The following chart may be the most interesting for those outside of Washington, DC.

The START Report does note that the Discovery Channel incident might be the first ever environmental issue related suicide attack in its records.  The report correctly notes that militant environmentalists and animal rights attacks have been to date property crimes.

The recent Supreme Court decision allowing corporations to freely spend money in political campaigns can generate considerable backlash among consumers and the public. While corporations have political interests, the hypersensitive political atmosphere can create unintended issue linkages. Companies that are consumer facing, need to be cautious.

Issues are created when there is a conflict of expectations. Target has strategically developed a hip, cosmopolitan brand, and a progressive work environment, including partner benefits. There $100,000 contribution to a probusiness/low tax lobby is not in itself surprising. But when the lobby funded a Republican gubernatorial candidate who was anti-gay marriage, the issue emerged quickly. Target will need to spend quite a bit more than $100,000 to stop the bleeding.

I would like to note that Target has managed the issue well. The personal note to employees and the public acknowledging the issue and apologizing was appropriate and well done.
 

BORN POOR? HALF OF THESE BABIES WILL SPEND MOST OF THEIR CHILDHOODS IN POVERTY; SIGNIFICANTLY MORE LIKELY TO BE POOR 30 YEARS LATER

WASHINGTON, D.C., June 30, 2010 — Already off to a tough start in life, 49 percent of American babies born into poor families will be poor for at least half their childhoods, a new Urban Institute study finds. Among children who are not poor at birth, only 4 percent will be “persistently” poor as children.

Fallout from persistent childhood poverty is evident during young adulthood, say Caroline Ratcliffe and Signe-Mary McKernan, the authors of  “Childhood Poverty Persistence: Facts and Consequences,” the first study connecting poverty status at birth, poverty persistence, and adult outcomes. Those poor at birth are more likely to be poor between ages 25 and 30, drop out of high school, have a teen nonmarital birth, and have patchy employment records than those not poor at birth.

For instance, while 4 percent of individuals in nonpoor families at birth go on to spend at least half their early adult years in poverty, the share jumps to 21 percent for individuals born poor. The difference for blacks is 24 percentage points; for whites, it is almost zero.

In general, the longer a child is poor, the worse his or her adult outcomes. Only 1 percent of never-poor children spend half their early adult years living in poverty, compared with 32 percent of persistently poor children. The likelihood that an individual drops out of high school, has a teen nonmarital birth, or has a spotty work record generally increases with the number of years poor as a child.

An estimated 14.1 million Americans under age 18 are poor. Approximately 4.2 million children are born annually.

“Because poverty status at birth is linked to worse adult outcomes, targeting resources to children born into poverty and their families would help particularly vulnerable people,” Ratcliffe and McKernan observe. They say education, training, and work supports (such as child care subsidies) for parents could brighten children’s prospects by providing needy families with economic security and stability. Other supports for parents, such as home-visiting programs, could help children by improving family functioning and the home environment.

Other Findings

• 13 percent of all children (40 percent of black children and 8 percent of white children) are born poor.
• 37 percent of children live in poverty for at least a year before reaching age 18.
• 10 percent of children spend at least half their childhood years (9 years or longer) in poverty.
• Black children are 9 times more likely than white children to be poor for at least three-quarters of their childhoods — 18 percent versus 2 percent.
• 69 percent of black children and 31 percent of white children who are poor at birth stay poor for least half their childhoods.

Childhood poverty rates, according to the U.S. Census Bureau, have ranged between 15 and 23 percent over the past four decades. In 2009, a family with two adults and two children was considered poor if its income was below $21,756.

About the Study

Ratcliffe and McKernan’s research on the circumstances of children from birth through age 30 uses 1968–2005 data from the University of Michigan’s Panel Study of Income Dynamics. The PSID sample includes people born between 1967 and 1974.

“Childhood Poverty Persistence: Facts and Consequences” is the latest publication from the Urban Institute’s Low-Income Working Families project, which is supported by The Annie E.

Casey Foundation and The John D. and Catherine T. MacArthur Foundation.

# # #

The Urban Institute is a nonprofit, nonpartisan policy research and educational organization that examines the social, economic, and governance challenges facing the nation. It provides information, analyses, and perspectives to public and private decisionmakers to help them address these problems and strives to deepen citizens’ understanding of the issues and trade-offs that policymakers face.

Here are the top lines from Monday’s article:

Here is the link to the website that contains great graphics and plenty of specific data: http://projects.washingtonpost.com/top-secret-america/articles/a-hidden-world-growing-beyond-control/

I would like to make a few comments on the article:

1. This will be a finalist for the Pulitzer
2. Most folks following The Community, including this writer, have know about the mess for several years. The piece is timely and should lead to Congressional action.
3. There are folks who are criticizing the Post for releasing the Report and the detailed data. What is a national security risk is the mess within the community. Flashing light on the community is not a substantial risk.
4. I believe that the Intel Community can not reform itself – too much vested interests. We need a Special Congressionally Mandated Commission to pull together a strategic plan for The Community.
5. As I have pointed out in the past, along with other strategic forecasters and futurists, despite all of the money, organizations, and agencies, there is no lead organization for providing long range forecasts or scenarios for the country’s decision makers.
6. There is way too much secrecy and compartmentalization in our government. As part of a review of  The Community, the government needs to refine and cut back the classification system. Much of what The Community creates should be public so that the public knows what it is buying.

Long-range forecasters and futurists have similar interests to The Community. We are both trying to find information that is actionable. We are both trying to anticipate the future in order to prepare for opportunities and risks. Our work cuts across culture, society, economics, politics, science, and technology. We often use similar tools. An open and accessible Intelligence Enterprise will enhance the nation’s security and would be an invaluable resource for its citizenry.

Thanks to the Foundation Center for bring the Report and Summary to my attention.

Although conventional wisdom suggests that the annual net job gain at existing companies is positive, the fact is that net job growth in the U.S. economy occurs only through start-up firms, a new report from the Ewing Marion Kauffman Foundation finds.

Based on the U.S. Census Bureau‘s business dynamics statistics, the report, The Importance of Startups in Job Creation and Job Destruction (12 pages, PDF), found that both on average and for all but seven years between 1977 and 2005, existing firms were net job destroyers, losing a combined one million jobs per year. In contrast, during their first year new firms added an average of three million jobs. The report also found that while job growth patterns at both start-ups and existing firms were pro-cyclical, there was much more variance in job growth patterns at existing firms. Indeed, during recessionary years job creation at start-ups remained relatively stable, while net job losses at existing firms were highly sensitive to the business cycle.

And it’s not just in net job creation that start-ups dominate. Although older firms lose more jobs than they create, the gross flows decline as firms age. On average, one-year-old firms create nearly one million jobs, while ten-year-old firms generate only 300,000. In other words, the notion that firms bulk up as they age is not supported by data.

Because start-ups that develop organically are the principal driver of job growth in the economy, job-creation policies aimed at luring larger, established employers inevitably will fail, said the report’s author, Tim Kane. Such city and state policies are doomed not only because they are zero-sum but because they are based on unrealistic employment growth models, added Kane.

“These findings imply that America should be thinking differently about the standard employment policy paradigm,” said Robert E. Litan, Kauffman Foundation vice president of research and policy. “Policy makers tend to focus on changes in the national or state unemployment rate, or on layoffs by existing companies. But the data from this report suggest that growth would be best boosted by supporting start-up firms.”

“Job Growth in U.S. Driven Entirely by Startups, According to Kauffman Foundation Study.” Ewing Marion Kauffman Foundation Press Release 7/07/10.

Primary Subject: Public Affairs
Location(s): National

FC015074

Public Sees a Future Full of Promise and Peril

Life in 2050: Amazing Science, Familiar Threats

INNOVATION

Re-Thinking Innovation

A New Agenda for Academic Investigation

Before the revolutionary upheavals of the late 18^th century, political leaders did not always look kindly upon innovation. It implied a break with tradition, the introduction of newness into political and religious affairs, and was thus often viewed with mistrust. Such times, of course, are long past. Today’s political leaders actively seek innovation—albeit a narrower form of newness in technologicalinnovation—as the basis for fostering jobs, prosperity, and economic growth.

The study of innovation has often happened at two disconnected units of analysis. Economists, sociologists, and political scientists have generally seen innovation from a high altitude where it is removed from the small-scale processes that, for instance, move discoveries from the lab bench into the marketplace. These scholarly models hold that academic research has over time become more interdisciplinary, problem-oriented, and entrepreneurial. As John Ziman argued in his 2000 book Real Science, research after 1960 became a “wealth-creating technoscientific motor for the whole economy.”

But national R&D policy has always been heavily goal-oriented. New models (see sidebar at right) for knowledge-making better reflect the experiences of university-based scientists and engineers than those in the corporate world that employs most graduates. At the scholarly spectrum’s other end, historians who study innovation have produced detailed case studies that provide different perspectives than the broad models of innovation by looking at specific events, institutions, or individuals. Yet it is difficult to extrapolate a broader picture from these well-researched “trees” in order to understand how the whole “forest” works.

What is often lacking is a middle ground that makes extrapolation possible—the tools and analyses that can help connect specific empirical studies to more comprehensive models of innovation and technological change. Bridging this gap would complement recent innovation policiesthat aim to support regional technological innovation as a key link between specific locales and the “national system.” Understanding innovation is crucial as the U.S. government moves to renew its investment in the innovation infrastructure. This is especially important as Congressional wrangling last week delayed reauthorization of the America COMPETES Act, which would supply $86 billion for scientific research, innovation, and education.

Recently, Christopher J. Newfield, a researcher with the National Science Foundation-supported Center for Nanotechnology in Society organized a workshop in Lyon, France. Catalyzed by the tenth anniversary of the U.S. National Nanotechnology Initiative, the workshop brought together academics and policymakers from several countries to re-think how a decade’s worth of research on the social implications of nanotechnology might inform broader innovation policy and perhaps inform understanding of how innovation works. Attendees presented several new perspectives on innovation that spanned levels of analysis ranging from specific case studies to general theories of innovation and policy formulation.

The common message was that finding this middle ground is possible, but first we need to re-evaluate what we mean by innovation, how we understand it, and, perhaps, to consider some heretical thoughts about questioning it as a universal good and panacea. Let’s now consider each of these observations in turn.

The value of innovation

First, the heresy. Rarely does anyone question the value of innovation. But is it always beneficial? Good intentions aside, innovation as a historical force doesn’t always create jobs. It sometimes destroys them, as Amy Sue Bix argued in her book Inventing Ourselves Out of Jobs. Automation and innovation, from the 1920s through the 1950s, displaced tens of thousands of workers—think of the conflict between Spencer Tracy (a proponent of automation) and Katherine Hepburn (an anxious reference librarian) in the 1957 film Desk Set.

But what of broader societal benefits innovation brings? A recent book by Stanley Joel Reiser, Technological Medicine: The Changing World of Doctors and Patients, suggests that, at least in the world of healthcare, innovation is not always an unalloyed good. In his study of several medical innovations, Reiser concludes that it produces winners and losers—and the winners are not always the patients. Sometimes, instead, they are hospital administrators, physicians, or Big Pharma.

As Reiser argues in the case of some medical technologies, technology for its own sake can lead to unexpected outcomes and moral dilemmas. An especially compelling example he gives is the invention of the artificial respirator: while saving countless lives, this medical innovation also created ethical, legal, and policy debates over, literally, questions of life and death. Moreover, there is the broader ethical question of whether it is better to spend large amounts of money for medical technologies and treatments that will benefit future generations if this means less funding to address current medical needs.

At the CNS workshop in Lyon, economist Shyama Ramaniraised similar issues with regard to how countries such as India were attempting to imitate U.S. nanotech policies. Her conclusion was that monies currently being spent for future nanotech innovation would be better spent on alleviating current environmental problems such as water remediation and agricultural productivity. The innovation needs of developing countries and emerging markets are not likely to map onto the priorities of countries such as the United States.

In other words, as Ramani argued, India’s proclivity to model its science, innovation, and intellectual property policies on those in countries like the United States—so as to compete in fields such as nanotechnology and biotechnology—may ultimately hinder India’s ability to serve the real needs of its people. Ramani also suggested that India not produce nanotech for the global market but rather for a global “technological commons,” which is more focused on the specific needs of emerging markets.

What is a “national innovation system”?

But these country-level priorities raise the question of a “national innovation system” making these sorts of decisions. Does such an entity exist—can it? Perhaps, as Berkeley economist David Mowery quipped, a “national innovation system” is a fiction like the Holy Roman Empire: not national, not about innovation, and not a system. This witticism is worth unpacking because it illuminates the components of innovation that we don’t fully understand.

First of all, are there really national innovation systems? Or is this a convenient way for academic and policymakers to parse something larger? Historians who have long studied the flow of technologies across borders and between nations would question that such a creature has rarely, if ever, existed. Andrew Jon Rotter makes this case, albeit with an extreme example, in Hiroshima: The World’s Bomb. Here we find that there are no national nuclear weapons programs—they have always been international in nature. The Manhattan Project, after all, was a multi-national undertaking by American scientists and engineers who were joined by their British and Canadian counterparts and dozens of high-profile refugee scientists from Germany, Italy, and Hungary. No nuclear weapons program then or since has been “home grown.”

The same could be said for “national” space programs, which also depend on much common engineering knowledge, and today’s “national” nanotech programs, which also build on shared engineering and scientific knowledge. The upshot: All innovation stems from a “transnational” network of knowledge circulation. A state that invests in R&D must, of course, have the capability to draw from this pool, but there is no guarantee that it will do that in ways that lead to economic growth and jobs. Simply put, too much focus on the “national” suggests a closed system that is ahistorical.

What happens if we de-center the nation from the narrative and think about innovation as a fully transnational phenomenon? This challenges the persistent inclination to frame innovation just a matter of national economic competitiveness. This would also entail reconsidering the metrics we use to evaluate success or failure in the innovation arena (patents, publications, numbers of engineers produced) by including ones that are more “purpose-driven.”

To use the case of nanotechnology, for example, the societal goals of investing in the NNI included more environmentally sustainable energy technologies and better healthcare technologies. How are we doing? The President’s Council of Advisors on Science and Technology recently completed its third review of the initiative. Beyond the traditional metrics cited above, PCAST concluded more attention was still needed to the “commercial deployment” of nanotech products and praised the idea of new “Signature Initiatives” to encourage application-specific R&D.

Innovation, however, means more than just bringing new products or market. If we are to think in terms of innovation systems, then this systemic view must be more wide-ranging. This means taking a view toward innovation that encompasses more than the traditional idea of introducing new “things” into the global marketplace. MIT economist Eric von Hippel notes that throughout history the use and re-use of existing technologies has been a powerful driver for innovation as well as the more traditional notion of supplier innovation. Von Hippel’s attention to the user complements British historian of science and technology David Edgerton’s argument that an over-commitment to “techno-nationalist” viewpoints obscures the reality of how innovation occurs.

Finally, in the United States, there is hardly an “innovation system” if one means a coherent set of policies, processes, and institutions working in concert. As historians know, metaphors and analogy have power to shape and frame debates and policy. Rather than thinking of an innovation system, with its flowcharts, performance metrics, and feedbacks, a more useful metaphor is that of an ecosystem. Complex and dynamic, ecosystems encompass the local, the regional, the national, and the global.

Such a metaphor also encourages us to think about the role played by niche and interstitial actors. For instance, in the 1980s and 1990s, futurists and visionaries played a powerful role in stimulating support for nanotechnology among the public and policymakers by generating ideas about what the field could be. In addition to the more familiar institutional actors, other components of the system that require additional consideration include visionary thinkers, long-term and sort-term goals, marketing, design, investors, entrepreneurs, popularizers, and skeptics.

Innovation in practice, scholarship, and policy

The power to shape the levers of innovation through such creative work is not new. Historically, artistic endeavor, broadly construed, has been a powerful driver of technological innovation. Advances in metalworking and ceramics traditionally originated in the workshops of artisans who produced objects valued more for their aesthetic quality than purely utilitarian ones. The feedback is powerful—in Renaissance Venice, improvements in glassmaking stimulated the production of more capable scientific instruments that played central roles in the Scientific Revolution.

At the CNS workshop, Roger Malina, a physicist and long-time editor of the art-and-technology journal Leonardo, proposed an idea for stimulating more of this creative “micro-innovation.” Similar in concept to micro-credit, a project would set aside small amounts of money to encourage innovation from unlikely quarters. Malina gave several examples of inexpensive products from the art-technology nexus that have produced interesting innovations such as smart textiles that change color in the presence of elevated CO₂ levels. The idea of micro-innovation complements the use of prizes to foster larger-scale technological innovation, as White House science policy advisor Tom Kalil has written about.

Initiatives that would fund and cultivate new models like Malina’s “micro-innovation” are the province of policymakers, but they present a challenge to academics who study innovation: they must question the basic models of innovation. For decades, the predominant model was linear. Based on Science: The Endless Frontier, Vannevar Bush’s 1945 social contract for science, the linear model posited that investments in basic science research would produce new technologies and societal benefits—meaning innovation. Rhetorically powerful as well as easy to understand and explain to policymakers, deployment of the linear model ignores the historical contingency of Bush’s report, which has, for better or worse, been the touchstone for much U.S. R&D policy.

Bush, director of the Office of Scientific Research and Development during World War II, was an anti-New Dealer who sought to justify continued federal investment in science. Along with Harvard President James Conant, Bush was also eager to deflect criticism of the scientists who had produced weapons of mass destruction, namely the atomic bomb.

And since 1945, scientists and policymakers have pointed to a select group of basic science discoveries that led to specific innovations—solid state physics research led to the transistor and the laser, the discovery of giant magneto-resistance led to the iPod. But what if these are extreme examples that don’t reflect the everyday nature of innovation?

This might be just an academic question, but given the heavy investment in research as a tool for economic recovery, the validity of the model itself needs scrutiny. The linear model holds that investment equals societal benefits, but Bush’s actual report said little specific about jobs.

In 1925, the English mathematician and philosopher Alfred North Whitehead wrote that the “greatest invention of the nineteenth century was the invention of the method of invention.” Innovation today, as in the past, demands much more than just invention. What the 21^st century needs is a better understanding not just of the method of innovation, but its goals, its transnational flows, its systemic nature, and the processes through which the “new” can become accepted, productive, responsive, and responsible.

W. Patrick McCray is a professor in the Department of History at the University of California, Santa Barbara and a researcher and former co-director of the Center for Nanotechnology in Society at UCSB. He is also a member of the Science Progress advisory board. This article is based upon research supported by the National Science Foundation under Grant No. SES 0531184. Any opinions, findings, and conclusions or recommendations are those of the author and do not necessarily reflect the views of the National Science Foundation.