"Give Us This Day Our Daily Breadth"

Distinguished Professor of Education Greg Duncan, President of the Society for Research in Child Development (SRCD), delivered the Presidential Address at the 2011 Biennial Conference in Montreal, Quebec, Canada, on April 1, 2011. The following is the text of his address.

Give Us This Day Our Daily Breadth
Society for Research in Child Development Presidential Address
Montreal, Quebec, Canada
April 1, 2011

PowerPoint to accompany address

[Slide #1] One of my favorite New Yorker cartoons shows Christopher Columbus at the court of King Ferdinand. Columbus has just returned from his historic voyage, only to be greeted by these words: “Just tell me about the new continent. I don't give a damn what you've discovered about yourself.”

I will ignore this admonition and proceed to tell you a bit about myself.

My early career was shaped by my economics training and a quarter century spent at the University of Michigan’s Institute for Social Research. Child development was a personal but not professional interest for most of those years. My work centered on the longitudinal study that I was involved with for nearly a quarter century – the Panel Study of Income Dynamics – which, as we shall soon see, continues to document the dynamic nature of families’ economic and demographic fortunes within and across generations. 

The Institute for Social Research was and is a profoundly interdisciplinary institution. [SLIDE #2] James Morgan, shown here with Tom Juster, was my primary mentor in my early years, but giants like Rensis Likert, Angus Campbell, Robert Kahn and Robert Zajonc also roamed the halls and manned the communal coffee tables.

My initial immersion into developmental thinking came in a research network organized in 1988 by the Social Science Research Council. The network’s mission was to understand the neighborhood effects embodied in William Julius Wilson’s seminal book The Truly Disadvantaged. Larry Aber, Tom Cook, Jeanne Brooks-Gunn, Jim Connell and others in the group would hold forth for hours. But I often had no clue what anyone was talking about. I stuck with it, though, made lifelong friends and started to figure some things out.

Of the more than 150 collaborators I have published with during my career, the overwhelming majority have come from disciplines other than economics – including, I might add, my esteemed Québécois colleague, sociologist Johanne Boisjoly, who is in the audience this evening. My greatest professional debt is to Jeanne Brooks-Gunn [Slide #3], who immediately saw the value of harnessing some of the ideas and methods used by economists like me for the sake of understanding the roles of family, neighborhood and policy contexts in children’s lives.

The need for breadth

[Slide #4] The Nobel laureate economist Frederick von Hayek once said: “The economist who is only an economist is likely to become a nuisance if not a positive danger.” Many economists have taken this to heart. Several have partnered with Daniel Kahneman and Amos Tversky to bring principles of cognitive psychology into the economics of decision-making. Neuroscience enriches behavioral economics with its use of functional neuroimaging and other methods to understand what is going on in the brain as we make decisions involving risk and present/future tradeoffs. And economists have a decades-long history of testing some of their theories using animal models, [Slide #5] for example establishing once and for all that rats and pigeons will consume less food as the effort required to secure it increases. In other words, they have downward sloping demand curves.

In contrast to these interdisciplinary successes, few insights from developmental psychology have penetrated the conceptual models or empirical methods that economists and, I might add, many sociologists use in their numerous studies of child well-being. Until very recently, economic models assumed an undifferentiated single period of childhood in which optimizing-investment decisions are made by parents or governments on behalf of children. If adolescents are studied, they are typically assumed to be as fully rational in their decision making as adults. Psychometric considerations are typically ignored, and mediational models are rarely seen.

Worse yet, all child capabilities other than IQ and achievement are often lumped into a single category and termed, of all things, “noncognitive.” [Slide #6] As a result, economists’ empirical studies throw attention problems, anti-social behavior, mental health, motivation, self-esteem, locus of control and whatever other measures happen to be available in the data set at hand into a single index of “noncognitive skills.” 

There are, of course, a number of important exceptions to this broad-brush tarring of my economist colleagues, but the point remains that developmental psychology is generally invisible within these disciplines. As a frequent reviewer of proposals and manuscripts submitted by economists and sociologists regarding child well-being, I find myself repeatedly encouraging authors to incorporate at least the simplest insights from developmental psychology into their conceptual models or empirical methods.

And what about the reverse? To what extent does developmental science open itself up to the models and methods of other disciplines? One testament to SRCD’s interdisciplinary character is the requirement that every third president come from a field outside of developmental psychology – an affirmative action policy that has brought me before you tonight.  I am pleased to note that I am not the first economist to be president of SRCD. That honor goes to Lawrence Frank, who served between 1944 and 1945. Frank headed the Laura Spelman Rockefeller Memorial Foundation and used that position to fund nine Child Welfare Research Institutes in major universities in the United States and Canada. His publications include Nature and Human Nature and the 1953 classic Babies are Puppies, Puppies Are Babies.

But the vast majority of SRCD members are developmental psychologists. As a frequent reviewer of proposals and manuscripts submitted by developmental psychologists, I find myself repeatedly urging authors to incorporate even the simplest insights from the models and methods of economists and sociologists. Enough of this disciplinary balkanization!

I would like to spend my remaining minutes making the case for breadth, for combining insights from different disciplines and methods in new and imaginative ways. [Slide #7] Referring to evolution, the French biologist and Nobel laureate Francois Jacob observed that “to create is to recombine.” So it can be with the social, behavioral and biomedical sciences.

Let me be clear that by “breadth” I mean true integration of disciplines at the levels of concepts, assumptions, theories, methods and interpretation. In a wonderful essay on interdisciplinary scholarship, Aletha Huston invokes the metaphor of young children’s peer interactions.  [Slide #8] The first stage is parallel play—side-by-side but essentially independent activities, with a research example being a conference in which scholars from different disciplines present papers on a common general topic. Associative play consists of independent activities using a common set of materials, as with children pursuing their own projects in a sandbox or, in research, mixed-method studies if the research teams using the different methods are not working closely with one another.

Cooperative play involves truly interdependent interactions. Here Aletha uses the example of children working together to build one structure, with each child placing blocks on those added by others.  In the case of research this conception of “breadth” means interactions among disciplines in which each builds on, and is responsive to, the others. I have found that drawing together disparate ideas about development and methods from different research traditions can be time-consuming and frustrating, but also deeply rewarding – personally and perhaps also for the promotion of science, policy and practice.

I will make my case for breadth using examples from research on the effects of poverty on children’s development. I first argue that poverty research needs a genuine life-span perspective, beginning in utero and stretching well into adulthood, and it needs to embrace early biology as a key dimension of development.

I then show that the macroeconomic dimension of poverty and affluence – in other words income inequality – appears to be highly consequential for child development. I look next at innovative methods of estimating causal impacts of income policies on child outcomes. All of these issues are best addressed through interdisciplinary collaboration. I close with some thoughts about how we might promote this kind of “cooperative play.”

Not enough boxes and time

Another favorite New Yorker cartoon depicts a couple bringing their baby home from the hospital The baby is scowling as it surveys its new home, thinking, "Oh, great - humble beginnings." Only in the New Yorker could “humble” be depicted with two well-to-do parents and a nice apartment. Truly humble beginnings for nearly quarter of America’s children mean family income below the poverty line, currently around $17,000 for a family of three. [Slide #9] The standard developmental model of family poverty posits two important ways in which growing up poor hurts children. First is the “income” pathway. Higher-income parents can buy more books, horizon-broadening travel, higher-quality child care, better schools and safer neighborhoods than their poor counterparts.

Second is the maternal stress pathway, which emphasizes how the day-to-day stresses of poverty can compromise parents’ mental health and the quality of interactions with their children.  Taken together, these two pathways are thought to translate poverty into lower achievement and worse behavior when poor children enter school, and this may overwhelm the compensatory efforts of schools to level the playing field by the time children transition from adolescence into adulthood.

Before concentrating on the shortcomings of this model, let me praise its utility and durability. Vonnie McLoyd’s work on the parental stress pathway helped to stimulate voluminous research on the consequences for children of maternal depression and harsh parenting. The 1997 book Consequences of Growing Up Poor, which Jeanne Brooks-Gunn and I edited, provided considerable support for the “what money can buy” pathway and also pointed to early childhood as a particularly sensitive period for impacts of economic deprivation on child well-being.

[Slide #10] To gauge the size of the income effects, let’s use a yardstick of a $3,000 increase in annual income, which is well within the scope of U.S. income support policies. After controlling for differences in an extensive set of parent characteristics, and for income in later childhood stages, Duncan, Brooks-Gunn and colleagues showed that for children living in low-income families, a $3,000 increase in annual income between birth and age 5 was associated with a highly significant eight-tenths of a year increase in completed schooling. In contrast, the estimated effects of increases in income during middle childhood and adolescence were smaller and not statistically significant.

Even eight-tenths of a year of additional completed schooling is important, since that effect size has been found to lead, on average, to tens of thousands of dollars in higher career earnings, less unemployment and better health.

These estimates by Duncan, Brooks-Gunn and colleagues used 20 years of data from the Panel Study of Income Dynamics project. Data collection on the children in this study has continued. Selecting children born into the study in its early years – 1968 to 1975 – we can now estimate associations between poverty as early as the prenatal year and a host of adult outcomes, measured as late as age 37.

[Slide #11] My collaboration with Ariel Kalil and Kathleen Ziol-Guest produced a 2010 paper in Child Development with estimates of these linkages. We found that for low-income children, a $3,000 annual increase in family income between the prenatal year and age five was associated with a 17% gain in earnings between ages 25 and 37. If sustained throughout an individual’s career, this would translate into nearly $200,000 in higher career earnings. As with completed schooling, income later in childhood and in adolescence appeared to be far less important than early income.

These links between poverty early in childhood and earnings three decades later are truly remarkable. Although many of you may find eventual labor market success to be a boring outcome for children, it provides obvious benefits for workers and their families. And for economists and policymakers it signals the worker productivity that fuels a nation’s prosperity.

Although curiously undervalued in developmental psychology, replication is a staple of most scientific disciplines. Working with a Norwegian colleague, Kjetil Telle, Ariel, Kathleen and I attempted to replicate and extend our poverty results using administrative data gathered on the entire Norwegian population. If we take the same cohorts as in our U.S. analysis – children born between 1968 and 1975 – the Norwegian data registers provide us with an impressive 496,000 observations. [Slide #12] And if we estimate the identical models of adult earnings as a function of income in different childhood stages plus demographic controls, we again find the strongest associations for early income, although the sizes of the effects are a little less than half those found in the U.S. data.

The much larger Norwegian sample sizes lend us the statistical power to do something that we cannot do with the U.S. data – break down stage-specific income effects even more precisely. Moreover, we were also able to estimate income effects using the stronger method of observing sibling differences in earnings and stage-specific childhood income. We found that economic conditions in the very earliest years of life – the prenatal year and birth year – matter the most for later earnings.

What is behind these associations? Testing the “what money can buy” and “parental stress” pathways was not possible with either PSID or Norwegian data. But in the PSID we were able to expand the range of adult outcomes to look for clues regarding process. [Slide #13]  As we have already seen, increments to family income early in childhood have a statistically and substantively important association with earnings later in life.

Suppose we take the PSID and estimate an identical model of income effects but substitute for adult earnings two behavioral outcomes – arrests and out-of-wedlock childbearing. Income early in life is not a significant predictor of either of these outcomes, which suggests that the positive effect of early childhood income on adult earnings is unlikely to be operating through some kind of problem behavior pathway. 

Let’s keep expanding our list of adult outcomes. Early childhood income is strongly linked to adult work hours. Something about avoiding poverty in the early years of life is enabling children to sustain full-time working careers in adulthood.

With NIH funding, the PSID has added health questions in recent waves. Remarkably enough, our work has shown that income in the prenatal and birth years reduces the likelihood of obesity in adulthood.  And ongoing work appears to show reductions in adult hypertension and arthritis as well. Perhaps research on childhood poverty should be spending as much time thinking about pathways related to health as achievement and behavior.

Doing so would open up exciting new opportunities for interdisciplinary collaborations. They connect us to rich literatures spanning psychology, neuroscience and epidemiology which point to detrimental consequences of in utero and very early life stressors on cognitive, social, emotional and health outcomes. We have long known about the harm caused by in utero exposure to teratogens such as alcohol. But stressors ranging from earthquakes to partner violence have also been shown to affect the length of gestation and neonatal health. Gary Evans and his collaborators have highlighted associations between childhood poverty and allostatic load, a biological index of the cumulative wear and tear on the body, measured in the teenage years. Andrea Danese and others are showing links between child stressors, such as maltreatment, and dysregulation of the immune system.

These pathways challenge our well-worn model of poverty effects [Slide #14]. Instead of the “what money can buy” and “parenting stress” pathways linking childhood poverty to child and adolescent outcomes, we need more time and boxes [Slide #15]. Poverty effects may begin prenatally and extend well into adulthood. The body’s stress and immune systems become important pathways linking poverty with later outcomes. And the outcomes themselves don’t fit neatly into attainment and behavioral categories, but instead relate to an individual’s ability to sustain a healthy and productive adult life.

SRCD members are among the leaders in some of these emerging research areas, but their work has not been embraced by most developmental researchers and is largely unknown to the majority of economists and sociologists. The payoff to interdisciplinary collaborations using this expanded model of poverty effects could be quite high.

Not enough planets

For my second example of the virtues of interdisciplinarity, let me explore the outer reaches of Bronfenbrenner’s ecological model [Slide #16]. As we expand outward from the child, we see the family and peers, and then the community and mass media. Further out is the macrosystem [Click#1], with its political and cultural influences and…wait, there’s something else!…[Click#2]..there are the economic influences… [Click#3] and over there are the policy influences. They are so distant from the child in this child-centric model, that it is tempting to follow the lead of astronomers in dealing with Pluto and classify them as Kuiper Belt Objects rather than as worthy planets. But we do so at our peril.

Let’s think big about economics and child development. When sociologist Glen Elder delivered his SRCD presidential address fourteen years ago, he featured the connections between economic hardship and child development detailed in his landmark books Children of the Great Depression and Children of the Land. 

But an even larger, and more important, set of macroeconomic forces are at work. [Slide #17] As Claudia Goldin and Larry Katz document in their wonderful 2008 book The Race Between Education and Technology, technological change rewards the acquisition of skills from an evolving workforce. In the first three-quarters of the twentieth century – until about 1975 – technology improved the productivity and pay of both higher- and lower-skilled workers. Since then, these rewards have shifted and fueled a massive increase in inequality with large but little-noticed consequences for child development.

Let’s look at the changes in family income over the past half century and express all of our income amounts in today’s dollars. [Slide #18] In 1947, the income threshold separating the poorest 20% of families from everyone else was a little over $13,000. Between 1947 and 1977, the economic fortunes of poor families improved markedly, with incomes doubling to about $26,000. Between the mid-1970s and now, technological change has favored only the most educated, as can be seen in the painfully slow growth –to only $28,000 – in the incomes of low-income families.

What about the richest one-fifth of families? Between World War II and the late 1970s, their incomes doubled as well – from about $40,000 to $84,000. But in contrast to low-income families, the incomes of affluent families have continued to increase. Of course, really high-income families did even better. By choosing the top 20%, I am including 15 million American children and providing a broader population view of child well-being.

A key question for this audience is whether the powerful forces fueling inequality have affected the developmental fortunes of children. Sean Reardon examines this question using achievement test scores, which are one of the few developmental indicators that have been gathered consistently over the past 40 years [Slide #19]. To get our bearings, let’s look first at familiar trends in the black-white test score gap. This slide presents smoothed data from the National Assessment of Educational Progress – the NAEP. Among children born in the early 1950s, shortly before Brown vs. Board of Education, black children scored one and a quarter standard deviations below white children when tested in the 9th grade. Over the next two decades, as the quality of schools attended by blacks improved, these gaps narrowed – by a remarkable half a standard deviation – but have changed little since then.

But now look at gaps defined by income, based in this case on various national achievement surveys. As with the race gaps, we have smoothed the line in order to focus on trends. The specific comparisons here are test score gaps between children at the 10th and 90th percentiles of the family income distribution.

Among children born around 1950, test scores of low-income children lagged behind those of their better-off peers by a little over half a standard deviation. For children born fifty years later, this gap was twice as large! This is hugely important. Fifty years ago, the race gap was much larger than the income gap. Now, the reverse is true. Not surprisingly, the income gap in completed schooling has grown as well. All told, this inequality story means that the “economic” planet in the solar system is looking more like Jupiter than Pluto.

Diversifying methods

Understanding how increasing inequality affects children’s attainment, and what might be done about it, could fill a book. In fact, it is about to [Slide #20]. Richard Murnane and I are editing a volume with Sean Reardon’s analysis, as well as the work of many others, describing the ways in which inequality works through the labor market, neighborhoods, families and schooling to affect children’s educational attainments.

I joined the book project midstream, after its structure of 24 chapters and 49 authors and co-authors had been determined. It is instructive to look at the disciplines of the 49 contributors.  They include numerous sociologists and economists, two neuroscientists, who help to explain the role of experience in the brain’s development, and several interdisciplinary scholars – but no mainline developmental psychologists. This is symptomatic of the fact that, with the important exception of experimental intervention studies, policy-focused studies of family, neighborhood, school, labor market and policy contexts published in developmental journals have little visibility outside of the developmental sciences.

In fact, apart from the interventions studies, there are very few developmental articles focused on the effects of policy. Policy implications abound. But they are inferred, often with leaps of logic, from analyses of the effects of conditions such as child care quality or parenting that might be affected by policy changes.

To be sure, developmental researchers have an enviable experimental tradition with intervention studies that are widely known throughout the social and behavioral sciences. And, as Aletha Huston observed in her 2007 SRCD presidential address, experimental studies of, for example, early childhood education programs are viewed as highly credible in Congress and other policy arenas.

But the scope and expense of random-assignment policy experiments limit their use. Lacking genuine experiments, how can we study policy effects? Economists and some sociologists and epidemiologists have developed sophisticated quasi-experimental approaches for this task. But here again, the absence of interdisciplinary collaboration with developmental psychologists means that these economic and sociological studies are quite unsophisticated with regard to developmental theory and measurement.

In my view, greater use of natural experiments holds the greatest promise for a new generation of policy-relevant development studies. Urie Bronfenbrenner and past SRCD president Sir Michael Rutter are among the advocates of natural experiments. They work by taking advantage of variation in key independent variables that are beyond the control of the family or child being analyzed. As illustrated by the use of dyzygotic and monozygotic twin births to estimate heritability, natural experiments have a long tradition in developmental research. But not for understanding the impacts of policy.

Let me give an example. The U.S. Earned Income Tax Credit provides income supplements to low-income working families that can amount to as much as $5,600 per year – a huge boost to the incomes of families supported by minimum wage jobs. Suppose that we are interested in understanding whether income from the EITC promotes child development, but lack the resources to mount a randomized trial. Since we believe that increased family income improves child outcomes, we would expect to find that children are better off with the EITC policy in place than they would otherwise be. And since we believe that the pathways to improved child well-being may involve reduced maternal stress, it would be valuable to be able to test for that as well.

What data and tools can be used to answer this question? [Slide # 21] Between 1993 and 1996, the generosity of the Earned Income Tax Credit increased sharply. For a single mother with two children who earned around $10,000, the credit was more than $2,000 higher in 1996 than in 1993. Moreover, and here’s the good part, the increase of $2,000 in the credit for families with two or more children was more than three times as large as the increase for families with just one child. So, if income matters for child and maternal outcomes, we should see a bigger improvement for children and mothers in two-child low SES families than in single-child low SES families.

Gordon Dahl and Lance Lochner used data on children’s test scores gathered before and after the jump in EITC benefits [Slide #22]. They estimated that benefit increases of $3,000 produced a one-fifth standard deviation increase in the test scores of children most likely to receive EITC benefits.

 How to test the maternal stress pathway? William Evans and Craig Garthwaite drew on data from the National Health Examination and Nutrition Survey gathered before and after the time of the EITC expansions. Remarkably, they found that low-SES mothers with two or more children, when compared with mothers with just one child, experienced larger reductions in risky biomarkers such as diastolic blood pressure and C-reactive protein and self-reported better mental health.

The statistics behind these studies are quite simple. They require no fancy multi-level, latent-growth or structural-equation modeling -- only a few interaction terms to isolate the key policy variation across groups and time [Slide #23]. No doubt many of you would disagree, but I would suggest that natural experiments and other tools for sharpening causal inference are at least as important in our empirical work as tools for psychometric or multi-level modeling. Perhaps we can agree that hybrid vigor is likely to result from transdisciplinary fertilization of both concepts and methods.

The case for breadth [Slide #24]

Let us step back and ask the biggest question: How can we best accelerate discoveries in the field of child development? As with any discipline, the field of child development progresses by both deepening and broadening its conceptual and empirical endeavors. The rewards to depth are impressive, and in no way do I want to minimize their importance.

As shown by the examples I have presented, however, there is a clear case to be made for breadth – for combining insights from very different disciplines and methods in new and creative ways. I am most familiar with the promise of interdisciplinary links between developmental psychology and other social sciences. Neuroscience is another obviously fertile field. Silvia Bunge writes of the synergies in the field of cognitive neuroscience. In her view, although cognitive neuroscience “is deemed overly reductionistic by psychologists and overly superficial by cellular and systems neuroscientists…its intermediate position lends itself to integrative research that spans several levels of analysis.” Indeed, she goes on to argue, “cognitive neuroscience is the right level at which to begin to understand how cognitive developmental trajectories are influenced by such important factors as…hormonal changes during puberty…and socioeconomic and cultural contexts.”

One of my favorite science writers is Matt Ridley. His 2010 book The Rational Optimist, tackles the daunting task of explaining the exponential progress of the world’s living standards. [Slide #25]. For all but the last two centuries of the last two thousand years, the average income of the world’s population hovered around $500 per person per year. But, around 1800, economic well-being began to grow exponentially, and it continues to do so today. Why the change? For Ridley, the answer to this monumental question lies more in breadth than depth.

As illustrated by Henry Ford’s assembly lines, depth in the form of division of labor played an important role in this progress. But more and more specialization surely cannot account for the exponential growth we have enjoyed in the last two centuries. Ridley instead points to a very different mechanism, as he puts it: [Slide #26] “ideas having sex with other ideas…The history of the modern world is a history of ideas meeting, mixing, mating and mutating...[S]o long as it can hop from country to country and from industry to industry, discovery is a fast-breeder chain reaction; innovation is a feedback loop; invention is a self-fulfilling prophecy.”

As illustrated by Arnold Sameroff’s SRCD presidential address in Denver and, I hope, my own, mixing, mating and mutating can also characterize our approaches to understanding the process of child development. Developmental science has much to contribute and to learn. 

Broadening the study of child development

Progress in the science of child development must come from depth and breadth. There is little need to worry about depth – the gravitational forces within our traditional social and behavioral disciplines and proposal review panels are robust and likely to stay that way.

How to promote cooperative play among the disciplines so that they combine ideas to yield new and exciting ways of understanding development and behavior? Learning about the key ideas and methods of other disciplines is a costly investment and the rewards are highly uncertain. It’s not for everyone, and that’s fine.

But how to encourage more of it? One way is interdisciplinary research networks. I have already mentioned that my own interdisciplinary journey began with a research network on the urban underclass. NICHD’s Network on Child and Family Well-Being enabled Jeanne Brooks-Gunn and me to launch our program of poverty research. The MacArthur Foundation has the longest history of supporting various social and behavioral research networks. Here I was fortunate to serve on three of its networks. Jacque Eccles’s Network on middle childhood provided the opportunity for Tom Weisner, Aletha Huston and me to integrate disciplines and methods in the New Hope work support intervention.

The National Institutes of Health provide grants for program projects – clusters of conventional proposals tied together by a common theme. A stated purpose of NICHD program projects is to encourage multidisciplinary approaches to the investigation of complex problems. NIH-funded population study centers such as Northwestern’s Cells to Society center promote interdisciplinary research among developmental psychologists and more traditional population-related disciplines. And some large data collection projects, such as Fragile Families and even the experimental Moving to Opportunity evaluation, engage researchers in cooperative play.

Schools and departments can also take steps to promote interdisciplinarity. Are graduate students best served by working within one lab throughout their graduate school careers, or by breadth-promoting rotation among labs? Shouldn’t we encourage them to take elective courses well outside their particular areas of interest? I believe that graduate students benefit most if they understand how psychologists think about development, neuroscientists think about the brain, economists think about policy and methods, anthropologists think about culture.

Given the narrow, disciplinary standards for awarding tenure, the years immediately following the attainment of tenure probably provide the most freedom for broadening one’s research agenda. Master lectures at professional meetings, seminars in other departments, professional meetings and journals focused on complementary research areas, books by good science writers and service on interdisciplinary review panels or research committees all provide opportunities for learning about ideas that might mix, mutate or mate with your areas of expertise. In the end, though, there is no good substitute for a wholehearted interdisciplinary research collaboration.

What about SRCD itself? A key goal in SRCD’s strategic plan is to promote interdisciplinary research. I am happy to report that the organization has taken a number of steps to achieve this goal. For the past three years, SRCD has funded proposals for workshops and conferences to promote interdisciplinary and other goals in our strategic plan. And as I hope you have heard, we are starting a set of themed meetings in the years between our biennial meetings [Slide #27]. The first three will be in 2012. A competition led to the selection of three topics, one focusing on developmental methodology, the second on positive development among minority children and the third on emerging adulthood. Please consider joining us, as you also begin to think about proposing your own themed meeting for 2014.

[Slide #28] I cannot begin to tell you how much I have learned and how much I’ve enjoyed my interdisciplinary forays into the tribal territories of developmental psychology. These adventures take a lot of hard work and involve more than their share of false starts and other frustrations. But they offer exciting possibilities for genuine breakthroughs in developmental science - in other words: for creation through recombination. Let’s get to it.