It's a privilege to be here and to be among all of you. Thank you for allowing me some time to share with you some information about social networks and some of the work that I've done over the years. Let me start the slide. Here we go. I love this image. This image is about the chemical transference between two neurons, something that fails to happen in my brain far too often. But there's a lovely little book written by our friend, Sigmund, called Civilization and Its Discontents. And I would press forward and say that maybe we need to write a book, another version of that called Civilization and Its Disconnects, but more importantly, not the negative, but rather the positive to think about civilization and connection. And I think that is what the challenge that we face in the 21st Century. I think it's the biggest challenge that we face is, how do we bring together people which have diverse interests? So I'm going to talk a little bit about civilization and connection. And this early Indian Jones photograph is in a galaxy far, far away, a long, long time ago when I was mere child, looking at the ancient trade networks. So I, unfortunately, cannot talk about the large database over the years that I've collected. I'm only going to be drawing from that database to share with you a couple of community and complex partnership examples.
The first thing that I'm going to start off with though it this little triangle. Instead of a pyramid, I'm going to go right to a little triangle. And our colleagues, Oliver Williamson in 2009 just won a Nobel Prize for talking about the two bottom types of relationships. When we transact with one another, which we can also do with technology, I can put my ATM into the ATM machine, I mean, my card into the ATM machine, I get cash for the weekend. I could put my credit card onto the Internet and buy tickets for my next vacation. Those are transactions. So I can work with any one of you, ask for your signature or give me a piece of paper or what's the agenda today? That would be a transaction. But when there's a little bit of uncertainty, or as Oliver Williamson called it, Asset Specificity, people do congeal or come around to try to resolve that uncertainty either in the partners that come together or in the nature of the problem that they're trying to solve. And when people do come together, they sometimes use authority. Somebody's got to be in charge, somebody's got to take orders, somebody's got to give orders. And those bottom two ties larger dictate the way we operate in communities and in businesses, in government, and in schools. But probably the most powerful human connection people can have is one of trust. And there have been lots of books and articles written about trust, but more from the soft, social capital side, the soft, warm-and-fuzzy side. And I'm not going to go into a lot of detail here, but I truly believe that trust can be looked at in a disinterested fashion. Much like Machiavelli talked about it in The Prince and people are still arguing about that book 500 years later. But trust is a force-field equivalent to nuclear force, I believe, that binds people together is probably the major contributor to why cultures don't change.
So when you're trying to move forward in the school district or when you're trying to move forward in a complex partnership, the way people trust one another before the change was announced is often the very thing that is a major resistor to any of your initiatives. Now if you can find the key connectors inside trust-based relationships, then that's a marvelous find, because what they'll do is they'll help move forward any change. Just like a school of fish can instantaneously turn in the ocean because of the chemical reactions that are spread all through the school of fish along the sides, it's the same thing in human, with human beings. If they trust one another, it's a very powerful force for change. But likewise it's a powerful resistor. Now if we continue on to look at organizational outcomes, this is again, where Oliver Williamson won the Nobel Prize. Because the whole idea of authoritative relationships trying to resolve a little bit of uncertainty or ambiguity between people gives rise to the firm. And if you solve for that uncertainty using authoritative relationships, you can solve a riddle, create a service, or perhaps produce a new product, which you then sell into a marketplace of transactions. And so a lot of the last 150 years has been developing the research and the theory behind the bottom half of this triangle. But if we look at the top half, we see that trust, ironically, again, the most powerful relationship. And yet the one thing we don't measure, gives rise to another organizational structure called Networks. Now it took Oliver Williamson about 80-some odd years to get a Nobel Prize for the bottom half of this triangle.
I suspect it will be another 80 before a trust and networks are finally recognized, but they are a force for change. And what I'm going to do today is talk a little bit about the outcome of trust, which is a human network. The model of it is what you see here. On the left-hand side for you that's the beautiful, hierarchical structure of authority. I personally find it elegant and simple. And unfortunately, life does not go this way in most organizations. But we can't live without a hierarchical structure, because, after all, hierarchical structures do last hundreds of years. They manage to-- They have a perpetuity all to their own. But they only have two degrees of freedom. And as such, they change little and infrequently. But they are elegant structures. And to the right is a network. And actually this comes from the database. This is real data. So to the right of the hierarchy is a human network of work, not just how they socialize, but really about how they get their work done. And the lines connecting these simple little black nodes, I mean, there's, there's much more compelling visuals. But I like keeping it in this very simple form, because it respects the theory. The lines that are connecting are two-way ties connecting people together. And you'll notice that there are some colored nodes there, a yellow, a green, and two reds.
Those actually are the mathematical cut points in graph theory, such that if you were to remove those nodes, the entire network would disaggregate. It couldn't hold together. Now sometimes you find this in organizations. And I can tell you right now, having worked with the United States Government, the British Government and the Dutch Government, they're trying to find who these connectors are
in fraud network, financial networks and terrorist networks. But what we want to do is find these nodes not because we're trying to disaggregate something, but because we're trying to build something.
We're trying to build a community, a learning community. We want to know how we can effectively collaborate? How can we effectively connect? Because connection is not a random event. It's non-random. So there are efficient, efficiency models for how one can connect. But as with anything in science, the model is beautiful, but the reality looks something like this. They merge together, they come inside the organization. And there's our little guy with the American flag, saying, "Okay, here's how we, here's how we run the organization."
But often what happens is that networks, because we don't have the tools to actually see them or measure them, can undermine peoples' authority or well-meaning networks can stumble and get in the way.
Just look at the recent attempts at many of the wonderful citizens, global citizens of the world. running to the help Haiti and of the Haitians. And look at many of the, unfortunately the perverse outcomes of that where well-meaning, lovely people are bumping into one another because of an inability really to connect effectively. But if I could just-- If I were just to talk about those three types of relationships, transactions, authority and trust I wouldn't be really addressing what I truly believe is the challenge for the 21st Century and something that Jim has mentioned that he's been working on for a long time as have I. And that is the way people come, come together and connect in these complex partnerships. And there is a word for that. It's heterarchy. It's a lovely word and rare to find in the archeological record.
I've got a call out to all my archaeologist friends, to say, "Where are these heterarchies in the archeological record?" We certainly face them now. And I'll talk a little bit about it now. If we look at how a heterarchy first forms, I'm going to first start with looking at partnership. There are some flawed assumptions about it, and let me just briefly go here. In, in simple partnerships, which we do understand, they are dyadic. Two people connect for a variety of reasons. They trust one another. Maybe they don't trust-- Maybe they have a transaction. Maybe one has an authority position over the other. But the simple two-person partnerships is something that we understand and is governed or mediated by trust-based relationship or, in the case of organizations, or sometimes in the case of human beings, by contracts. Marriage contracts, prenups, joint ventures, all of these different types of paper products dictate some of the constraints around simple partnership. And this two-way tie is, permeates a lot of the thinking and a lot of scholarly work. And it's near and dear to any anthropologist's heart, because it's the underlying story behind reciprocity. But if we got further, I want to talk about adding one more node to a partnership.
Now this is a funny little diagram, but bear with me. Imagine that you are at the top of that triangle. That's you, the happy face. Okay. And you're feeling mighty fine because you're surrounded by all these positive relationships, which are singed with a positive green plus sign. But let me just explain what this relationship is all about, this type of partnership. If you go down to the left-hand side, you'll see that you're connected to a node. And let's imagine that that node, that image there, is your spouse or significant other whom you love dearly and who loves you back. So that's a positive relationship. And your spouse or significant other also happens to love, to the right, his or her mother, very powerful relationship. And your mother, of the mother of your spouse, a significant other, loves you because you take care of her child. But let's just imagine that you have an argument, a dispute, a conflict with your spouse. Suddenly things change. The relationship becomes somewhat negative. You've got to try to mediate it. You've got to try to figure out how did you get off track. Because there's a lot of trust holding that relationship together. But faster than the speed of trust or the speed of light, your spouse or significant other is also going to tell his or her mother, whom takes absolutely, has zero tolerance for this thing happening to his or her child, and immediately comes at you. So now you've got two negative-signed relationships. This is a very simple diagram of a three-person network. Every day you and I wander through hundreds and hundreds of networks with hundreds of connections, and look at where you could get off track with a simple three-person network. Now I am not Doctor Phil, but I can tell you inside relation, I mean, inside organizations, there are a lot of these little tri-partite relationships. And this, my friends, is where politics begins. Right there.
Because you have no direct control over one of their relationships. Levy Strauss, who recently left us, nearly, almost-- Last year. he was almost 100-years-old, said in his, on of his articles in The Mathematics of Man, he said that, "I'm less interested in a country with a population of 300 million and what happens to it when there's a ten percent increase in population than I am when a two-person household becomes a three-person household." And it's precisely because of this diagram. So it's a tiny little network, and it's the beginning of politics. Because we don't have direct control over one of those relationships. There's a lot of uncertainty and ambiguity in an indirect relationship. So that's how you feel after the entire thing, not a happy camper. So now let's expand it out a little bit more. So let's look at a tax, you know, a taxonomy or a classification scheme.
If I start with a simple person, there I am. I'm a single node, and I form a simple partnership, which you can see, and I expand out to a three-person network, that's the basis of a human network. And many of us, we pass through these relationships all the time. But when you take a look at how institutions come together, institutions-- It's kind of hard to talk about the intentionality of institutions. They're comprised of people who have intentionality. But the-- If we look at it at the macro-level, the institutions also come together in partnership. Now we understand when two institutions partner, because that is governed by a simple contract. But when you have three institutions partnering, it gets complicated. So the definition for heterarchy really begins with three or more, not two. Two is the simple dyadic partnership. But three institutions, three or more, locked in an interdependent collaboration where each institution is not priviledged over the other and a shared governance presides. That's a heterarchy. And in those relationships, no one has--All those institutions that it might be in direct partnership, there's always an indirect relationship that's going on. It's the same thing that happens on the bottom half of the diagram when we're looking at a human network. Three or more individuals blocked in mutual reciprocal exchange, exchange that is both interested and repetitive to use the words of Oliver Williamson, or to use the words of the French sociologist Mauss, he called it, In looking at the Melanesian exchange, he called it the how or the spirit of the gift. Because when you exchange with people, there's a spirit of governance over that. So now let's test this idea.
I'm going to show you a university structure. It's the Department of Education at UCLA. And the three big squares that you see highlighted are assistant, associate, and full professors. And I've made the image over the boxes a little bit bigger so that those of you in the back of the room could perhaps see it. What you can-- And you may not be able to see the detail of the network, but let me just explain. There's also adjunct to the upper right and emeritus onto the--Excuse me, the upper left, and emeritus on the right-hand side. But the important things is what you're seeing in each one of those three boxes, there are subsets of circles showing male and female professors, male and female assistant professors, male and female associate professors, and male and female full professors.
What you're only looking at in this diagram is the image of the connection of the men and who they're connected to. So we're only looking at male assistant professors who they're connected to, male associate professors, and male full professors. Now as you can see, they're connected all over the place and across multiple circles.
But now what I'm going to do is show you the slide of just the females and who they're connected to. A dramatic difference. And the reason for that is because there was an intervention that was done in this university department. And let me just accentuate it. It's a very tight network of women connected to women. Yes, they do talk to our male colleagues, but they're much more tightly connected to each other. And the reason for this is, is that in many universities, there is an abysmally low percentage of tenured women in these, in these various departments. And that had been the case in the Department of Education. Anywhere from three to ten percent were tenured. And ten years ago, there was a professor, a university professor, who wanted to change that. And so started an active mentorship program where the women worked with other women. And if you can see the size of the circles in the assistant box and in the associate box and in the full box, it's almost up to 50 percent.
It took years to change that demographic, that statistic, but never underestimate the power of mentorship. Because it can change the face of an institution. This was an NSF-funded study in the '90s.
This is the comparison side by side. So you can see it. On the left, is the female network; and on the right, is the male network. I'm not arguing for only speaking to men and/or women. What I'm suggesting is that because of the intervention of this leader and the way that she worked with the mentorship to change the dropout rate of tenure amongst female professors, she directly led to this changed percentage. And she was very grateful for this study. So now that little three-way network that you saw is a little tiny heterarchy of different types of professors.
But now let's come here to another image of heterarchy which is used by the United States Government and by the British Government. The yellow cylinders that you see around -- there's five -- represent institutional hierarchies. So that could be a universe-- It could be maybe a high school, a junior high school, maybe a community that's, a community organization, a volunteer organization.
Maybe a business. And also maybe an IHE that could be working together. So you have five different institutions that are arrayed around a well-designed, measured network that coordinates the efforts of this collaborating group. And the reason why you have that blue-designed network there is because none of these institutions could achieve their collective goal on their own. That's why it's a heterarchy. They have to-- They each have their own raison d'être for why they're there. But they have a larger goal that they have to collaborate on where they really must work with everybody else.
So this heterarchy of five or more institutions is a pretty-- the image that we created fort the UK Government was such that they felt that they could communicate this across the world to public/private partnerships. And the US Government also uses this in changing the supply chain of the United States Army and other aspects of the government. We're still working on the Department of Homeland Security. Check with me next year.
So if I look at this heterarchy and blow it up a little bit, I can see that there are some complexities associated with it. And maybe what I'll do is I'll just change the image up top. Instead of heterarchy, I'm just going to call it healthcare. And the reason why I'm going to go there is because we could talk about education, but I think you all know the challenges that you'd face. So let me just tell you a story about the healthcare one. Let's imagine that you've got an aging parent. And I could give a personal story of this. And you've got a father, 74-years-old. He's got Alzheimer's and type-two diabetes. He goes into an assisted living institution, which is the first yellow cylinder. And while there, when they take off his sock, they discover that he has an open sore, a broken blister wound on the heel of his foot. And for those of you who know about type-two diabetes and aged folks, none of us would qualify for that here. But you know that it's very serious. And so what happens is they immediately transfer him, and they take him to the second gold cylinder, which is a hospital where they pump his body full of antibiotics to try and cure the disease, the infection. He's three months on his back. He forgets how to walk. So after three months, the infection is cured. They move him to the third gold cylinder. That's a physical therapy institution where he can relearn how to walk. Because he's forgotten. He's aged. He's got Alzheimer's. And then while they exercise him, what happens is that they're moving him around, his Alzheimer's gets activated. And they discover him at two or three in the morning out wandering the streets. So they transfer him yet again to now a lockdown facility. That would be the fourth gold cylinder. And the lockdown facility can teach him how to walk again. And they have the doors locked down so that the Alzheimer's patients or those patients with dementia won't wander. But by this time, because there is no blue diagram telling people how to transfer a patients. Because every single one of these healthcare people are measured internally by their own institution. So he could be left out in the hall for 12 hours, out in the rain. There's trauma that's associated with the transfers, the ability of these different institutions to collaborate with each other. So by the time he gets to the fourth institution, he's become so demoralized. He's in a wheelchair. And then he goes into a full Alzheimer's unit, which is the fifth golden cylinder where he dies shortly thereafter.
Now when you talk to people in these healthcare institutions, they do not come to work everyday to try to make somebody's' life miserable. They care about people. They care about healthcare. They care about finding cures. They care about palliative care for people if there is no cure. But every single one of them is measured by the, by the protocols and that they have to check off inside their own institution. Nowhere is there a broad-based measure for how these institutions collaborate. Now does this sound familiar to many of you in your communities? I know it does. And that's what we're looking at here. That's why heterarchies, it's a concept, but it's very difficult to understand and to manage. And we really do need new tools in order to be able to look at this. So the transformational challenge I think for all of us in the 21st Century, is to take, to move away-- Well, not to-- Yes, in a way, to move from a total dependence on a hierarchical structure, which personally, as I told you, I think is so elegant.
To understand that networks exist, which now with social media and new tools for measuring networks, we have a better understanding of. But we still have a long way to go to take a look at networks from an evaluation standpoint. But it's really not just about the network. IT's about the intelligent integration of these two structures in complex partnerships which are called heterarchy. And I think that is the next big challenge. And we certainly see it-- Not everything is a heterarchy. Healthcare is a heterarchy. We just experienced a financial meltdown and saw the European leaders standing on the steps. They each run their different nations with different policies. That's an example of a heterarchy that was forced together. We have-- In education that's a heterarchy. Not everything is a heterarchical structure. But what-- The challenges that we face in this room, I do believe we are looking at heterarchy. And the interesting thing is, we cannot look to the past because we don't find records of it in the archaeological trace. You know why, I think? Because never before in the course of human history have human beings been this interconnected.
We have technology to help us, we have trust-based relationships to help us. We have new kinds of organizations to help us. But the fact of the matter is, if you do look over at the great migrations and how civilizations worked with one another, we weren't this interconnected. so maybe we can look to the past, but I think, most of us, we need to look into the future and that the solution for heterarchical governance isn't going to be coming out of some research. It rests in every single one of us, because I think little tiny bits of the solution are in this room. We just have to bring it together.
So what I thought I would do is share with you about what some people are doing with heterarchy. In the UK Government, you have 13 of these heterarchy pilots-- Actually, there's about 25. This is an old slide. But I thought that you would interested in this. Because the UK Government is very interested in reducing burglary, domestic violence, lowering crime in these community, in the communities around. And the national government realizes that they can put out policies and initiatives all day long. But it won't make a difference in terms of lowering crime rate. Because it really requires the support and the coordinated efforts of volunteer organizations of local, elected councils in local communities. So it's at least a tri-partite network or a small heterarchy. And usually it consists of 30 or 40 different organizations. And can you imagine trying to run an organization like that? Nobody knew how. Nobody knew who even to talk to, except maybe at the heads of the organization. And that measure was failing. So what we did-- And this about the-- This is the work, the labor of over 10 years of research. We would go and scan a community.
This is data from the area in Mansfield. And what we could find-- We could identify some key connectors, which I'm just showing you in a simple slide here. And these key connectors were people that nobody knew had connections with other people, that were trusted by other people, that were considered to be knowledgeable in certain areas. And I don't know if you can see, but there's a little blue circle right there in the middle, a very tight blue circle with a lot of blue lines. That's the police department. And the police department is connected to the big circle over to the left. And those are the elected official. Typically in local communities like this, this is where the strong connections lie. But what we were able to look for and what we were able to find were key connectors throughout the other parts of the community, that ended up having the solution once you brought them together in the room and they had a discussion. But they never would have been identified and they never would have been brought into the room had this technique not been used. And many solutions have been provided in the area of the UK when it comes to PPPs or Public Private Partnerships. They're also called LSPs for Local Strategic Partnerships. The way we'd look at that is we take little parts of that network and we look for the key connectors.
Remember the yellow, the green and the red nodes, those key cut points? We tried to look for them. We look at them in different ways. We create charts around it. So here in this chart, what you can see is--There's three things on this cart. There's the big area of Mansfield. There's a close-up of it. And then because the police, they may or may not care about network structure. They really want to know, who's my next leader? Who-- Can you identify my current leader? And who are some potential leaders? Who can help others, mentor them onboard the new people into a community? Who can really solve a problem? These take different kinds of skills, different kind of competencies. And then who are the rising starts, which I personally call--That's my favorite. These are the wildcard people. I call them my STEM cells. Because you could take these people, and you can put them next to anybody. And they'll turn into them.
So they're kind of interesting. That's my bucket list right there. Now what ends up happening is that here we got three teams, team 1, 2, and 3. You can seen the blue lines connecting. This is little tiny heterarchy of teams. And you can see there's a connection here that's missing. The blues lines connecting team 1 and team 2, and team 2 and team 3 are there because these two teams were, in the past, collocated together. But when you're dealing in communities such as the complex communities that you're working with or global strategic partnerships, you can't collocate everybody. It's an expensive proposition. And if you can afford it, that's great. But you still will have areas that you can't collocate. So how do you bring these teams together? Well, I wouldn't know. But they know. What we did is we found the key connectors in each one of those teams. And when they finally got together and had a meeting, they could design the solution for closing the gap, which I'm just going to illustrate here with a dotted line. People have the solution in them, but it's only a part of the solution. We've got to bring them together. First, we have to identify them. And then we've got to bring them together. And, my friend, they are not the usual suspects as Humphrey Bogart said in Casablanca. They're not the usual suspects.
So let me share with you another connector story from Philadelphia. Two-hundred-- Approximately 250 years ago, let's go back to 1776 when we had Benjamin Franklin. And he was working, exhorting the 13 colonies to try to come together. One could take a look at Philadelphia back at the beginning stages of the, of the birth of this nation and to look to Philadelphia's contribution to this nation as being one of collaboration, of working together. Because it kind of all happened right there in Philadelphia. You had Ben Franklin, they were all arguing with each other. Let me tell you, they did not agree on many of these points. But if you flash forward now to the present day, look at Philadelphia. And I think those of you in the audience from Philadelphia will agree with me that you have a lot of issues around leadership with Philadelphia. In fact, I don't want to give any offense; I see some Philly's heads nodding here that, you know, you got a lot of indictments of these elected officials. A lot of them are behind bars. You're got soaring drop-out rates and crime rates. What happened? What happened? This beautiful city, it's the nation's first capital before New York, before Washington DC. It's the nation's first capital. What happened? So people like Chris Satullo in The Philadelphia Inquirer wrote articles saying,
"Where's the outrage? Why-- Where-- Where does this-- Where do people try to come together to do something about it and fix this problem?" So what ended up happening was that Liz Dow, whose President of Leadership Philadelphia -- every city has one of these leadership organizations --called upon Malcolm Gladwell to come and give a talk in Philadelphia. This was around 2004. She did not know that Malcolm Gladwell knew about my work and had written about my work in The New Yorker in 2000. So Malcolm Gladwell comes there, and he's talking about these connectors and these tipping points. She said, "These are the people I need to find, the unusual suspects in Philadelphia. Help me, Malcolm, find these people." He said, "I don't know how to find them. I'm a journalist and I can write stories. But I know somebody who can. We want you to call Karen Stephenson." So she calls me up. I get this phone call. And I'm thinking, "This is an unusual request. She has no money." And I said, "I don't need it. This is so powerful, this idea is so powerful. I'll do it. I'll just do it." And I can tell you now, it's led to some really interesting findings.
So we got a core group of people together from various different sectors, a little kind of team, a heterarchical team from all these different public/private sectors, futurists lawyers, marketing people. And we go the two newspapers who hated each other to collaborate on this great project. Because they thought it was a great idea too. And we put a call out for, where are these connectors?
So this is the approximate timeline, from Spring of 2005, where I said I had a close encounter. Because that's when I got my phone call. And then we devised a methodology, which is a two-part stage of social-network analysis. It's a modified snowball sample where you collect nominations. You call those nominations. You clean the data for gaming and things like that, which people can, you know, hit enter for instance on an online thing. And you can, you can guard against that. There's all kinds of techniques for eliminating stuffing the ballot boxes, if you will. And then what you do is you take a look at who might have received the highest nominations. And then you call that list. And then you ask them. Well, we saw statistical breaks at about 200. But we were only a team of ten people who were all donating our time. So we couldn't-- It was overwhelming to look at 200 people.
So we saw another break at 100. So we decided we would look at the top 100 people. And we said "101" because there was a tie for the last position. We weren't being cute; it really was 101 where the break was. We then asked them if they knew each other. Because imagine this story in you community, in your schools, in the, and in the public/private sectors, and amongst business and volunteers. There's lovely people out there working in the weeds, the unusual suspects that you may not be aware of. But what if you could identify them? And then what if you could bring them together? Because what these people do is they connect others. But a human being can only connect so many. They work in those smaller, what we call egocentric networks. So we convene the connectors, as you can see in December 5 of 2006. And then later on we did some additional studies. And there is a book coming out this year, which I'll get to here in a moment. But I have to tell you something very funny. When we convened these 101 connectors, there was no television, no press. We wanted to recognize them. And we made a little video for them. We had Benjamin Franklin as the actor. And we had a video that was divided into two parts. He was black and white and he talked about all the great works around 1776. And then a little bell rang like the angel gets its wings. And then it immediately went into color. Benjamin Franklin was in color. And then all of the projects that he was talking about were in color. And they were all the projects of the people in the room. It was a lovely event. They were recognized. We shone a light on them. And let me just tell you that the meeting was only scheduled for two hours. We were pushing them out the doors four hours later. Because what were they doing? Connecting. They can't help themselves. So the questions that we asked were about seven questions aimed at not looking at organizations in, with boundaries around them. But again, based off of the work that we'd done in the UK, we adapted these kind of local community questions to get at, who are these people that have got the guts to see it through to the end? Who's got the integrity? Who's got the fortitude to work with you? Who's got the resources?
Who can-- And I like the last question: Who reaches across outside your own race, class, social circle, gender, religion, age group? Who do you consult? And the proposition, the reason why people were even answering these questions is because since Philadelphia --it was the nation's first capital -- we said, "Look, imagine that Philadelphia is on a short list for 2012 and it's going to be recognized as one-- It has the opportunity to be recognized as one of the best cities to live in." So if you were going to believe in that proposition, who would you call? It's like the Ghostbusters thing. Who are you going to call? And so those are the kinds of questions that we asked them. Then what we did is, once we called the list down to 101, then we asked them a shortened version. And this is the more network-analysis side of it. We asked, do you connect ors know each other? We didn't know if they knew each other. So this is what the diagram looks like. The not-for-profit sector, the private sector. And you'll see there's two boxes within each sector, and one with an M in it and one with an F for male and female.
Sometimes I think it's kind of interesting to look at balance. And then we have government and academic. So you can see that there's relative different sizes. And, you know, my colleague here who are statisticians--I fully recognize this is not, you know, this is not-- We don't have the resource to do a census bureau. But we did the best we could with the limited funds we had to try to reach out and find who these people were. Here's how they got-- Here's how they're connected to each other, which is pretty good. But, you know, when you look at all these connections, there's some things that you can't see. So what we did is we combined all the questions, And we looked at how they were connected internally, which I think you might find interesting. You know, they responded the same way in Philadelphia. I showed the slide, I didn't say anything. And a colleague finally stood up from the government, says, "You're right. We don't trust one another or from one department to another." So-- But there's the interesting news about this. The not-for-profit--As you can see, the super-connectors and the not-for-profit in the private sector are in there. And let me just also mention that in every city, normally they, the, the PR firms of a city get together, and they will publish a short list of the 50 or the 100 most powerful. And the PR firm that did this in Philadelphia was very interested in our list, because they wanted to know if new resources were identified. And we certainly did identify new resources. But they were not the usual suspects. In fact, when we compared the list side by side, what we discovered is there was only one percent overlap between the two lists. So how we sort of think of powers is maybe inversely related to the good works of what these people are doing.
Now the one person where there was an overlap is now the mayor of Philadelphia. And guess who he's using to improve civic engagement? He's go the usual suspects and he's using the unusual suspects. So-- but what we did learn is that Philadelphia is a wonderful location with magnificent educational institutions. And something happens when people come there to get educated. It's the crucible of learning where they come together. And they have such powerful experiences in the process of education that they come back to Philadelphia. Or what happens is that they go away, and then they later return. So we don't know what's causal or if it's a correlation or a cause. Because we don't have enough data to really know. But we do know that education really matters. Also, we know that a non-native-- Because in some, in some cities, you can cut your wrist. And if you don't bleed the right shade of blue, you're not considered to be in the in crowd. But that was not going on in Philadelphia. The non-native was as powerful as the native. We do know that these connectors were so busy, these key people, that they didn't have any time to mentor. So we interviewed them and got them involved in a mentorship programs with high school. And then we've also developed a list of competencies, because what we found is in traditional leadership courses, the competencies that are identified are very different from their competencies. So we think maybe we could add a few more competencies, particularly since heterarchy and complex partnerships is a 21st Century problem. Connection is a part of that skill set. Now the interesting things about this it's an idea that caught hold.
So we're conducting another study in Louisville. We're just about to announce the connectors. Tuscan, Arizona is already begun. And Portland, Oregon will be starting. And for those of you who may be visitors to the United States, that may not be familiar with the shape of the country, this is where we're going. Now I just have to tell you, when Liz Dow called me up and asked me if I'd be interested, I didn't know that it would result in this. But what we're going to have is some very interesting-- We don't have an N of one, we're going to have four N's here, four events in different regional areas of this great nation. And we're going to look very hard at those competencies to see if they're consistent across. If they're consistent, that's interesting. If they vary because of local regional constraints, that too is interesting. We don't know. It's a living experiment. So this is the image that Benjamin Franklin created. We colored the P for Pennsylvania yellow. But what he did is he, he took the snake, he cut it into 13 pieces representing the 13 colonies, and said, "We must unite or die." And that brings me back to this concept of heterarchy and complex partnerships. Because going into the 21st Century, I think we need to connect. And that brings me back to Civilization and Its Discontents and civilization and its disconnects. If we can get on top of that and really understand effective connection and partnering, I think we'll have come a long way. So this is the book that will be coming out in February. I have an afterward in it. And as you can see, Malcolm Gladwell has lent his fine script to it as well.
So, in summary, I've gone through a couple of examples which have illustrated these ideas of complex partnership. The first one, collaboration and mentoring, is truly a game-changer for institutions. It is. It happened to the UCLA Department of Education in an NSF-funded study. Currently we're running studies for ELAM(?) and Famer(?) with Drexel University looking at alumni networks, and how if they support one another in the institutions where they are, we see statistical change in the demographic profile of that institution as to who is dean, who's tenured and things like that. So we're continuing on with that work. The second bullet point is that this measure has been used to measure nascent national networks among the Public-Private Collaboration for Women and Girls in Information Technology and Computing. I did not show you that network, but the people that are a part of widy(?) Some of those folks are here this room who knew I was speaking about this. Because we measured their networks a year ago when they were forming this multi-national collaboration. And we might be doing a second measures. And, again, they're very interested in women and girls in science and technology.
The third bullet point is out of 450 UK Government measures-- I didn't mention that, did I, when I was telling you about the pilots; 450 government measures, neither one of them really measure anything. And that's why they were having these perverse outcomes to policies. So what they did is they swept it clean. And they have five measures. And one of the five is this methodology. They go and they find who these key connectors are. Because they have found that over the ten years of research across 25 different pilots, it's a game-changer.
It makes a difference. The Philadelphia Study. Initially recommended by Gladwell, and then as a consequence of this, there was an award of the first Katharine Hepburn Fellowship, which I was happy to say thank you. And now we've got four city comparative studies targeting civic engagement. If we can do this in university departments, if we can do this local economic regions in the UK, if we can do this across national, inter-institutional collaboration, if we can do it in an area in these cities, we can do it here with the NSF and the MSP. So can SNA. We don't know. Let's look at it. Let's take a look. And that is why we asked you to fill out those forms yesterday. We thought we would take a look at it and see. This is a learning network. You all are collaborating. Let's do a baseline measure and see where we are. And we probably ought to do a measure later on in the future, maybe a year from now or something like that and see.
So in closing, this beautiful slide that Jim showed the other day in his talk about the Math and Science Partnership, he talked about these core participants of these benzene rings, of the IHE and the K-thru-12 school system. But I want you to look at the business and industry and the community organizations and state educat-- There's a larger community that's also important. So maybe it isn't just two benzene rings. Maybe it's more than two.
So I want to share with you, since I am the quantum chemist, that's my training, this lovely image that's a model of the pentacene. So if we go back, maybe it involves other aspects of the community. It's we've got two benzene rings there; let's look at pentacene. But, again, it's a model. But now let me show you something. I'm going to now take the model away and show you the first x-ray of the pentacene molecule. There it is. I just-- This is the chemist in me. Isn't that beautiful. And the little white around the edges is the electronic charge. Because you've got all those hydrogens, and they've got nothing to connect to. So they're creating a little extra energy there. But now if you go back and you look at the model, there's the model. This is the real picture. This picture was just released last year by IBM out of Zurich from the IBM laboratories. Because we didn't have the technology to see the real thing. But the real thing is very, very close to the model.
So, my friends, when we come up with these models, the models for collaboration, maybe they're not so far from reality. Maybe we can learn something about heterarchical models and try to implement them in our collaborative communities here. All right, thank you.