Monthly Archives: October 2017

new research on “civic deserts”

(Washington, DC) My colleagues Kei Kawashima-Ginsberg and Felicia Sullivan coined the phrase “civic deserts” to name places where there are few or no opportunities to be active and constructive participants in civic life. The analogy is to “food deserts”–geographical communities where there is little or no nutritious food for sale. You can still be an active citizen in a civic desert, just as you can grow vegetables in your back yard; it’s just that the whole burden falls on you.

Today at the National Conference on Citizenship, we are releasing Civic Deserts: America’s Civic Health Challenge by Matthew N. Atwell, John Bridgeland, and me. It’s a 36-page report that documents the declining opportunities for civic engagement in America. John Bridgeland and Robert Putnam also write about it today in a PBS opinion piece.

This is an example of a table from the report:

Thanks to friends at USC’s Center for Economic and Social Research, we were able to ask a  large, representative sample of Americans whether they belonged to various kinds of groups; if so, whether they participated actively in any of them; and if so, whether they thought that the group’s leaders (a) usually did what they promised and (b) usually tried to serve and include all the members. It turns out that only 28% of adult Americans actively belong to groups whose leaders are accountable and inclusive. That statistic does not tell us how much geographical space is taken up by civic deserts, but it suggests that they are common. And the historical data implies that civic engagement used to be much more widespread.

I separately formed a hypothesis that lacking direct, personal experience with good leadership would make a person more tolerant of the leadership style of Donald J. Trump, controlling for one’s political ideology. In other words, given two people who agree with Trump on issues, the one without experience of good local leadership would be more supportive of Trump as a leader. This was testable with the USC data, which includes a whole battery of questions about ideology, issues, and Trump. My hypothesis turned out not to be true: partisanship and media choice seem to explain opinions of the current president almost completely, and experience in groups adds no explanatory power. Still, I think there may be a more circuitous story about civic deserts as a cause of Trump’s victory: the decline of civic associations increases the power of partisan heuristics and ideological media. Even if that hypothesis is also false, civic deserts are still a problem, because civic engagement benefits health, economic development, safety, education, and good government.

See also: The Hollowing Out of US Democracy (my blog post for USC); Mitigating the Negative Consequences of Living in Civic Deserts – What Digital Media Can (and have yet to) Do (a new CIRCLE article); America needs big ideas to heal our divides. Here are three by Bridgeland and Putnam; and the power of the NRA in an age of civic deserts.

Comparative Effectiveness Research for democracy?

In health, we’ve seen an influential and valuable shift to Comparative Effectiveness Research (CER): measuring which of the available drugs or other interventions works best for specific purposes, in specific circumstances. Why not do the same for democracy? Why not test which approaches to strengthening democracy work best?

My colleagues and I played a leading role in developing the “Six Promising Practices” for civic education. These are really pedagogies, such as discussing current, controversial issues in classrooms or encouraging youth-led voluntary groups in a schools. Since then, we have been recommending even more pedagogies, such as Action Civics, news media literacy, and school climate reform. I am often asked which of these practices or combinations of practices works best for various populations, in various contexts, for various outcomes. This question has not really been studied. There is no CER for civics.

Likewise, in 2005, John Gastil and I published The Deliberative Democracy Handbook. Each chapter describes a different model for deliberative forums or processes in communities. The processes vary in whether participants are randomly selected or not, whether they meet face-to-face or online, whether the discussions are small or large, etc. Again, I am asked which deliberative model works best for various populations, in various contexts, for various outcomes. There is some relevant research, but no large research enterprise devoted to finding out which deliberative formats work best.

Some other fields of democratic practice have benefitted from comparative research. In the 2000’s, The Pew Charitable Trusts funded a large body of randomized experiments to explore which methods of campaign outreach were most cost-effective for turning out young people to vote. Don Green (now at Columbia) was an intellectual force behind this work: one motivation for him was to make political science a more experimental discipline. CIRCLE was involved; we organized some of the studies and published this guide to disseminate the findings. Our goal was to increase the impact of youth on politics.

Our National Study of Learning, Voting, and Engagement (NLSVE) is a database of voting records for 9,784,931 students at 1,023 colleges and universities. With an “n” that large, it’s possible to model the outcome (voter turnout) as a function of a set of inputs and investigate which ones work best. That is a technique for estimating the results that would arise from a whole body of experiments. We also provide each participating campus with a customized report about its own students that can provide the data for the institution to conduct its own experiments.

So why do some fields of democratic practice prompt research into what works, and others don’t?

A major issue is practical. The experiments on voter turnout and our NSLVE college study have the advantage that the government already tallies the votes. Given a hard outcome that is already measured at the scale of millions, it’s possible to vary inputs and learn a great deal about what works.

To be sure, people and community contexts are heterogeneous, and voter outreach can vary in many respects at once (mode, messenger, message, purpose). Thus a large body of experiments was necessary to produce insights about turnout methods. However, we learned that grassroots mobilization is cost-effective, that the message usually matters less than the mode, and that interactive contacts are more efficient than one-way outreach. We believe that these findings influenced campaigns, including the Obama ’08 primary campaign, to invest more in youth outreach.

Similarly, colleges vary in their populations, settings, resources, missions, and structures, but NSLVE is yielding general lessons about what tends to work to engage students in politics.

Other kinds of outcomes may be harder to measure and yet can still be measured at scale. For example, whether kids know geometry is hard to measure–it can’t be captured by a single test question–but society invests in designing reliable geometry tests that yield an aggregate score for each child. So one could conduct Comparative Effectiveness Research on math education. The fact that mastering geometry is a subtler and more complex outcome than voting does not preclude this approach.

But it does take a social investment to collect lots of geometry test data. For years, I have served on the committee that designs the National Assessment of Education Progress (NAEP) in civics. NAEP scores are valuable measures of certain kinds of civic knowledge–and teaching civics is a democratic practice. But the NAEP civics assessment doesn’t receive enough funding from the federal government to have samples that are reliable at the state or local level, nor is it conducted annually. This is a case where the tool exists, but the investment would have to be much larger to permit really satisfactory CER. It is not self-evident that the best way to spend limited resources would be to collect sufficient data for this purpose.

Other kinds of outcomes–such as the quality of discourse in a community–may be even more expensive and difficult to measure at scale. You can conduct concrete experiments in which you randomly vary the inputs and then directly measure the outcomes by surveying the participants. But you can only vary one (or a few) factors at a time in a controlled experiment. That means that a large and expensive body of research is required to yield general findings about what works, in which contexts, for whom.

The good news is that studying which discrete, controllable factors affect outcomes is only one way to use research to improve practice. It is useful approach, but it is hardly sufficient, and sometimes it is not realistic. After all, outcomes are also deeply affected by:

  • The motivations, commitment, and incentives of the organizers and the participants;
  • How surrounding institutions and communities treat the intervention;
  • Human capital (who is involved and how well they are prepared);
  • Social capital (how the various participants relate to each other); and
  • Cultural norms, meanings, and expectations.

These factors are not as amenable to randomized studies or other forms of CER.  But they can be addressed. We can work to motivate, prepare, and connect people, to build support from outside, and to adjust norms. Research can help. It just isn’t research that resembles CER.

Democratic practices are not like pills that can be proven to work better than alternatives, mass produced, and then prescribed under specified conditions. Even in medicine, motivations and contexts matter, but those factors are even more important for human interactions. It’s worth trying to vary aspects of an intervention to see how such differences affect the results. I’m grateful to have been involved in ambitious projects of that nature. But whether to invest in CER is a judgment call that depends on practical issues like the availability of free data. Research on specific interventions is never sufficient, and sometimes it isn’t the best use of resources.

symposium on issues raised by Big Data

Wednesday, November 8th 2017, 9AM – 5PM
Breed Memorial Hall • 51 Winthrop Street • Medford, MA 02155

Keynote Presentations • Panel Discussions • Poster Sessions

As Tufts seeks to develop a University-wide, interdisciplinary center dedicat­ed to data-intensive research and pedagogy, studying the science of data and its uses in application domains that span the breadth of the university, we are happy to announce the upcoming Fall’s DISC symposium. We encour­age you to visit the DISC website for more information on the purpose and goals of this University-wide initiative.

For updates to the Program: Fall DISC Symposium
For RSVP Details: 
http://go.tufts.edu/RSVPforDISC
Contact me if you have a poster idea!

PROGRAM 

Welcome Remarks
Anthony Monaco, President at Tufts University

Session I: City and Urban Planning

AnnaLee Saxenian – Dean of the School of Information at UC Berkeley

Panel Discussion
Herbert Dreiseitl, Justin Hollander, David Mendonca, Adam Storeygard

Session II: Ethical Use of Data

David Lazer – Professor of Political Science and Computer and Information Science at Northeastern University & Co-director at NuLab

Panel Discussion
Chaitanya Baru, Matthias Scheutz, Nick Seaver

Lunch and Poster Session

Session III: Privacy and Security

Jeannette Wing – Avanessians Director of the Data Sciences Institute & Pro­fessor of Computer Science at Columbia University

Panel Discussion
Kathleen Fisher, Erin Kenneally, Alex “Sandy” Pentland

Session IV: Data Science and Computational Science in Healthcare

Henry Kautz – Founding  Director at Institute for Data Science & Professor of Computer Science at University of Rochester

Panel Discussion
Frank Alexander, Harry Selker, Jerry Sheehan, Harry Sleeper

Session V: Data Science and Computational Science in Biology

Peter Coveney – Professor of Computer Science & Director of the Centre for Computational Science and the Computational Life and Medical Sciences Net­work at University College London

Panel Discussion
Christoph Börgers, Diego Martinez, Grace Peng, Donna Slonim

Reception and Poster Session

what it means to view modernity as our basic condition

Let’s say that modernity has the following features, which tend to arise together fairly rapidly because they are causally linked. Their arrival is the process of modernization:

  1. Instead of using a small number of traditional tools to affect nature and other people, we begin investing substantial resources in a continuous process of inventing and improving tools.
  2. Traditional values–moral, spiritual, and aesthetic–are subject to doubt. One response is a fragile conservatism about the inherited values. Another is heroic creativity: making up new values. Another is imitation: self-consciously replicating values from the past or from other places. A fourth is nihilism: losing commitment to values in general.
  3. Instead of assuming that roles (responsibilities and powers) derive from individuals’ social status, which people typically inherit, we view roles as the result of contracts, which can be renegotiated.
  4. We become increasingly skillful at choosing efficient and effective means to a given end, but less confident about being able to choose good ends. Many people become relativists or subjectivists, assuming that ends are simply what individuals happen to want.
  5. In addition to relating directly to people whom we know, we have frequent and important interactions with strangers, often via abstract media such as money or written orders.
  6. People become increasingly fungible, not only in market systems but also in organizations of all kinds.
  7. Social roles constantly differentiate and specialize; and complex systems develop to train, evaluate, and coordinate specialists. Many of the specialists work on inventing or improving the systems for coordinating people like themselves.

I see modernization as momentous. That sometimes makes me dissent from widely-held opinions:

  1. I disagree that we are living in a time of especially rapid change, at least in the OECD countries. The really big shift occurred during modernization, which had happened in countries like the USA by 1910. Constant novelty still arises as a result of #1, #2 and #7 (above), but new tools and fashions are superficial developments compared to the wrenching shift from pre-modernity to modernity.
  2. I often disagree that capitalism is the underlying cause of social problems. For one thing, the same problems occur under state socialism. If “capitalism” meant free markets, it would be something quite different from socialism. But capitalism is mainly a system in which large organizations–firms and governmental agencies–employ and coordinate specialized workers. That is a feature of modernity, not specific to market systems.
  3. I have doubts about the term “postmodern.” Most of the moves made by postmodern thinkers were well known to Nietzsche and others in 1890. To be sure, the heroic, create-new-values strand of modernity was especially dominant ca. 1900-1960, and the skeptical, doubt-all-grand-narratives strand has been more prevalent since then; but both were available as soon as modernity arose.
  4. I am less impressed by cultural differences across space–but more struck by changes over time–than many people seem to be. I start with the assumption that life in France and in China ca. 1500 was pretty similar, as is life in Paris and Beijing today. The big difference is before and after modernity in each country.
  5. I interpret imperialism a bit differently from many people. I have no doubt that it has been exploitative, cruel, and traumatic. But I don’t see it as the imposition of “Western” culture on “non-Western” societies as much as a phenomenon of modernization. To be sure, it was much worse to be on the receiving end of colonialism and to have modernity thrust on you at gunpoint, rather than to profit as an agent of modernization. But the imperialist countries typically shed their traditional cultures by modernizing while they exerted power abroad. Today, people all over the world are just as authentically “modern” as Europeans are, and global modernity contrasts with European traditions as much as with other traditions.

Modernity is neither good nor bad; it is liberating and traumatic. It isn’t recent–we’ve had a century of it already. But it is a change compared to two centuries ago, and therefore older social theories don’t apply without serious modification.

See also: Dubai, Uganda, and today’s global political economy;  the rise of an expert class and its implications for democracyon modernity and the distinction between East and WestLifeworld and System: a primertwo cheers for the West; and postcolonial reaction

changes in how we talk about cities

At a meeting at a community organization in Boston, we were using various terms to describe local issues and observing that those phrases would not be clear to the people we were talking about–especially new immigrants. That made me wonder about the history of our vocabulary, so I used Google’s Ngram tool to see the frequency of “urban poverty,” “inner city,” “gentrification,” “deindustrialization,” and “urban redevelopment” in published books. This graph shows trends since 1900.


In rough order of when these phrases became popular…

  1. “Urban redevelopment” starts very soon after WWII but declines after 1970. It is a keyword of high-modernist urban planning from the era of big housing projects and highways blasted through downtowns.  It has been notably less popular (at least in books) since ca. 1980.
  2. “Urban poverty” rises in the 1960s and the 1990s, but has–interestingly–fallen in the 2000s.
  3. “Inner city” seems to have become rapidly popular during the Kennedy and Johnson administrations, plateaued at a high level until about 2000, and then fallen off.
  4. “Gentrification” enters the lexicon in 1975. It plateaus in the 1990s and then rises rapidly in our century.
  5. “Deindustrialization” is a new term ca. 1980, describing a phenomenon that started in the 1970s. It peaks in the 1990s.

These changes seem to reflect objective circumstances–cities lose their industrial base but then sometimes attract yuppies who push up housing values–as well as shifts in intellectual fashions, such as the rise, and then fall, of high-modernist design.