Darcia Narvaez is Professor of Psychology at the University of Notre Dame and writes a blog for Psychology Today called “Moral Landscapes.” This is a talk given at the conference, Sustainable Wisdom: Integrating Indigenous Knowhow for Global Flourishing, which took place at the University of Notre Dame in 2016. Narvaez is also a scholar with the project Virtue, Happiness, & the Meaning of Life.
An avalanche of newly accessible datasets – popularly called “Big Data” – is transforming research questions and processes across the social sciences. Dialogo, UChicago Social Sciences, spoke with Howard C. Nusbaum and James A. Evans to discuss the impact and opportunities surrounding these changes. Link to original article below.
Dialogo: What does big data mean in the realm of the social sciences?
James Evans: Big data can mean many different things. The classic triptych is high volume, high variety, and high velocity. In the social sciences especially, it’s increasingly high volume and high variety. Each does a different kind of thing. Large-scale data comes off of highly instrumented social processes. For example, our cell phones and all of the transactions that we engage in online and in many other contexts are instrumented by an ensemble of sensors. Those sensors create large streams of data that allow us to ask and answer questions about social process at high levels of resolution than we could have only conceived before, and with much larger scale data over many different kinds of interactions and time periods, et cetera.
The variety part means that we can also explore the relationship between different kinds of social action because they exist in this common format in a way that was previously only conceivable in contexts like ethnography, where people were looking at multiple modes but in very small scales.
Overall, it’s a game changer in social sciences.
Howard Nusbaum: For a long time, social scientists have used survey instruments like the General Social Survey, which is a very structured set of questions that people answer, and tracked that data over a long period of time. We used to consider that big data, but now there are projects like the Kavli HUMAN Project at New York University, where they intend to survey 10,000 people. To extend this into a place where there are 10,000 people instrumented across the boroughs of New York City gives access to multidimensional data in a way that we’ve never had before. One can think about it as the Hubble telescope of social sciences, moving the social sciences into the realm of something where we have evidence about people’s movements, people’s choices, people’s feelings, interactions between individuals.
Evans: Recently, we published a study that used all of the Amazon.com book purchase data, along with Barnes and Noble, and other online book purchasers to identify the association between preferences for political ideology books on their red or blue side, and all other consumptive science and literature. That’s a transaction trace, but also clearly reveals insights about the way in which people who hold or consume information about a certain ideology also consume other kinds of things.
We are also using eye-tracking data of a variety of types, which again, increasingly is able to provide really rich interaction signals. We’re able to instrument in ways that before were specific to like one or two labs. Now, you can run a virtual laboratory of 10,000 or 15,000 or 100,000 people and get detailed interaction traces that capture arousal and attention, and other things.
In another study, we took data for tens of thousands of publications related to gene/drug interactions in the literature and aligned them with data from a high-throughput experiment on gene/drug interactions that replicated about 1.7 million of those interactions. We used the trace of collaboration and a whole host of variables that we extracted from the original papers to predict, in some cases with enormous success, the degree to which different kinds of communities produced knowledge that was more or less replicable in the future. This would have been impossible without the ability to perform high-throughput experiments, on the one hand, or use computational tools to extract information in mass from publications, on the other.
In short, there is data that we previously didn’t think of as data; like full text, government documents, user-generated images and videos, from which we can pull signals which are, in some cases, enormously predictive.
Nusbaum: Finding signals that were heretofore unused or hidden or latent is interesting. That standard model of a meta-analysis, which you’re alluding to as an upgraded approach, the standard modeling of published research in psychology and other fields, is taking studies — specifically the summary statistics recorded in those studies — and analyzing them for consistency across conditions reported in the studies for those statistics. You’d say, ‘Oh look, nine out of ten studies, or 100 out of 150 studies show a certain kind of pattern of data consistent with the conclusions,’ so you have this sense of reproducibility. Now there are new methods of using data in publications that can lead to new insights.
For example, with functional magnetic resonance imaging (fMRI) papers — those publications have data tables in them, so the data tables have X-Y-Z coordinates corresponding to neural activity in specific spots in your brain. Instead of just taking summary statistics, an approach called NeuroSynth is used to recreate an idealized version of the data from the data tables from each of these studies, generating a new synthetic data set at a much finer grain resolution that the old approach to meta-analysis. This actually lets you do new experiments on data that has been published. This is a way of doing new studies that are a type of synthetic research.
Dialogo: Are conclusions in research stronger because of the volume of data that is available?
Evans: The answer to this question has to be ‘yes and no,’ right? Because the ‘yes’ acknowledges that, okay, we’re able to access data from new places, and at new scales. And the ‘no’ highlights that digital data is data from the wild, so to speak…data from transactions or data from clicks online, or from online activity, or dating sites, or wherever, has this deep problem of algorithmic confounding. You have data on choices (e.g., “clicks”), but those choices were given to you because it was predicted that they would most appeal to you, and so as researchers we don’t know what part of online activity is a result of people’s preferences, and the “smart” algorithms that were used to predict them. As a result, there’s way more data on these huge global platforms, but the platforms are smart and that smartness shapes the results of the experiment that you’re performing every time you go online and search for things. It creates enormous opportunities, enormous challenges.
Nusbaum: Every method, regardless of where it comes from, has its pluses and minuses. In the past days, social psychologists, sociologists, and political scientists would go to NORC (a social sciences research organization at University of Chicago) and collect stratified samples of data from populations according to a certain kind of model. Cognitive psychologists like me would run 10, 20, maybe 30 people if we were lucky, in our laboratories and collect data. Then Amazon came along with Mechanical Turk, and researchers started running studies online. We can ramp up a study now from 10 people in the lab to 1500 people (online) basically in a week.
And those people are sitting at home, perhaps watching TV while they’re doing a study. There could be kids running around and dogs barking. If you’re doing an auditory study, the quality of the headphones differs. We have to insert new kinds of quality control checks to see if people are actually engaged in a task. We have to collect demographics in a way we didn’t before. We have to find ways to collect online measures over the Internet. Yet, at the same time, we can see that we generally get very similar results from 1500 people in the field to 10 people in our laboratory. Because of that, it gives us a methodological reach in new directions that we didn’t have before.
At the same time, by going out on the web, we can now collect data from a wide variety of people. For example, there are supposed to be roughly one in 10,000 people who have absolute pitch, the ability to name the note when you hear a note played. As it turns out, we can find them all over the place, and if you set up a website and do testing for absolute pitch, we can start to bring them in to the site for testing. We can now get people with different kinds of backgrounds interested in doing our studies from all over the world. We never could have done that before.
That’s not big data, per se, but it’s a kind of reach into a data space that we didn’t have before.
Evans: It’s big sampling.
Nusbaum: It’s big sampling, that’s right. One of the things that is interesting about big data is we’re now trying to think about data in different ways. Scientists in social sciences who perhaps never thought about those issues are confronting those kinds of forces as well, grappling with how to think about the kind of person who has produced these data. How do you think about the framework and situation under which data was collected? What were the intents of the researchers compared to the participants?
Dialogo: What are some of the other challenges that come out of big data?
Evans: The institutions with the greatest sense or reach into human activity are not public researchers. They’re private companies like Facebook, and LinkedIn, and Google. They have more touches of more individuals than anyone else; any other government agency.
That creates a couple of different kinds of challenges. One is that there’s a hierarchy of access by selective individuals who have selective relationships with important people and these companies that creates a kind of random access to this data by the social sciences. A second associated challenge is that the government has decided to invest less in social science data, which puts at risk the possibility that more and more of the science that emerges from these social data streams becomes private rather than public science.
Nusbaum: There are also problems of meaning. For example, suppose you want to do a study that looks at the neighborhood safety of older people in different income brackets. How do you go about that? There are different ways of deciding what the meaning of safety is and how that translates into existing data or collecting new data, such as converting street view images from different addresses into visual measures of local safety.
The other problem that the data scientists talk about is sustainability. As more data is collected, it piles up and the set of data gets bigger and bigger. How do you organize the data? How do you organize and allow access to the data, maintaining privacy and security? How do you maintain reproducibility as opposed to replicability such that the same data can be processed by the same kinds of tools and get the same result or the same conceptual kind of tools even as software develops over time?
Evans: Reproducibility and replicability have become deeper issues on platforms that are constantly changing. That’s the polar opposite of something like a NORC survey, which has been the same for 50 years. Just the velocity of technological change for filtering out information from noise signal is changing dramatically. I completely agree with Howard that often data science teams are just looking for variation and they rediscover things over and over again that have maybe been discovered 50 or 100 years before in small scale data.
One of the biggest challenges for the new kinds of insight that comes from big data is that as social scientists we have a taste for certain kinds of questions and we like answers of a certain resolution that conform to a certain kind of story, in the same way that a blockbuster movie has to be between an hour and a half and two and a half hours. You can’t have a five-hour movie or a half-hour movie. It’s both a problem to digest those new studies and to take them seriously, but its also an opportunity, because it holds the possibility of expanding the collective imagination of the social sciences.
Nusbaum: Early on, the Journal of Cognitive Neuroscience required that every time you published a paper, you had to put your data in a central repository they maintained. The problem is data came from different scanners, different instruments with different properties, with different work flows, with different kinds of data structures. Nobody could easily make use of it.
Now there is the opportunity for somebody who doesn’t know anything about, for example, Alzheimer’s disease to basically analyze brain data in a unique way that psychologists or neuroscientists haven’t thought about, because we had preconceived notions of the disease. A computational approach that looks for data patterns can come up with some new information that can provide fundamental insights. Getting more of that behavioral and neuroscience in common formats that are publicly accessible with common data modeling and analysis tools is critical for making breakthroughs in a lot of areas.
Evans: But many of these methods are fundamentally not “statistical” yet. They’re so high dimensional. There’s no meaningful articulation of a confidence interval or anything like that because we have no precise sense of the search space that methods like multi-layer neural nets explore to identify their answers. And it remains unclear how these kinds of issues are going to shake out in the social sciences.
Dialogo: How is the availability of big data impacting methodologies?
Evans: We see it even in the traditional survey. Today – and this has really been pushed and piloted by social media and information companies like Facebook and Google – has been this development of what I’ll call active and interactive learning surveys, where you’re predicting the answer to the next question that a person might be posed.
Rather than asking a thousand questions, you might ask six personally sequenced questions to maximize that information, which means you have more space and time to ask about a whole host of other things. That’s a big shift using these models and using prediction in the context of performing survey and I would say observational data is similar.
Nusbaum: That’s an extension of an old process that’s taken place in other areas, often called adaptive testing. GRE uses this kind of adaptive testing. On the one hand, it’s efficient and often effective, and predicts performance in other circumstances. On the other hand, in other cases, it can miss out on some things. We know from work by people like (U.S.C. Professor) Norbert Schwarz that the context of the questions matters as much as anything. If the context changes by adaptive testing, then there may be things changing that we’re not aware of. One question primes you in one way. For example, if you say, ‘How good is your life?’ Then you say, ‘How good is your marriage?’ That gets one kind of ordering versus if you say, ‘How good is your marriage,’ and then, ‘How good is your life?’ It gives another kind of pattern of response. So thinking about those kinds of things are going to nuance the way we approach these things. That will be a developmental process, I think, over time.
Evans: This highlights that more than just forms of data gathering are changing. There was a recent paper by Tom Griffiths then at Berkeley, now Princeton, which talked about experimental design as algorithm design. The idea is when you’re using these algorithms to optimally collect data then, all of a sudden, the whole idea of collecting data and then analyzing it, with a strong wall between the two processes, doesn’t make sense anymore, right?
Nusbaum: We don’t have yet the precision of understanding our instruments in the way that physicists often do because they’re building them from scratch. Our instruments are much more context dependent than their instruments. The algorithms we use for designing our studies and the algorithms that we use for analyzing our studies are slightly mismatched.
Evans: By building these models, you figure out what is it that you know firmly, and what you know only loosely.
Dialogo: As big data continues to become bigger, what changes do you anticipate? What do you think will happen in future research?
Nusbaum: From my perspective, we’re seeing a convergence of different kinds of research methods. James and I were part of a common National Science Foundation research project. The conversations that we had suggested a common approach in conceptualization and different kinds of data that we can bring to bear on the same question.
One of the things we’re seeing in the social sciences is sociologists are taking blood spots. Political scientists are taking buccal swabs. Economists are doing fMRI and using methods from neuroscience. We’re getting biological data. We’re getting behavioral data. We’re getting location and movement data. We’re getting choice data. We’re getting all kinds of data, and it doesn’t matter what discipline you are coming from.
Finding the causal links between the individual and the group by looking at how the individual’s choices and behavior are influenced by the invisible forces of society is fundamental whether we’re talking about linguistics or psychology. Social science research moving in a direction where we can start to address that, because we have data with the grain of the individual and data with the grain of the group. We can look at the big forces, and we can look at the individual in relationship to them. That’s one place in which we’re going to have traction that we have not had good traction in the past.
One thing that relates to this notion of multiple levels of resolution that are studied by different fields coming together is a shift from what a focus on establishing necessary causal conditions to establishing sufficient conditions. This is a distinction that we talk a lot about in explanations in the social sciences. Is the factor that you’re observing necessary for the operation of a mechanism? Is it necessary for the outcome that you observe? Or, is it sufficient? With the integration of different perspectives, and with large-scale data, there is an increasing taste for sufficient explanations that hold in different contexts and situations.
That’s driven almost all activity in the quantitative social sciences over the last 100 years; find something statistically significant, but typically … it’s really small, not really substantial. Increasingly by integrating all these levels of analysis, we’re able to explain sometimes 90, 95, 98, 99 percent of the activity of an individual or of a group in a particular setting.
It changes a lot, right? This can make social science more potentially applied, because now we are talking about effects that are reliable but maybe not substantial, and we’re talking about reproducing phenomena. This shift in stance will provide more opportunities for us to quickly send insights out into the world of systems that generate values for people.
Evans: Our theories become shaped in a different way. That moves us closer to physics in certain ways. As theories about various phenomena become more complex, seeing the relationships among those kinds of structures becomes much more straightforward. We have this problem in genetics. People in genetics used to have these simple causal theories, ‘This gene produces this outcome.’ Now there are statistical theories, ‘This pattern of genes gives this population.’ There’s no causal theory there. It’s only a statistical association. They don’t go from genes to proteins to neurons to behavior, or structure. They’re in search of the same kind of problem and solutions that we are. They have very complex, highly dimensional problems with data, big data that relate these things. They don’t know how to connect them. There will likely be forms of theoretical solution that may be common amongst different fields now that didn’t used to occur because those disciplines weren’t viewed in common. I think that’s going to be a huge change.
Dialogo: Closing thoughts?
Evans: There are a number of different potential worlds that could come out of this Big Data moment. In one world, I could imagine that the computational social sciences and behavioral sciences move so quickly and aggressively, and adopt or embrace other epistemological levels of analysis and styles that they separate, and you are left with psychology, and sociology, and political science on the one hand, and you separately have a computational social science that has speciated from those things. On the other hand, you could have a world in which computational approaches just become the way of doing good sociology or psychology or economics, which brings all of those fields a little closer.
Questions also remain about whether the biggest tranches of data are going to be locked up in such a way that the science that comes out of them is really also locked up in databases and services, and can only be used by the proprietary producers of those things? Or, are they going to be become part of a broader interchange, and feed the individual social sciences that gave rise to them? I don’t know. I think none of us knows.
Nusbaum: This is particular challenge we see right now. 23andMe has collected many people’s genetic data. If you want to ask questions of and get a guaranteed 10,000 responses with genetic analysis, it’ll cost you six figures. Essentially, you can pay them hundreds of thousands of dollars and run a social science study on the genetic database and you have guaranteed results. If you just imagine the fact that there’s this huge database of hundreds of thousands of peoples’ genetic data as a potential pool that you could sample, consider what kind of social science you could do.
As neuroscience tools have become more effective and cheaper, there has started to be a schism within the field of Psychology. As a cognitive neuroscientist, you might be using fMRI to address basic questions of mechanisms in language understanding and decision making, and you train students in neuroscience methods and forget about the deep theoretical background coming from psychology. There is now a whole cadre of people studying brains and forgetting that we know a lot about behavior and psychology. Hopefully in the future these perspectives will be merged together. In fact, as we’ve seen more biological methods used in other parts of the social sciences, there’s a hope that actually there can be a broader convergence of disciplines and methods, moving from the past separation of psychology versus sociology versus political science to have better understanding of the questions and theories that span the social sciences. I think that’s a real opportunity that’s been missing for a long time.
Read the article: Dialogo. (2018, May 2). Common ground: Howard Nusbaum and James Evans. UChicago Social Sciences. Retrieved from https://dialogo.uchicago.edu/content/common-ground-howard-nusbaum-and-james-evans
Howard C. Nusbaum is the Stella M. Rowley Professor of Psychology and director of the Center for Practical Wisdom at the University of Chicago. He is internationally recognized for his multi-disciplinary studies of the nature of wisdom and the cognitive and neural mechanisms that mediate communication and thinking. Nusbaum’s past research has investigated the effects of sleep on learning, adaptive processes in language learning, and the neural mechanisms of speech communication. His current research investigates how experience can increase wisdom and produce changes in insight and economic decisions, and examines the role of sleep in cognitive creativity and abstraction. He is a scholar with Virtue, Happiness, & the Meaning of Life.
James Evans is a professor in the Department of Sociology, director of Knowledge Lab at University of Chicago, and faculty director of the Masters program in Computational Social Sciences. In his research, Evans explores how social and technical institutions shape knowledge—science, scholarship, law, news, religion—and how these understandings reshape the social and technical world. He has studied how industry collaboration shapes the ethos, secrecy and organization of academic science; the web of individuals and institutions that produce innovations; and markets for ideas and their creators, as well as the impact of the Internet on knowledge in society.
Note: This post is an excerpt of “Narrative Identity: What Is It? What Does It Do? How Do You Measure It?” published March 1, 2018 in Imagination, Cognition, and Personality. Read the full article here.
Psychology’s turn toward narrative in the 1980s was a logical extension of its gradual emancipation from the behaviorist grip. It may have been inevitable that once empirical psychologists defied the strictures of behaviorism to peer inside the black box of the human mind, as they began to do in the late 1950s and 1960s, they would eventually happen upon the idea of story. After all, human beings the world over love to tell and hear stories, as Bruner (1986) and Sarbin (1986) both observed. Human beings routinely adopt a narrative mode of thought and expression, Bruner wrote, when it comes to explaining why people do what they do. He distinguished the narrative mode from the paradigmatic mode of thought, which employs logic, evidence, and argument to explain instead how the (physicochemical) world works. Sarbin went so far as to anoint narrative as the new root metaphor for psychological science. Human beings are storytellers by nature, Sarbin argued. Human conduct seems to obey narrative rules. People think about their own lives, and the lives of others, in narrative terms, as stories unfolding over time (Polkinghorne, 1988).
Outside of psychology proper, social scientists and humanists of many different persuasions became enamored with narrative in the 1980s and 1990s. A central question running across many disciplines during this time concerned the function of narrative: What do stories do? First and foremost, they entertain us, some scholars argued (Brewer & Lichtenstein, 1982). Stories engage human emotions, and when they do not, they fail. What is the worst thing you can say about a story? That it is boring. From the parables of Jesus to Dickens, stories also provide instruction on virtue and morality, on how to live a good life (Coles, 1989). Throughout human evolution, even before language when people enacted narrative in gesture and dance, stories have functioned to simulate social experience (Mar & Oatley, 2008). When we read a good story or watch a good movie today, we observe social interactions up close. We witness the clash of human intentions and the timeless social conflicts and motivational dilemmas that characterize so well what human life has always been about. It is probably no exaggeration, then, to claim that stories teach us how to be human (McAdams, 2015).
Narrative identity is a special kind of story—a story about how I came to be the person I am becoming. With this special status comes the special function, a function that Erikson (1963)assigned to identity itself. It is the function of integration. Narrative identity brings things together, integrating elements of the self in both a synchronic and a diachronic sense (McAdams, 1985). Synchronically, narrative identity integrates different social roles (Dunlop, this volume), values (Pasupathi et al., this volume; Wang, Song, & Koh, this volume), attitudes, and performance demands in the variegated here-and-now of life. A person’s story, thus, explains how he or she continues to affirm a sense of “inner sameness and continuity” (Erikson, 1963, p. 251) across different situational and role contexts. The life story also integrates life in a diachronic sense, that is, over time, ideally showing how the self of yesterday has become the self of today, the very same self that hopes or expects to become a certain kind of (different but still similar) self in the future. Concerns about both synchronic and diachronic integration—self-unity in space and time—are salient in Holm and Thomsen’s (this volume) study of self-event connections, self-concept clarity, and dissociation.
Since the 1980s, psychologists have identified a number of other potential functions of narrative identity. As the most notable example, Bluck and Alea (2011) have enumerated (and developed a measure to assess) three primary functions of autobiographical memory in everyday life. People may call upon stories about their personal past to serve social, directive, or self functions. Telling autobiographical memories may promote social relationships; people enjoy sharing stories about their lives with each other. Autobiographical memories may also provide guidance (directives) for life. When confronting a difficult decision, for example, a person may call up memories of similar events in his or her life, consulting them for advice, mining them for insights that may prove helpful in the current situation. What Bluck and Alea put into the domain of functions serving the self includes promoting self-continuity (diachronic integration) for sure, but it also includes the ways in which memories may be called upon to boost morale or sustain positive self-regard. In this light, Liao et al. (this volume) found that positive meaning making in self-defining memories predicted enhanced self-esteem one year later.
In adopting a developmental framework for understanding narrative identity, Fivush, Booker, and Graci (this volume) bring together issues regarding both function and form. They point out that life story construction is constrained by the exigencies of the developmental period during which a narrator aims to make sense of the past. The same event, then, can mean very different things for the same person at two different points in time (Josselson, 2009). At an early age, for example, the narrator may lack certain skills in autobiographical reasoning that would otherwise enable him or her to discern a significant theme or insight from the event, or connect the event to similar others (Habermas & Bluck, 2000). When those skills come online later in development, the person may now understand that same event in very different terms. In this regard, McLean, Breen, and Fournier (2010) have shown that unlike older individuals and unlike females, early-adolescent boys who narrate negative experiences in highly elaborative ways do not enjoy higher levels of psychological well-being. Young adolescent boys may lack the autobiographical skills to process aversive life events in a psychologically productive manner.
Whereas developmental level may constrain meaning making in narrative identity, meaning making efforts may also catalyze development. Fivush et al. (this volume) describe the process of making narrative sense out of life as a mechanism for self-development. The performance of narrative identity may function, therefore, to refine meanings and thereby help the narrator attain a better understanding of self and reach a higher developmental plateau. Elaborating upon the distinction between narrative as window and narrative as process, introduced by Grysman and Mansfield (this volume), Fivush et al. (this volume) contend that narrating life experiences is indeed a window into the current developmental dynamics and parameters that prevail in a given life, but also a process that may promote development itself.
Dan P. McAdams is the Henry Wade Rogers Professor of Psychology and Professor of Human Development and Social Policy, and former chair of the Department of Psychology at Northwestern University. He is the author most recently of THE REDEMPTIVE SELF: STORIES AMERICANS LIVE BY (Oxford University Press, 2013) and THE ART AND SCIENCE OF PERSONALITY DEVELOPMENT (Guilford Press, 2015), and President of the Association for Research in Personality. McAdams is a scholar with Virtue, Happiness, & the Meaning of Life.
When I sent in my application to be a part of the Virtue, Happiness, & the Self-Transcendence seminar, I was certain that I would benefit from participating but I was not quite sure how much. Now, after the experience, I am really glad that I was part of it. I found it intellectually stimulating and very helpful. I learnt a lot from everyone. The keynote speakers and other participants were ready to discuss my research topics and the discussions that I had with them gave insights for developing my work both as a lecturer and as an early career researcher. For example, Professor Candace Vogler gave me wonderful suggestions for improving my teaching, and I have been able to apply some of them in my classes in Lagos. In addition, the discussions in the sessions helped me to gain a deeper understanding of the topics of virtue and happiness. I learnt a lot from the interactions between the scholars. Those discussions I had with everyone made me want to study more and understand these topics better.
After the seminar, I came up with questions I emailed to the scholars I met in the seminar. I have been pondering over the themes of the discussions since the summer ended, and some more questions come up in my mind when I reflect on my experience from the seminar. The seminar reinforced my interest in interdisciplinary research work and the discussions and the subsequent emails from the participants, (e.g. Dan P McAdams, Timothy Reilly) gave me ideas for future directions in my research.
One of such questions was about the evolution and development of the self and how to interpret and integrate information, research results and ideas from psychology and the humanities while trying to understand human life. The discussion that I had with Tim and Maureen during the seminar and the emails afterwards, were really helpful. They suggested looking at the topic from the perspective of developmental psychology, while seeking themes that may be congruent with philosophical frameworks of the good life. I would like to explore these topics in future research.
What was the best part of the experience?
I think that the best part of the experience for me was being able to reflect about a topic that the participants and keynote speakers had explored from different perspectives. The scholars from the different fields gave a deeper understanding of the same topics in different lights, and I found it very interesting to see some of the different perspectives and views across fields and to see their commonalities identifiable from the discussions. Oftentimes, scholars from different fields use the same words to describe concepts that are similar and one can think that different fields are referring to the same concepts and content. However, the use of the same terminology may carry different connotations or meanings. Even while studying a concept within the same field, the depth of the meaning attributed to a specific concept may differ significantly. For example, I discovered that narrative psychologist’s concept of virtue is understood quite differently from what I thought I understood from my personal study of psychology. I discovered that the relationship between virtue and the ultimate good for human beings which is clear within classical Aristotelian philosophy ought not to be imposed on psychology’s notion of virtues. Even though both fields use the same words for similar concepts of habits which foster human flourishing and wellbeing, the Aristotelian concept of virtue is tightly linked to the ultimate good of the person found with the best use of his highest faculties, while this link is not so clear with psychology. Therefore one would need to be more attentive to such details when comparing results of studies from these two fields. Being able to speak and exchange ideas with scholars whose works that I had studied helped me to clarify my doubts about what I had understood from personal study.
What did you learn that you didn’t know before?
One of the many things I gained is a deeper understanding of Immanuel Kant’s anthropology and a moral philosophy. The concept of the highest good in Kant’s moral philosophy is a topic which was relatively new to me and I gained a lot from discussions on that topic. The discussions on Aristotelian concept of philia, identification and identity also gave me deeper understanding of friendship.
Additionally, I spoke with Dan P Mc Adams, whose work I had studied for my PhD thesis and to understand his thought better. After the seminar, he sent me an email explaining some points in the evolution of his thought to me which I had not known before. For example, he noted that the original idea in his early work on narrative psychology presents the role of narratives in the heroic quest to make grand meaning. Now, one discovers that narratives are one among many other tools for that quest.
How did the interdisciplinary nature of the seminar open new possibilities for your research?
My PhD thesis had an interdisciplinary approach and meeting people who work with an approach similar to mine helped to discover points of dialogue.
I am currently thinking of a research project on virtues and values in education in Nigeria and I hope to engage some of the scholars whom I met at the seminar. I am still in the idea stage. Additionally, I think that some of the projects which the participants were working on can be replicated in my country. I expect that applications of the discoveries from such projects will foster human flourishing, virtue and happiness in my context. It is true that the methods, the specifics of such investigations and the findings in my country may differ from those in other contexts. However, I think there will be significant proportions of commonalities in the general framework for such investigations and findings and it would be interesting to discover points of confluence that cut across cultures. For example, even though the specific manifestations and applied nomenclature of some of the cardinal virtues may be different in different cultures, one may be able to find that there is some essential concept which stems from each virtue that is common to all.
On the whole, I am quite happy that I participated in the seminar as I am sure it has contributed to my development. I believe that it is the beginning of intellectual dialogue and mutually enriching interactions.
Omowumi Ogunyemi obtained her first degree in medicine and surgery. She has worked as a medical practitioner in various hospitals in Nigeria including The Federal Neuro-Psychiatric Hospital, Lagos, where she co-managed patients with substance-induced disorders. She holds a licentiate degree and a doctorate in philosophy (Anthropology and Ethics) from the Pontifical University of the Holy Cross, Rome. Currently, she lectures in the Institute of Humanities of the Pan-Atlantic University, Lagos, Nigeria. “Molly” Ogunyemi was a participant with the 2017 Summer Seminar, Virtue, Happiness, & Self-Transcendence.
Join researchers and practitioners from over 30 countries at the 2018 Meaning Conference, a “big tent” gathering known for its inclusivity, integration, and innovation in meaning research and its applications since 2000.
The conference will also celebrate the International Network on Personal Meaning’s 20th year anniversary jointly with founder Dr. Paul Wong’s 80th birthday. Paul Wong is a scholar with the project Virtue, Happiness, & the Meaning of Life.
August 2-5, 2018 | Vancouver, Canada
Early Bird ends May 31, 2018 at 11:59 PM (EST).
This conversation is reproduced from “Common Ground: Emily Talen and Marc Berman,” Dialogo: UChicago Social Sciences. LINK
Emily Talen and Marc Berman
DIALOGO: What big questions motivate your research?
TALEN: I spent my senior year in college in Paris. I was homesick, so I ended up just walking every inch of the city. As a sociology major, I was interested in cities from a built environment perspective and appreciating public space, great architecture, and great urbanism. Paris is different because it’s so planned. There has been forethought put into the way its public spaces, its streets, the frontage quality, everything about the city somebody’s thought about it. That contrasts with the suburban sprawl that I grew up in, where it’s much more driven by the bottom line of buying and selling, and much less attention given to public space mostly. Throughout my career, I’ve focused on what we can do to intervene and actually make things happen. In Paris, there was intervention, and you got Paris. I mean, we have so little of that in the US. In Chicago, sure, you can point to some good public spaces, but the design of the city is just not that thought out. There’s a lot to study there. Why did that happen? Where does it work? Where does it not work? What’s the fall-out of not being good city planners? Why does that happen and what’s the effect? It’s been a rich source of things to tap for a research agenda.
BERMAN: I’m interested in how the physical environment affects brain and behavior. A lot of people have this misconception that because humans have so much control over the environment, that we’re sort of immune to it — but the environment plays a huge role in our behavior, and we’re not even aware of it. We started to do some studies where we had people walk in nature versus more urban environments, and we found that people could improve their memory and attention by about 20% if they just went for a short walk in nature, versus a walk in a more urban environment. Much of our research is trying to figure out why. And also to touch on what Emily was saying, that at least in the US/North America, we haven’t done that good of a job in terms of designing cities for human psychological functioning. It’s good for moving goods and for housing people efficiently and things like that. But is it good for having a populace be the most productive they could be, or to have the highest wellbeing? I think we’re lacking in that area. As a lab, we are working to incorporate some of these elements of nature that we think are good for human psychological functioning, for human brain functioning, and retrofit those elements into cities.
TALEN: To me, a baseline question is how much attention is paid to the public realm, as opposed to the private realm. You go to some cities and think to yourself, “They’re really focused on the private world.” As an example, I usually pick on Phoenix because that’s where I was for some years. That built environment is reflective of people having their own internal worlds. You drive down the street, it’s nothing but walls separating different housing pods. How much of the public ground was cared for? That means everything from how the building meets the street to actual public spaces to the width of the sidewalk. How are people moving around in the city? Is it efficient for them to do, and do they have to rely on a car, which is bad for the environment? Even electric cars, self-driving cars, aren’t that great either because there’s a lot that goes into fabricating and manufacturing of an electric vehicle. I want people to just walk. To what degree are cities good for human beings to go out and use their two legs? In some ways, it’s just that simple.
BERMAN: That’s a big problem. Think about how much in this country, too, we have problems with obesity and lack of exercise. It’s difficult to take time out to exercise, but if walking is a part of your daily routine, you will get some exercise there. I mean, that’s kind of what recent Nobel laureate Richard Thaler says, “If you want somebody to do something, make it easy.” We make it really hard in our current society to exercise and do other healthy behaviors. I mean, we’re not meant to just sit in a car and go places. We’re meant to move around — there’s all this research about how exercise is good for cognition and mental health, not just good for physical health. That’s a huge element to this. Also, by having these huge roads many of the natural elements that you could have if you had a more walkable kind of space are destroyed.
To pick up on that idea of what’s natural, how do you define natural when you’re looking at these questions?
BERMAN: In the first study where we had people walk in an arboretum versus in a busy urban environment, we made the distinction ourselves. We’ve done studies where we show people pictures of nature versus pictures of built spaces. They’re not as strong as actual walking, but they are similar and suggest that there’s something about the visual aesthetic of nature that might be contributing to these cognitive benefits. Could it be the fractalness of nature, the amount of curved edges, the color palette? People have lots of different conceptions about nature versus urban. To someone who is an avid hiker, for example, a city park might not seem that natural. To somebody who is a very urban person, it might seem quite natural. The kind of nature that we’ve been researching thus far has been nearby nature in cities.
TALEN: Do you worry about defining cities as unnatural? If the urban is unnatural, we might somehow forgive poorly designed urbanism because, well, it’s not natural.
BERMAN: This is a good point. And people do see naturalness in buildings. We’re doing a study now where we’re showing only buildings to people, and they are seeing nature in some of these buildings. A Gaudí building in Barcelona is rated as more natural than a very 1960s cubic kind of architecture, which is rated as very unnatural. Our algorithms can predict whether something will be perceived as natural or not because it mimics patterns in nature, even though there’s nothing “natural” about it. It’s an entirely built structure. Look in this room here. This room has a lot of patterns in it that mimic nature, so you can construct environments that look like nature, even if they aren’t nature. That’s not exactly what we’re advocating for, although I think we should be thinking about that as well.
Do definitions of nature play into the way neighborhoods and cities have been managed?
By Lynn Betts / Photo courtesy of USDA Natural Resources Conservation Service., Public Domain, https://commons.wikimedia.org/w/index.php?curid=24785226
TALEN: This is how we’ve gotten into trouble. In some ways, suburban sprawl is a quest to be near nature, right, but it ended up backfiring, with people having a sense that they’re closer to nature when really they were undermining nature. That’s set up a tension and confusion about how we should be designing cities and the place of nature in cities while we’re trying to be compact and have a lot of proximity between what people need in their daily lives and where they live. How do you bring nature into that in a way that doesn’t then spread everyone out and end up being bad for nature? That’s an interesting urban design question. In some ways, Paris has been good at bringing in nature in a way that is not destructive, and still being very compact and dense. They’ve sort of formalized nature, nature exists in very manicured small settings. When we bring nature in here, it’s all these big parks, or it’s suburban sprawl. We don’t know how to have the best of both worlds.
BERMAN: I think another area to touch on, too, is the physical space and the pattern of behavior. Suburbs might have more “green space” but people’s behavior is less natural, right? You’re going into your car, you’re zipping around. In cities, if you’re walking to places and if your social interactions mimic the environments that humans have lived in for a longer period of time, that in some sense is more natural than living in the suburbs, even though there might be more green space there. That’s another layer to add onto the physical environment —interactions with that environment and the patterns of the human behavior.
Light Detection and Ranging (LiDAR) data for Cook County (O’Hare airport excluded) with 7 landcover variables plotted; Dark green = Tree Canopy, Light Green = Grass/Shrub, Pink = Bare Soil, Blue = Water, Red = Buildings, Orange = Roads, and Gray = Other paved surfaces. Within a county, there is notable variation in the balance of urban and natural elements.
TALEN: Have you heard of the transect? It’s a way of thinking about cities along a transect, a line, where you cut a line from rural to urban, and at every spot along that line you try to form cohesive environments depending where you are on the line. If you’re on the rural end, you don’t get those urban level services. As you move in and you don’t have as much nature, you have lots of services. Some people have been trying to think about zoning our cities that way. Zoning is a total mess, total disaster, it makes no sense. If we zoned our cities to be those immersive kind of coherent environments along the transect, we’d have better cities.
Does looking at how things have historically been organized in cities like Chicago help explain how things got this way? Does it suggest how we can get out of it?
TALEN: I’m focusing right now on retail, working with a post-doc and looking at small, independent, mom-and-pop shops. Where they are in the city, and where they’re dying. There’s an existential crisis in retail — first it was the big boxes, now it’s e-commerce. So what does that mean for our street life? If it’s not going to be retail, then what’s it going to be? The big boxes are not so good at activating street life. Streets are the most public land that we have in the city, by far. Do we want our cities to be composed of streets that are just conduits for cars? So we’ve been mapping out every block in the city of Chicago, looking at where are the mom-and-pop stores and what kinds of environments are they located in. And now I’m sending students out with a survey to ask these retailers how they are doing. Are they connected to the neighborhood? What is the future from their perspective?
There’s been a lot of hand wringing about bad decisions that were made — basically, everything between 1930 and 1990 was a total disaster for urbanism. The focus on urban renewal, tearing things down, putting in big highways. Really, really bad mistakes were made, globally. There’s a lot of attention paid to not repeating those mistakes. That’s why I brought up autonomous vehicles. The circles I run in, which is all about walkable urbanism, are very leery about that because it’s the next technological fix, and it sounds so much like the discussions that were going on in the 1950s: “Oh, look at these big highways. Everybody will be able to just drive everywhere.” You’ve seen these utopian “Jetsons” kind of worlds that were envisioned, and it’s the same thing going on now.
There’s not a lot of nature in those images of the Jetsons future.
TALEN: Right. No, no. There’s no nature there. I show some of these films in my classes, and the students are just amazed at the thinking that was going on. Futuristic city thinking, but we actually constructed a lot of the nightmare that didn’t pan out. That’s why relying too much on technology makes me nervous. How do you think, Marc? Do you agree?
BERMAN: It’s an interesting question about these autonomous vehicles, and if they just perpetuate this driving culture, that’s not desirable. I guess the technology is going to come whether we like it or not. We’re using some of the technology to quantify the benefits of cities. We’re developing apps like the ReTUNE app so if you want to get from point A to point B, it will give you the most restorative walk or route that has the most green space, the least amount of traffic, and is the quietest, and safest. I think walk-ability is a huge thing, and it also needs to be something that has to be equitable. Naomi Davis, who has a non-profit in Chicago called Blacks in Green, talks about one square mile, about having African American neighborhoods where you can get everything in one square mile (i.e., workplaces, shopping, entertainment, etc.), which is really not true in current times. All these things are highly related to each other and might foster better social interactions, which could have lots of other types of positive downstream consequences.
Another theme that Emily and I talk about is this movement to slow things down. We come up against this with mobile technology and phones. We’re each interested in how interacting with nature gives people a chance to be kind of contemplative and reflective, which is something that people don’t do a lot now because they distract themselves with music, social networking and other things. One of the reasons why we think interacting with nature might be beneficial is that it kind of forces people to be alone with their thoughts, and that’s why when we did the studies we kept cell phones in the lab. We made them go out on their own to force them to interact with the environment. And we found amazing effects. The weird part about the mobile technology is that it’s an addictive technology. Usually, things that are addictive are not really good for you.
Can nature be addictive?
BERMAN: I suppose it could. It’s hard for me to conjure up a lot of negatives. Whenever I talk to people about this and say, “we need to interact with nature more,” nobody ever argues with me about it. They may argue with me about why it works, but nobody argues with me that it does.
One misconception about nature is that it’s all about mood or pleasantness or something. It’s more than that. Something else is going on there. Certainly, people tend to get into better moods when in nature, but that doesn’t seem to be the driving factor for these kinds of attention and concentration benefits that we see. One reason could be that our brains evolved in these more natural types of environments. When we did our study in Ann Arbor, we had people walk at different times of the year. Some people walked in June, when it was 80 degrees Fahrenheit. People loved the walk, and showed these really healthy memory attention benefits. We also had people walk in January, 25 degrees Fahrenheit. People said, “Marc, I was freezing my butt off out there. Why did you make me go out there?” But they showed the same memory and attention benefits as the people that walked in June. You didn’t even have to enjoy the nature interaction to get the cognitive benefit.
Now, the trick is figuring out what is it about this environment that’s producing these benefits? Also, what is it about how our brain’s are organized and how they function that we’re seeing this kind of synchrony between the brain’s processing of natural environments?
Is there room to collaborate on all of these questions? What would that look like?
TALEN: Urban planning is, by definition, very interdisciplinary. There are different wings of urban planning, and certainly the exciting part of urban planning is where it intersects with another discipline like psychology, like architecture, like sociology. “Innovation at the margins of disciplines” — I think it’s true with urban planning. The trick is to not get too disparate with all these different fields and lose sight of the end game, which is that we want better designed cities. How do we take all that interdisciplinary thinking and corral it back into what is sort of a more narrow focus, which is, can’t we just have cities that look like Paris? Why can’t we?
BERMAN: We want to know how to design the environment for better human psychological health. That can mean a lot of different things. In talking with Emily, she’s brought variables to mind that we haven’t really thought about, like having people map out where all the mom-and-pop shops are — we can incorporate that into our models where we have green space over the whole city, and we have health variables of people all over the city, crime in the whole city. We can start adding all these different variables in and see what’s predicting crime, what’s predicting disease, school performance, things like that. To me, it’s exciting that with big data we may actually be able to quantify some of these things. To say, well, when you have this many mom-and-pop stores, a reduction in car traffic, and you have 12 more trees per city block, you can reduce cardiovascular disease by 3% and crime by 5%. I think we’re moving in that direction. There’s a lot of people on campus that are very interested in these issues. It’s an exciting time.
Emily Talen is Professor of Urbanism in the Division and Director of the Urbanism Lab at UChicago. Her research is devoted to urban design and urbanism, especially the relationship between the built environment and social equity. Studying the making and unmaking of neighborhoods in cities like Chicago, Talen (who worked as a professional planner in California and Ohio before entering academia) looks for ways to improve the form and pattern of American cities and neighborhoods so they can be more inclusive and supportive. In a book currently underway, Talen explores the ideal of the neighborhood, comparing a wide range of perspectives on what makes a neighborhood, and the relationship between idealized neighborhood plans and reality. An earlier book, City Rules: How Regulations Affect Urban Form, looked at urban codes over the ages — showing that while many contemporary codes stifle communities, encouraging sprawl and even blight, revised codes can produce a more positive outcome.
Marc Berman is an Assistant Professor in the Department of Psychology and is involved in the Cognition and Integrative Neuroscience programs. His research centers on understanding the relationship between individual psychological and neural processing, and environmental factors. Berman’s Environmental Neuroscience Lab uses brain imaging, behavioral experimentation, computational neuroscience and statistical models to quantify the person, the environment and their interactions. Recent studies from the lab have determined that the density of trees in a neighborhood has positive effects on individual health comparable to being younger and wealthier, and have identified elemental features of natural and man-made environments that influence individual preferences, and also memory, attention, and mood. He is a scholar with the project Virtue, Happiness, & the Meaning of Life.
Prior to the 2017 summer seminar, my research exposure was mostly on the field of Psychology. My collaborations were also limited to the Psychological discipline; hence, my understanding of the world was mostly influenced by the psychological frame. The best part about the experience was the interdisciplinary nature of the discussions. It was truly refreshing to be among philosophers and theologians who enlarged my understanding of virtue, happiness, friendship, meaning in life, and self-transcendence. I was not limited to a psychological standpoint, which usually automatically involves operationally defining virtue and happiness in measurable ways. The engaging and meaningful conversations I shared in and outside the sessions enriched my understanding and deepened my appreciation of pursuing knowledge for its own sake. I am also grateful for the cultural exposure through the faculty and my co-attendees. Prior to my attendance in this seminar, I only learned about other cultures vicariously through books, scientific papers, and movies. The interactions and conversations I have had with everybody from the summer seminar contributed to a deeper appreciation for cultural diversity.
Studying the constructs from a philosophical lens contributed to a holistic understanding of these constructs. It reminded me of the intimate history of Philosophy and Psychology as academic disciplines. This, in turn, inspired me to keep the philosophical perspective in mind as I currently write my dissertation proposal. The dialogues I’ve had with the other seminar attendees have also helped me clarify my own research agenda. I came to the seminar with a rough idea of what I wanted to study but I came out of it with more questions, which have been valuable in helping me tease out what I truly wanted to investigate. Continue reading “Samantha Mendez: “Musings from the VHML Summer Seminar 2017””