individuals—the idea is that social capital—the idea is that social capital is a property of collections of individuals, a property that did not exist before the individuals were assembled into the kind of network group.  Moreover, the idea is that social capital is a property of collections of individuals, a property that did not exist before the people were assembled into this network and moreover, a property that does not adhere within the individuals themselves.  It is a property of the collection of individuals again illustrating the idea of emergence that we have been discussing.

Now this idea was best advanced by sociologist James Coleman, but related ideas are found in the work of Robert Putnam and Pier Borduex [ph] and Coleman’s perception differs from Borduex’s and Putnam’s conception in a number of ways.  Borduex tends to see social capital as residing within individuals and is more like what I would consider to be cultural capital and Putnam’s perspective stresses the important role of official or formal institutions, whereas, Coleman’s perspective on social capital is a bit more organic like what we have been seeing, that social capital arises because of the interactions between people that almost naturally take place, that are a part of our very fabric as social animals.

Now one of the important aspects of social capital is that it is a public good.  Now a public good is one in which there is no exclusivity in consumption.  So everyone can benefit from it.  Think about the difference between this cake and this lighthouse.  If you have a cake there are two things you can do with it that are relevant to what we’re discussing right now.  First of all, you can prevent anyone else from eating the cake.  It is your cake.  No one else can touch it.  And second, if you eat the cake there is none of it left for either you or anyone else to use, but think instead about the good that is the light that comes from the lighthouse.  Your using that light to avoid crashing on the shore doesn’t prevent anyone else from using the light, not only that, but there is no way to consume the light.  There is no way to use it all up.  More light is there, so this good is totally different than the cake and that is the kind of aspects or those are the kinds of properties that a public good like a lighthouse has.  It is a good in which there is no exclusivity of consumption and in which the good is sort of inexhaustible.  This is not right.

So a public good is one in which there is no exclusivity in consumption and everyone can benefit from it and public goods typically arise by accident and social capital may be—and public goods typically arise by accident.  Maybe one group of people puts up the lighthouse because they are really concerned about it, maybe a port authority or a private entity that is concerned about their ships not crashing, but now that they have put it up everyone can benefit and their benefits do not reduce the ability of the intended individuals to benefit.

Social capital is sort of like that.  It is a public good.  It arises by accident from people’s interactions with each other.  It is not a deliberate thing that we do.  We don’t set out to make it and once we create it though everyone can benefit from it.  Social scientists have developed a number of overarching approaches to understanding human behaviors in human society.  One classic way of understanding collective behaviors is to look at individuals themselves.  For example, we can see markets or elections or riots as the mere byproduct of individual’s decisions to by and sell goods, to vote or to express anger and the classic example of this approach, which is known as methodological individualism is provided by Adam Smith’s conceptions of markets where each individual transacting their business as if guided by an invisible hand gives rise to a kind of an efficient market where each individual acting in the furtherance of their own interest as if guided by an invisible hand gives rise to markets.

Now another classic way of understanding collective human behavior dispenses with individuals and focuses on groups, groups with collective identities that cause people within the groups to act in concert.  Some scholars in this tradition like Karl Marx even believe that groups can have their own consciousness imbuing them with a kind of indivisible personality that cannot be deduced or understood from the actions of its members. 

Others have also focused on the primacy of group culture.  For example, as we saw sociologist Emile Durkheim argued that the relatively constant rate of suicide within particular religious groups and in particular places at particular times could not be explained by the actions of individuals and must be properly understood as a property of the collective, as a property of the groups.  How was it he wondered that people came and went, but the suicide rate in French Protestants stayed the same.  This is known as methodological holism and this approach sees collections, sees groups, sees society as being distinct from the individuals, distinct from the constituent individuals and sees society and groups as having properties that cannot be deduced merely from studying the constituent individuals.

Now in the 20th century social scientists often focused on how membership in particular kinds of groups having particular kinds of attributes such as race or class for example could explain the behavior of the individuals within them.  Now in the 20th century many social scientists focused on how membership of individuals within groups denoted by particular attributes or characteristics, for instance, race or class affected or helped determine the behavior of those individuals and maybe gave rise to collective phenomena, but the social network approaches, some of which we have been discussing today offer a further way of understanding human society and in fact a way perhaps best suited for the 21st century.

Social networks are about both individuals and groups and in fact they are about how individuals become groups by connecting to each other.  Interconnections between people can give rise to phenomena that are not present with individuals themselves and that are not reducible to the solitary desires and actions of the individuals.  

The issues of social capital and emergence and the phenomena of social networks illustrate the issue of how we explain social phenomena, so methodological individualism seeks explanations for social phenomena such as social class, markets, power, institutions and so forth by saying that they must be formulated as or reducible to the characteristics or actions of individuals.

Methodological holism on the other hand sees each social entity, a group or institution or a network as having a totality that is distinct from and that cannot be understood by merely studying the individual component elements.  So for example, you can understand markets perhaps by using a methodological individualistic approach, but if you’re interested in understanding market bubble or panics you might need a more methodological holism approach and the methodological holism also refers back to the example, the carbon example-

The issues of social capital and emergence and the phenomena of social networks that we have been discussing illustrate the issue of how we can come to explain social phenomena using alternative approaches.  On the one hand we have methodological individualism.  Here in this perspective, explanations for social phenomena such as social class, markets, power, institutions and so forth must be formulated as or reducible to the characteristics or actions of individuals.

On the other hand we could have methodological holism.  Here this perspective sees each social entity, group, institution or network as having a totality that is distinct from and that cannot be understood by merely studying its individual component elements.  So for example, we may be able to understand markets by using an approach of methodological individualism, but if we want to understand market panics or bubbles we probably need an approach that uses methodological holism and holism in fact, as you probably have gathered is related to emergence.  Various social phenomena, for example, culture can have an enduring reality that transcends individuals and Durkheim for example argued that social facts can and must be studied by looking at groups of individuals, not individuals themselves.

Social capital is complicated because certain aspects of it arise as byproducts of individual actions, so it is true that individuals choose their friends, but in choosing their friends they give rise to a collection, a network that has its own properties, so while the individuals contribute in some sense to the emergence of this phenomenon they are not a part of the phenomenon.  The phenomenon is distinct from the individuals and in fact, in some ways you can think about the study of social networks as illustrating something else, another big idea because it is part of a much broader—and in fact the study of social network illustrates something else—and in fact the study—and in fact the study of social networks illustrates something else.  It is part of what I call a much broader assembly project of modern science. 

For the last 400 years swept by a reductionist fervor and by considerable success scientists have progressively dissected matter into ever smaller bits, so we disassembled life into organs and then cells and then molecules and then genes and we disassembled atoms—and we disassembled matter into atoms, then nuclei, then subatomic particles and we have invented everything from microscopes to super colliders to study ever smaller bits of matter, but across many disciplines right now scientists are now trying to  put all the parts back together again whether they’re trying to put—but across many disciplines right now scientists are trying to put the bits back together again whether it is macro molecules into cells, neurons into brains, species into ecosystems, nutrients into foods or people into networks,  Scientists are changing-

Scientists are turning their attention into how and why the parts fit together to make the whole and how interconnection can give rise to properties that aren’t present within the component parts.  Understanding the structure and function of social networks and the phenomenon of emergence within social networks is thus part of this larger scientific movement.

But sociology has always been doing this.  It has always sought to put the parts back together and to make a bigger whole.  It has always realized that the whole is greater than the sum of its parts.  Moreover, sociology has always emphasized—moreover, sociology has always emphasized the ways in which actually the parts have properties that are not present within—moreover, sociology has always emphasized the extent to which we are not in fact masters of our own destiny and in this regard sociology touches on ancient philosophical concerns such as free will.

Because what—and in this regard sociology has concerned itself with another ancient philosophical concern, namely, the issue of free will because sociology is interested in the ways in which what happens to you aren’t just a product of your own agency.  Don’t just depend on your own choices and actions, but depend on broader structural factors outside of your control like the race of your parents or your birth order or your birth weight or the talents you happen to be born with or super structural factors such as the networks you belong to or which country you were born in or the relative wealth of these countries or the culture of these countries or the other attributes that surround you that you as a part of now come to partake of and as a result determine your destiny just as much as your own individual choices and actions.  

It is the tension between structure and agency that we opened with.  To what extent do our destinies depend on our own behavior and to what extent do they depend on these larger factors that we have been discussing today?

In other words, how does what happened to—in other words how does what happens to you depend not just on what you choose to do, but what others choose to do and what the whole society around you and the whole culture around you dictate as your destiny above and beyond what you dictate as your own destiny.

And the field is only going to get better.  Look, if you had asked social scientists even 20 years ago what was their fantasy of the ideal kind of data that they could have they would say oh my goodness we would love it if we could have these little tiny helicopters that were microscopic and invisible and they flew on top of every person and they monitored this person 24 hours a day looking at what this person was buying, what this person—who this person was interacting with, where this person was, what this person was thinking and if they could do this for millions of people in real time that would be amazing.  We would have a kind of data that would allow us to understand society and individual behavior in a way we never could before, but of course that is what we have now.  In our everyday use of cell phones and credit cards and online networks and blogs and all these administrative records that we leave behind us we leave these little digital breadcrumbs as we move about our lives that can be pulled together and studied using new analytical and computational tools that give us whole new insights into how and why society operates.

So for example there all kinds of such pervasive data that are available nowadays, telephony data, internet data, video cameras in cities, RFID devices in all kinds of products and other places, administrative records regarding emergency room visits or crimes, transactions records, geographic information, voluntary losses of anonymity, people participating in citizen science and contributing their information for others to use or even personal genetic information.

And the availability of all these new kinds of data heralds the onset of a new kind of computational social science.  The availability of data of this kind is only increasing and will continue to increase and these data properly analyzed and with the proper concern for research—and these data properly analyzed and subject to the—and these data properly analyzed and subject to ethical rules can allow us to understand and address all kinds of important social problems from violence to poverty to epidemics to political extremism.

In 1969 sociologist Morris Zelditch asked rhetorically can you really study an army in the laboratory and nearly half a century later the answer appears to be yes and this will offer us all sorts of new opportunities and raise new questions both intellectual and philosophical about how and why humans and the groups they form do what they do.  

Nearly half a century later the answer appears to be yes and this will raise all sorts of questions both intellectual and philosophical.  Nearly half a century later the answer appears to be yes and this will offer all sorts of new opportunities both intellectual—and this will offer all sorts of new opportunities and raise all sorts of new question both intellectual and philosophical about how and why humans and the groups that they form do what they do.  If you want to understand all this and be a part of all this then you need to understand sociology.  If you want to understand all of this and be a part of this then you need to understand sociology. 
 
This will offer all sorts of new opportunities and raise all sorts of new questions both intellectual and philosophical about how and why human—this will offer all sorts of new opportunities and raise all sorts of new questions both intellectual and philosophical about how and why humans and the groups that they belong to do what they do.

If you want to understand all of this then you need to understand sociology.  Thank you.    

Early life

Christakis' parents are Greek. They had three biological children and then adopted two others, an African-American girl and a Taiwanese boy.[9] His father was a nuclear physicist turned business consultant and his mother a physical chemist turned psychologist.[10] He was born in New Haven, Connecticut in 1962 when both his parents were Yale University graduate students. His family returned to Greece when he was three, and Greek became his first language. He returned to the United States with his family at age six and grew up in Washington, D.C.[11] He graduated from St. Albans School (Washington, D.C.).[9]

Education

Christakis obtained a B.S. degree in biology from Yale University in 1984, where he won the Russell Henry Chittenden Prize. He received an M.D. degree from Harvard Medical School and an M.P.H. degree from the Harvard School of Public Health in 1989, winning the Bowdoin Prize on graduation.

In 1991, Christakis completed a residency in Internal Medicine at the University of Pennsylvania Health System. He was certified by the American Board of Internal Medicine in 1993. He obtained a Ph.D. degree in sociology from the University of Pennsylvania in 1995. While at the University of Pennsylvania as a Robert Wood Johnson Clinical Scholar, he studied with Renee C. Fox, a distinguished American medical sociologist; other members of his dissertation committee were methodologist Paul Allison and physician Sankey Williams. His dissertation was published as Death Foretold, his first book.[12]

Career

In 1995, Christakis started as an assistant professor with joint appointments in the Departments of Sociology and of Medicine at the University of Chicago. In 2001, he was awarded tenure in both Sociology and Medicine. He left the University of Chicago to take up a position at Harvard in 2001. Until July 2013, he was a professor of medical sociology in the Department of Health Care Policy and a professor of medicine in the Department of Medicine at Harvard Medical School; a professor of sociology in the Department of Sociology in the Harvard Faculty of Arts and Sciences; and an attending physician at the Harvard-affiliated Mt. Auburn Hospital.[13]

In 2013, Christakis moved to Yale University, where he is a professor of social and natural science in the Department of Sociology, with additional appointments in the Departments of Ecology and Evolutionary Biology; Statistics and Data Science; Biomedical Engineering; Medicine; and in the School of Management. He served as the Sol Goldman Family Professor of Social and Natural Science until 2018, when he was appointed as a Sterling Professor, the highest honor bestowed on Yale faculty.

From 2009 to 2013, Christakis and his wife, Erika Christakis, were Co-Masters of Pforzheimer House, one of Harvard's twelve residential houses.[14] From 2015 to 2016, he served in a similar capacity at Silliman College at Yale University.[15]

Research

Christakis uses quantitative methods (e.g., experiments, mathematical models, and statistical analyses). His work focuses on network science and biosocial science, and it has also involved sociology, economics, demography, evolutionary biology, evolutionary psychology, behavior genetics, and epidemiology. He is an author or editor of six books, more than 200 peer-reviewed academic articles, numerous editorials in national and international publications, and at least three patents.[16][17][18] His laboratory is also active in the development and release of software to conduct large-scale social science experiments, pioneering its use beginning in 2009 (e.g., Breadboard, Trellis).[19][20]

Christakis' early work was on physician decision-making and end-of-life care. He first began to study interpersonal social network effects in this setting in the late 1990s, with a series of studies of the widowhood effect, whereby the death of one person might increase the risk of death of their spouse.[21][22] He developed a number of innovative ways to estimate the causal nature of these effects (e.g., by studying how the death of a man's ex-wife might affect his risk of death),[23] and he expanded the scope of such work to analyze, for instance, how the precise diagnosis or duration of illness of the decedent might modify the risk of death of their survivor or how better quality of health care given to a dying person might reduce the risk of death of their survivor.[24][25] He also explored, in a 2006 paper in The New England Journal of Medicine that analyzed 518,240 elderly couples, how hospitalization of a spouse, and not just their death, might affect a survivor's mortality risk.[21] These were all early studies in network effects, but they involved just simple dyads of people (pairs of spouses).

Beginning in 2004, Christakis began to study "hyper-dyadic" network effects, whereby processes of social contagion moved beyond pairs of people.[26] Initially using observational studies with his colleague James H. Fowler, he documented that a variety of phenomena like obesity,[27] smoking,[28] and happiness,[29] rather than being solely individualistic, also arise via social contagion mechanisms over some distance within social networks (see: "three degrees of influence").[30] Other work by Christakis and Fowler, and by Christakis and other collaborators, used experimental methods and diverse data sets and settings to study social networks, thereby enhancing the robustness of causal inference (e.g., in a 2010 paper that showed that altruistic behavior in college students, or in a 2015 paper that showed that vitamin use in developing-world villages could both be made to be contagious).[31][32][33][34][35] Indeed, the 2010 experiment demonstrated that cooperative behavior could spread to three degrees of separation.[31] A 2022 paper used another experiment to show how a novel "pair targeting" algorithm could enhance population-level social contagion of the adoption of iron-fortified salt to reduce anemia in mothers and children.[36] A randomized controlled field trial involving 24,702 people in 176 villages in Honduras published in 2024 documented social contagion in a health behavior intervention to two degrees of separation.[37] In a 2010 TED talk, Christakis summarized the broader implications of the role of networks in human activity.[38]

In addition to studying how diverse processes, ranging from cooperation to emotions, obesity, resource sharing,[39] and vaccination,[40][41] might spread across social networks, Christakis and his colleagues have published a series of papers exploring how experimental manipulation of social network structure itself might enhance human welfare. Early work, starting in 2011, focused on how experimental manipulation of network structure could enhance human cooperation and economic productivity.[32] Other work explored how network topology could affect human communication during a time of crisis.[42] A 2019 paper in Proceedings of the National Academy of Sciences of the United States of America (PNAS) showed that experimentally re-wiring social networks could enhance human welfare without either redistributing or increasing resources.[43] Additionally, an observational study of a novel monetary system (Sardex, a complementary currency introduced during the 2010 financial crisis) showed that k-cycle centrality was associated with economic success at the level of individual firms or the system as a whole.[44]

In 2009, Christakis' group began to study the evolutionary biology and genetics of social networks, publishing in PNAS a finding that social network position may be partially heritable, and specifically that an increase in twins' shared genetic material corresponds to differences in their social networks.[45] In 2011, a follow-up paper on "Correlated Genotypes in Friendship Networks" in PNAS advanced the argument that humans may be metagenomic with respect to the people around them.[46] Further work on this topic included "Friendship and Natural Selection" in PNAS in 2014, showing that people have a small but discernible preference for choosing as their friends other people who resemble them roughly as much as third or fourth cousins.[47] In 2012, in a paper in Nature, Christakis' group analyzed the social networks of the Hadza hunter-gatherers, showing that human social network structure appears to have ancient origins.[48] Anthropologist Joseph Henrich noted that "the crucial insight from this work is that understanding distinct aspects of cooperation among these hunter-gatherers must incorporate an analysis of the dynamic processes at the population level."[49] Christakis and his colleagues did similar work mapping the networks of the Nyangatom people of Sudan in 2016.[50] His group has also demonstrated that social networks are deeply related to human cooperation.[31][32] These ideas are explored in Christakis' 2019 book, Blueprint: The Evolutionary Origins of a Good Society.

Beginning in 2010, Christakis' lab initiated a program of research to deploy social networks to improve welfare, health, and diverse other social phenomena—for example, facilitating the adoption of public health innovations in the developing world (e.g., India, Honduras),[51][52][37] understanding the origins of economic inequality (published in Nature in 2015),[34] or demonstrating the utility of autonomous agents (AI "bots") in optimizing coordination in groups online (published in Nature in 2017).[35] Economist Simon Gächter noted that "the most striking insight from these findings [in 2015] is the effect of wealth visibility on the dynamics of inequality: conspicuous inequality breeds more inequality. Although visibility of wealth does not change economic incentives in this experimental scenario, it invites social comparisons that... undermine cooperation and diminish social ties."[53] Gachter also commented on the 2017 paper and its contributions to evolutionary game theory.[54]

The 2017 paper on bots[35] initiated a program of work on "hybrid systems" composed of humans and machines (endowed with AI) that reshape how humans interact not with the machines, but with each other. A 2020 paper in PNAS extended this idea by showing that physical robots could modify conversations among people interacting in groups.[55] Another paper that year showed that simply programmed bots could re-engineer social connections among humans in networked groups in order to make them become more cooperative.[56] A 2023 paper in PNAS showed that simple forms of AI could change humans' ethical behavior towards others (using a cyber-physical lab experiment involving remote-control robotic cars playing the game of chicken).[57] Christakis argued in 2019 that "the effects of AI on human-to-human interaction stand to be intense and far-reaching, and the advances rapid and broad. We must investigate systematically what second-order effects might emerge and discuss how to regulate them on behalf of the common good".[58]

Finally, in 2010, a paper analyzed the spread of H1N1 influenza at Harvard University (as part of the 2009 swine flu pandemic) and showed that an understanding of social networks could be used to develop 'sensors' for forecasting epidemics (of germs and other phenomena).[59] In another 2010 TED talk, Christakis describes this effort (and computational social science more generally).[60] A follow-up paper in 2014 documented the utility of this approach to forecast online trends, again based on the "friendship paradox", using Twitter data.[61]

Christakis' lab has been supported by grants from the National Institutes of Health, by the Pioneer Program of the Robert Wood Johnson Foundation, by the Bill & Melinda Gates Foundation, and by other funders. In 2019, his lab received support to extend their work to studies of the human microbiota from the Nomis Foundation.[62]

Medicine

Christakis has practiced as a home hospice physician and in consultative palliative medicine. He took care of indigent, home-bound, dying patients in the South Side of Chicago while at the University of Chicago, from 1995 to 2001.[63] During this time, he was also active in translating research results into national policy changes with respect to end-of-life care in the USA; for instance, he testified before the US Senate Special Committee on Aging in 2000 (regarding barriers to hospice use, prognostication, and the cost-effectiveness of hospice).[64]

In Boston, from 2002 to 2006, Christakis worked as an attending physician on the Palliative Medicine Consult Service at Massachusetts General Hospital. In 2006, he moved to Mount Auburn Hospital. In 2013, he moved to the Department of Medicine at Yale University.

Books

Christakis' first book, Death Foretold: Prophecy and Prognosis in Medical Care, was published by the University of Chicago Press in 1999 (ISBN 978-0226104706), and has been translated into Japanese.[12] The book, based on his dissertation, explored the role of prognosis in medical thought and practice, documenting and explaining how physicians are socialized to avoid making prognoses. It argues that the prognoses patients receive, even from the best-trained American doctors, are driven not only by professional norms but also by religious, moral, and even quasi-magical beliefs (such as the "self-fulfilling prophecy").

His second book, Connected: The Surprising Power of Our Social Networks and How They Shape Our Lives, was co-authored with James Fowler and was published by Little, Brown Spark in 2009 (ISBN 978-0316036146).[65][66] It was awarded the "Books for a Better Life" Award in 2009 and has been translated into 20 languages.[67] Connected draws on previously published and unpublished studies and makes several new conclusions about the influence of social networks on human health and behavior. In Connected, Christakis and Fowler put forward their "three degrees of influence" rule, which theorizes that each person's social influence can stretch to roughly three degrees of separation (to the friend of a friend of a friend) before it fades out.[68][69]

Christakis' third book, Blueprint: The Evolutionary Origins of a Good Society, was published by Little, Brown Spark in 2019 (ISBN 978-0316230032).[70] It made The New York Times Best Seller list in its debut week.[71] It was widely and favorably reviewed.[72][73][74][75][76][77] For instance, Bill Gates described the book as "optimistic and terrific."[77] Blueprint explores the idea that evolution has given humans a suite of beneficial capacities, including love, friendship, social networks, cooperation, and learning; humans have innate proclivities to make a good society, one that is similar worldwide. "For too long," Christakis writes, "the scientific community has been overly focused on the dark side of our biological heritage: our capacity for tribalism, violence, selfishness, and cruelty. The bright side has been denied the attention it deserves."[78] Overall, Blueprint advances an argument about sociodicy, that is, the "vindication of society despite its failures". It proposes a list of eight attributes of societies that are innately favored due to human evolutionary history.

Christakis' fourth book, Apollo's Arrow: The Profound and Enduring Impact of Coronavirus on the Way We Live, was published by Little, Brown Spark in October 2020 (ISBN 978-0316628228).[79] It was widely and favorably reviewed[80][81][82][83][84] and was called "magisterial",[85] "gripping",[86] and "provocative".[87] It was long-listed for the PEN America EO Wilson Literary Science Writing Award.[88] Apollo's Arrow provides an account of the origins and course of the COVID-19 pandemic and its end, biologically and socially (in what Christakis has compared to the Roaring Twenties of the 20th century). In essence, the book argues that "plagues are not new to our species — they are just new to us".[89]

Christakis also co-edited two clinical textbooks on end-of-life care, published by Oxford University Press.[90][91]

Public intellectual

In addition to his scientific research and books, Christakis has contributed to popular media as a public intellectual, in a range of publications and on a range of topics. He has said he is invested in "advancing the public understanding of science",[92] and he typically writes about matters at the intersection of the social, biological, and/or computational sciences.

For instance, in addition to his book about the COVID-19 pandemic, Apollo's Arrow, released in 2020, Christakis published numerous essays helping to advance understanding of the social, economic, psychological, and epidemiological aspects of the pandemic. In The Wall Street Journal, he forecast the long course of the pandemic in 2020,[93] outlined optimal responses,[94] and provided a kind of post-mortem in 2024 (outlining how the pandemic would leave us with "public forgetting and private remembrance").[95] In The Washington Post, he wrote about the role of compassion during epidemics.[96] In The Atlantic, he wrote about school closures,[97] risk perception,[98] and public health responses.[99] In FiveThirtyEight, he showed how voting in the primary elections did not worsen the course of the pandemic.[100] Early in the pandemic (in August 2020), he wrote an invited essay for The Economist about how intrinsic properties of SARS-CoV-2 would make the COVID-19 pandemic more challenging to fight.[101] The magazine relied on him for subsequent assessments of the long-term impact of the pandemic.[102] In an interview for The Atlantic, Christakis also discussed the importance of free expression in combating the COVID-19 pandemic.[103]

For The New York Times, Christakis has written on prognostication,[104] university education,[105] free expression,[106] and the evolution of social sciences.[107] His essay on social science was said to have "created quite a stir", and it prompted debate and commentary.[108][109] For The Washington Post, he has written not only about COVID[96] but also on mass shootings[110] and fatherhood.[111] He has also written about how to "construct novel, unnatural social systems based on the predictable ways that humans act" for The Boston Globe;[112] the role of social artificial intelligence for The Atlantic;[113] and about social network dynamics for the Financial Times.[114] He published an article in The Economist in 2023 on the social and economic spillover effects of AI, arguing that AI systems will change how humans treat each other.[115]

In 2012, he wrote a series of online columns for Time with his wife, Erika Christakis, on a range of topics from academic dishonesty to women in the armed services.[116] For the same publication, in 2011, he wrote about biosocial science,[117] and, in 2019, about the link between cooperation and individuality, arguing that such a perspective was useful "in a moment when too much tribalism is causing devastating problems".[118] In 2024, he argued that poor decision-making by corporate and nonprofit boards could partly be understood based on their internal network structure.[119]

Christakis has also appeared periodically on TV and radio, commenting on social networks and social interactions, the COVID-19 pandemic, and other matters, including on NPR,[120][121] Amanpour & Company,[122] and other venues. Krista Tippett of NPR has said his perspective on human goodness "deepens and refreshes".[123] He has been featured in a number of documentaries about science, including Through the Wormhole,[124] Unnatural Causes: Is Inequality Making Us Sick?,[125] and This Emotional Life (on PBS).[126][127] Interviews with Christakis have appeared in The New York Times,[128][129] The Atlantic,[103] and elsewhere.[130] He has been a repeat guest on many leading podcasts, including Joe Rogan,[131][132] Sam Harris,[133][134][135] Michael Shermer,[136][137] and Reason.[138]

Christakis has given two mainstage TED talks,[139][140] appeared at the Aspen Ideas Festival,[141] and been a frequent contributor to the online salon of leading scientists and intellectuals Edge, including answering ten of its annual questions, from 2009 to 2019[142] and giving talks on how "social networks are like the eye" in 2008,[143] on "a new kind of social science for the 21st century" in 2012,[144] and on the science of social connections in 2013.[145]

Advocacy for free expression

Christakis has been involved in the defense of free expression for some time. At Harvard in 2012, he and his wife came to the defense of minority students who were using satire to criticize the elite final clubs at that institution. They suggested that the critics might be "more concerned with ugly words than the underlying problems" and that policing free expression on campus "denies students the opportunity to learn to think for themselves."[146] Their argument expressed confidence in the capacity and maturity of Harvard students to discuss contentious issues.

In April 2020, Christakis expressed concern that, in the setting of the COVID-19 pandemic, hospitals and medical schools were seeking to silence faculty and staff who were highlighting problems with the response; he stated that "clamping down on people who are speaking is a kind of idiocy of the highest order."[147]

In July 2020, Christakis was one of the 153 signers of "A Letter on Justice and Open Debate" (also known as the "Harper's Letter") that expressed concern that "the free exchange of information and ideas, the lifeblood of a liberal society, is daily becoming more constricted".[148]

In 2021, Christakis was asked to join the advisory council of the Foundation for Individual Rights and Expression (FIRE).[149] In 2022, he joined the advisory council of Heterodox Academy.[150]

In 2023, Christakis was the recipient of the Silverglate Award for Championing Free Expression at the inaugural gala held by the Foundation for Individual Rights and Expression in New York City.[151]

Yale Halloween case

In 2015, Christakis and his wife, Erika, were involved in a case arising from advice about Halloween costumes at Yale University. In October of that year, the Intercultural Affairs Council at Yale (a group of fourteen administrators) sent an email to undergraduates that recommended students be careful when choosing Halloween outfits, suggesting they avoid various sorts of costumes incorporating potentially offensive elements and including a link to a Pinterest page with recommended and non-recommended costumes.[152][153][154] In response, Erika (a lecturer on early childhood education at the Yale Child Study Center) wrote an email on October 29 on the role of free expression in universities. She argued, from a developmental perspective, that students might wish to consider whether administrators should provide guidance on Halloween attire or whether students would prefer to "dress themselves". She noted that her husband's advice was that "if you don't like a costume someone is wearing, look away, or tell them you are offended. Talk to each other. Free speech and the ability to tolerate offense are the hallmarks of a free and open society".[155]

This e-mail played a role in protests on campus that received national attention in the United States.[156] Christakis and his wife were criticized by some students for placing "the burden of confrontation, education, and maturity on the offended".[157] Other students, however, pointed out that Erika Christakis was defending the rights to free expression of all Yale students and expressing confidence in them and in their capacity to discuss and confront such issues among themselves.[158][159]

During the episode, some students "[asked President] Salovey to remove Nicholas and Erika Christakis from their positions at the helm of Silliman College", and, in a separate development, over 400 faculty members signed a letter on the broader issue of supporting "greater diversity".[160] Ninety-one Yale faculty members signed a different letter supporting the Christakises, and this letter noted that the couple themselves distinguished support for freedom of expression from supporting the content of such expression (the Christakises had noted that they would find many of the same costumes offensive as some students would).[161] Christakis stepped down from his role at Silliman College eight months later, at the end of the academic year, a step The Atlantic later decried (noting "when Yale's history is written, they should be regarded as collateral damage harmed by people who abstracted away their humanity").[162]

In a subsequent op-ed in The New York Times (his only published comment on the events), Christakis argued: "Open, extended conversations among students themselves are essential not only to the pursuit of truth but also to deep moral learning and to righteous social progress."[163] A year later, commentators condemned how students, administrators, and faculty had behaved at Yale (and linked to substantial video footage of the events).[164] In her only published remarks regarding what happened, published a year later, in October 2016, Erika Christakis described the circumstances (including threats) that she had faced in an Op-Ed published in The Washington Post.[165] Alum James Kirchick and former dean of the Yale Law School Anthony T. Kronman have since criticized the university administration for abandoning or not supporting Christakis and his wife.[166][167]

The incident led to some students being called members of "Generation Snowflake".[168] In January 2016, Bill Maher expressed consternation at how the Yale students had behaved.[169] In April 2017, an episode of The Simpsons titled "Caper Chase" satirized the events. Also in 2017, a short documentary was released about the episode, arguing that they reflected a collision between "old values" centered on reason and debate, on the one hand, and "administrative bloat" and a shift to a "consumer mentality" on the other (this documentary also noted that Christakis comes from a multi-racial family and has African-American and Chinese siblings).[154] The New York Times published a coda regarding the episode in August 2018, upon Christakis' appointment as a Sterling Professor, Yale's highest faculty rank.[166]

The case has been discussed in at least twenty nonfiction books.[170][171][172] Philosopher Russell Blackford provides a very precise and comprehensive timeline.[173] Some of these books noted the "sexism" and "irony" that, in a key episode that was part of the events (when Christakis was surrounded by 150 students in a quad for two hours), the students wished to hold Christakis responsible for his wife's email.[174][175] Commentator Douglas Murray summarizes statements by students based on his review of extensive video footage released by the students themselves of the events in the quad, and he notes Christakis' emphasis on "our common humanity".[171] Many of these books have expressed concern at the "illiberal" actions of the students (and of many administrators and faculty) at Yale. The behavior of the students also sparked a minor controversy at Harvard Law School when a student there wrote a piece decrying the Christakis' treatment as "fascism" in the Harvard Law Record; criticized for publishing the piece, the Record's liberal editor-in-chief wrote that his role was "editor-in-chief, not thought-policeman-in-chief."[176][177] The case has also influenced fictional portrayals of such events.[178]

A 2023 article in The Chronicle of Higher Education argued that the event signaled a worrisome sea change in attitudes on American university campuses, one "which in retrospect appears a compact fable containing all or almost all of the elements of our disorienting campus present".[179] A "free speech summit" organized by PEN America at Harvard University in 2024 also treated the event as a pivotal one, reflecting a "fundamental shift in campus climate".[180]

Christakis has spoken publicly about the events only rarely. In an October 2017 interview with Sam Harris, he discussed parts of the situation he faced, framing the events at Yale in the broader context of what was happening on many campuses during that time period; Harris noted that Christakis had "the imperturbability of a saint."[181] In March 2019, Christakis told Frank Bruni that, partly in response to the events, he worked to complete a long-standing book project on the origins of goodness in society (Blueprint).[182]

Personal life

Christakis resides in Norwich, Vermont.[183] He is married to early childhood educator and author Erika Christakis and they have four children, one of whom they adopted later in life, while serving as foster parents.[184][185][186] His hobbies have included Shotokan karate (as noted by his instructor, Kazumi Tabata)[187] and making maple syrup.[188]

Published works

Books

  • Death Foretold: Prophecy and Prognosis in Medical Care (1999) ISBN 978-0226104706
  • Connected: The Surprising Power of Our Social Networks and How They Shape Our Lives (2009) - with James Fowler ISBN 978-0316036146
  • Blueprint: The Evolutionary Origins of a Good Society (2019) ISBN 978-0316230032
  • Apollo's Arrow: The Profound and Enduring Impact of Coronavirus on the Way We Live (2020) ISBN 978-0316628228

Selected scientific papers

References

  1. ^ "Preface", in Nicholas A. Christakis, Blueprint: The Evolutionary Origins of a Good Society, Little, Brown Spark, 2019
  2. ^ Tom Conroy, "New Institute Will Advance the Interdisciplinary Study of Networks", Yale News, April 11, 2013.
  3. ^ "Dr. Nicholas A. Christakis named Sterling Professor". YaleNews. July 23, 2018. Retrieved July 25, 2018.
  4. ^ "2024 NAS Election". www.nasonline.org. Retrieved May 2, 2024.
  5. ^ "Five professors elected to American Academy of Arts and Sciences". Yale News. April 11, 2017. Retrieved April 18, 2017.
  6. ^ "Αναγόρευση του Καθηγητή του Yale Nicholas Christakis σε επίτιμο διδάκτορα του Τμήματος Οικονομικών Επιστημών του ΕΚΠΑ". iatronet.gr (in Greek). October 6, 2021. Retrieved October 9, 2021.
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  90. ^ P. Glare and N.A. Christakis, eds., Prognosis in Advanced Cancer, Oxford University Press, 2008 ISBN 978-0-19-853022-0
  91. ^ G. Hanks, N. Cherny, S. Kassa, R. Portenoy, N.A. Christakis, and M. Fallon, eds., Oxford Textbook of Palliative Medicine, 4th ed., Oxford University Press, 2009 ISBN 978-0-19-969314-6
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