Wednesday, September 1, 2021

FOR IMMEDIATE RELEASE: September 1, 2021
CONTACT: Jen McAndrew
jennifer.mcandrew@tufts.edu | 617.627.2029

Tufts University students will soon have more opportunities to explore the complex relationships between faith and civic life in a religiously diverse world, thanks to a grant from the Arthur Vining Davis Foundations (AVDF). Building on its undergraduate Civic Studies major, the only one of its kind, Tufts University will launch a new interdisciplinary curriculum track in interfaith civic studies.  This two-year project represents an innovative collaboration between the Jonathan M. Tisch College of Civic Life, Tufts’ School of Arts & Sciences Department of Religion, and the Tufts University Chaplaincy.

The AVDF grant will catalyze the development of a 6-course sequence in interfaith civic studies at Tufts, provide opportunities for faculty professional development and course design, support a cadre of new “student interfaith ambassadors,” and support a Resident Fellow to facilitate interdisciplinary, interfaith discussions at Tufts.

Peter Levine, Tisch College Associate Dean of Academic Affairs and Lincoln Filene Professor of Citizenship & Public Affairs, who is the lead principal investigator, notes, “Religious traditions, identities, institutions, and conflicts are central to civic life. This generous grant will allow Tufts to develop new insights about the relationships between faith and civic life and to educate students to be effective and ethical contributors in a religiously diverse world.”

Co-principal investigator Brian Hatcher, former Chair of the Department of Religion, adds, “The Department of Religion is excited to join with the Tufts Chaplaincy and Tisch College to develop this new initiative to promote Interfaith Studies at Tufts and Beyond. Thanks to the generous support of the Arthur Vining Davis Foundations, we hope to explore new avenues for integrating the academic study of religion with lived, practical approaches for promoting awareness, knowledge, and engagement among faith communities. Our aim is to help prepare students to address the challenges of interfaith collaboration and religious contestation and to find ways to foster reflection on the role of religion in civic life.”

University Chaplain and co-principal investigator Elyse Nelson Winger is committed to centering student voices in all phases of the initiative. She says, “I am thrilled that our students and University Chaplaincy team are a vital part of this new initiative.  Through experiential learning, community-building, and co-curricular programming, the Interfaith Ambassador Program will equip students from different religious, spiritual, and philosophical backgrounds to ‘live the questions’ most pertinent to interfaith engagement.” 

Jennifer Howe Peace, Senior Researcher at Tisch College and co-founder of the Interreligious/Interfaith Studies Program Unit at the American Academy of Religions, will work with colleagues across departments to design an introduction to interfaith civic studies course and coordinate the grant.  Peace comments, “Young people are eager to creatively tackle the dilemmas and opportunities of living in religiously diverse societies. This grant gives us an opportunity to harness the expertise already at Tufts to educate a new generation of civically-minded leaders with a nuanced understanding of interfaith relations.”

I have been offline because we’d been enjoying a lovely vacation in Amsterdam. While there, I read James C. Kennedy’s A Concise History of the Netherlands. His argument has general implications.

It’s an argument about why the Netherlands has been so successful–even an “enviable” country. Before addressing that question, we should acknowledge, as Kennedy does, that the Dutch participated actively and influentially in European imperialism, including the transatlantic slave trade. So their story is not entirely admirable–perhaps not mainly so. It is nevertheless an interesting question why the Dutch have frequently been more tolerant, free, equitable, and prosperous at home than their neighbors have been.

It’s common to claim that a long tradition of commercial acumen and mercantile values made the Dutch tolerant. They have been too busy to hate. But this is not really an explanation. For one thing, why were they often so good at commerce? Besides, are we sure that the causal arrow points from commercial interests to tolerance? Couldn’t a tolerant culture be good for business?

Kennedy offers a different explanation. He notes that it has typically been impossible for anyone to dominate the Low Countries. In the middle ages, the region was divided into many counties that fell within different duchies and kingdoms. It also developed many prosperous towns, which were profitable for their various feudal lords but hard to control. Later, the Reformation added several religious sects (Calvinists, Mennonites, Moravians, Anabaptists, Jews, and others, plus the many Catholics). The land has always been carved up by water, creating quite disparate regions. And after industrialization, the society split into multiple “pillars” (traditionalist Calvinist, Catholic, socialist), each with its own parties, schools, unions, and press–none strong enough to dominate the rest.

Yet the Netherlands has frequently faced grave threats: the French, the Hapsburgs, the English, and–always–the ocean. Thus the Dutch have been forced to coordinate or perish. Seeking a central authority to lead them, they broadly backed Philip the Good, the Duke of Burgundy, to acquire titles to their whole region. But Philip had to negotiate with the cities to rule, and his descendants, the Habsburg emperors, faced a successful revolt. Later, the Orangist faction favored rule by the House of Orange as a means to centralize, but they always faced effective opposition. Voluntary association has been more common.

What were the odds that the Dutch would survive as an independent country? Things looked bad in 1421, 1672, 1795, 1940, 1953. It is risky to generalize from one case that turned out successfully. Maybe other people did the same things but failed.

However, it looks as if voluntary coordination has been a learned skill in the Netherlands. The Dutch already founded an extraordinary array of philanthropic and municipal associations, guilds, almshouses, beguine-houses, etc., during late medieval times, to which they subsequently added the world’s first true corporation, a complex republican confederal government, councils of church elders and synods, and many other innovations in self-governance. In this context, tolerance can be seen as a mode of relating to other people when you need their cooperation but you cannot dominate them. Tolerance results from polycentricism. It comes with skills of self-governance and an ability to invent new mechanisms for cooperation.

See also: polycentricity: the case for a (very) mixed economy; the UK in a polycentric Europe; modus vivendi theory; how a mixed economy shapes our mentalities; what sustains free speech?; China teaches the value of political pluralism etc.

Science is at the heart of several of our hardest issues, including COVID-19 and global warming. (And even race and policing.) While some Americans display “Science is real” yard signs on their front lawns, Dr. Fauci is the face of oppression for others.

The question of science is not simple.

On one hand …

What individuals think about matters like vaccination and climate change has consequences for everyone else. It can be hard to coexist with people whose beliefs seem fundamentally, even willfully, false.

Some findings are well-substantiated, e.g., that vaccines work and that human beings are causing the climate to heat up dangerously.

For any given question, there are better and worse methods of inquiry. If you want to know whether a vaccine works, a randomized, double-blind, controlled experiment is an excellent method. Google-searching to see what various “influencers” say … is not.

Science is a process of inquiry, not a set of truths. When scientific consensus shifts, that is a sign of learning, not an embarrassment.

The process of learning about COVID-19 has been extraordinarily fast and impressive. It is harder to assess the pace of learning about climate change, but we have learned how to learn a lot better than our ancestors could have done three or four centuries ago.

On the other hand …

No one obtains complex knowledge directly or alone. Science is a collective enterprise, deeply dependent on interpersonal trust. Even if you are an epidemiologist or a virologist, you can’t directly observe truths about COVID-19. You must trust data, instruments, protocols, metrics, and theoretical models that come from other people. For instance, you can only know what you’re seeing through an electron microscope because you trust that device and all the previous science that yielded it.

Science is a set of human institutions that confer power and status on some, while excluding others. Anyone with a doctorate has received a graduate education that cost someone hundreds of thousands of dollars. Americans rank physicians highest in status (7.6) out of hundreds of jobs. Physics professors and college presidents come next. Environmental scientists also rank high (6.5). But many Americans are in no position to obtain these jobs, and many may not want them. By the way, just 5 percent of physicians are Black, and 0.3 percent are Native American.

It is all very well to say “Trust the experts.” But the experts in foreign and defense policy bear responsibility for two disastrous wars since 2001. Experts in urban policy wrecked our cities’ cores by slicing highways through them and forcing people into segregated public housing. Medical experts described homosexuality as a pathology in the DSM until 1973. Some influential nutrition experts insisted that fats were bad and sugar was safe while being financed by the sugar industry.

People like me have deep personal reasons to give scientific institutions the benefit of the doubt. One of these institutions literally pays my comfortable salary. My parents, spouse, sibling, and children have been admitted, supported, and (in many cases) paid by universities. I live in a neighborhood dominated by people who have benefitted from the same institutions; it has good public schools, safe streets, and high property values. Many other people could not get into any of these institutions, or don’t want to get into them, or would not feel comfortable in them, or would not be valued by them. Trusting science comes naturally to me but has no natural appeal for many other human beings.

Partisan and ideological heuristics affect all of us. I find it very comfortable to decry Ron DeSantis’ handling of COVID-19 and to blame him for Florida’s current wave. That fits with what I want to think about Republicans, conservatives, etc. It is a lot less comfortable for me to consider why the highest cumulative per capita COVID rates are in New Jersey, New York, and Massachusetts, while Florida ranks 26th and has (to date) just 62% the cumulative case rate of New Jersey. I don’t think the takeaway is that liberal policies have worsened COVID-19. (For one thing, Mississippi is close behind Massachusetts, and Vermont and Hawaii have done best of all.) But it is no more valid to infer that conservative policies are to blame.

As the last point suggests, there is much that we really do not understand, such as the reasons for the variation in COVID-19 outcomes by state or nation. If we knew the answer to that, it might help us to assess overall social systems. We are deeply divided about what kind of society we should live in, and science has not answered that question. It is not as useful as it could be for public debates, yet it should never provide the solutions, since we must reason about values as well as facts.

There is no such thing as value-neutral data. People always decide what to observe and measure and what to call the results. When I search Google Scholar for “school social distancing COVID,” I see the following keywords in the top results: school closure, workplace non-attendance, school lockdown, mental health, weight gain, nonessential workers, nonessential businesses, epidemic control, and mitigation strategies. Whether these are the most important topics, what is missing (race, for instance), and whether these factors are rightly named–these are value questions, not scientific ones. Besides, in many cases, the data come from mandatory reports, and what we require people to report is a value-judgment.

Finally, the methods that work best for evaluating the effects of a mass-produced chemical compounds, such as vaccines, may not work best for assessing many social, cultural, and moral issues. In many domains, positivist methods are too influential and not enough credibility is accorded to laypeople’s knowledge.

I agree with Jonathan Badger that the most prominent critics of science are not raising subtle points about the soft despotism of scientific institutions or the tension between expertise and democracy. Instead, they are making false statements with great certainty. That is a disgrace, but it doesn’t negate real questions about the role of science.

See also methods for engaged research; we should be debating the big social and political paradigms; what is Civic Science?; “Just teach the facts”; notes on the social role of science; etc.

Amy Cabrera Rasmussen, Valeria Sinclair-Chapman, and I co-direct the American Political Science Association’s Institute for Civically Engaged Research (ICER). The 2021 Institute took place online, and Political Science Now has published an article about it.

The first cohort assembled in 2019, and members of that group have since edited a symposium on civically engaged research for PS. Some of the symposium articles are starting to appear in “first look” format and will be published together soon. The preface to the symposium is online and open access: Rasmussen, A., Levine, P., Lieberman, R., Sinclair-Chapman, V., & Smith, R. (2021). Preface. PS: Political Science & Politics, 1-4.

Please watch PS for more ambitious articles from the symposium. They review definitions of civically engaged research, critically analyze various motivations for undertaking it, connect engaged research to teaching, and so on.

See also: how to keep political science in touch with politics; methods for engaged research; what must we believe?; civically engaged research in political science; etc.

There is much writing–from a variety of ideological perspectives–about a new elite that is said to dominate culture, politics, and the economy. This group obviously bears a resemblance to previous elites (and disproportionately descends from parents who were wealthy and powerful), but perhaps it demonstrates some new features.

Among the novel characteristics could be: high education and technical skills (as opposed to deriving wealth from physical property), a meritocratic ideology, competitiveness and addiction to work, a tendency to cluster together in specific neighborhoods of selected cities and to marry only people of the same group, and a tilt toward center-left parties, which are said to be losing their working-class base in reaction to the dominance of meritocratic elites.

For instance, David Brooks writes:

The class structure of Western society has gotten scrambled over the past few decades. It used to be straightforward: You had the rich, who joined country clubs and voted Republican; the working class, who toiled in the factories and voted Democratic; and, in between, the mass suburban middle class. … But somehow when the class conflict came, in 2015 and 2016, it didn’t look anything like that. Suddenly, conservative parties across the West—the former champions of the landed aristocracy—portrayed themselves as the warriors for the working class. And left-wing parties—once vehicles for proletarian revolt—were attacked as captives of the super-educated urban elite. These days, your education level and political values are as important in defining your class status as your income is.

I found this story perfectly plausible but wanted to examine it empirically. Therefore, I explored it using data from the General Social Survey (GSS). In brief, I do not see evidence that today’s elite have different ideological or partisan leanings from their predecessors nearly fifty years ago, nor have they diverged from non-elites in terms of work hours, religion, or geographical mobility. They are more educated and more racially diverse than elites were in the 1970s, but overall, they look very much like their predecessors. That means that we are not experiencing a scrambling or a situation that has “suddenly” developed. Rather, critiques of a liberal-leaning, highly educated elite have been pretty consistent since the days of Richard Nixon, Spiro Agnew, George Wallace, and Pat Buchanan.

Method: The GSS categorizes jobs by prestige, based on a survey of representative Americans. In 2012, respondents rated a street corner drug dealer and a panhandler lowest (at 1.9 and 2.1, respectively) and a college or university president and a physics professor highest (at 7.1 and 7.2). [Correction: physicians are highest, at 7.6] A lawyer was rated 6.4; a mechanical engineer, 6.6; and a board member of a large company, 6.8 (Smith & Son 2014).

I isolated people who either held jobs in the top tenth of the prestige scale or else were married to people in the top tenth. Although it matters whether one is the worker or the spouse, I was interested in high-status households and wanted to include partners, especially in the 1970s.

I could have defined the “elite” in different ways. Trying various definitions would be valuable. However, it is important not to select on the dependent variable. In this case, one could define the elite as people who are liberal, live in major metro areas, hold advanced degrees, and meet other criteria assumed by commentators like Brooks. But then the conclusion would be foreordained. With equal validity, one could identify survey respondents who are conservative, religious, and powerful and tell a story about them. To avoid this form of bias, I pre-selected a definition of “elite” and then examined this group empirically. To be honest, I was surprised by how little change I observed.

Here are some comparisons and contrasts between the most-prestigious households in the 1970s and the 2010s.

Education: Today’s elite (as defined above) is more educated. Seventy-two percent hold at least a bachelor’s degree, up from 58% in the 1970s. Less than one percent don’t have a high school diploma, down from 6% in the 1970s. The non-elite also have more education than they did in the 1970s; however, just 24% hold a bachelor’s degree or more.

At the same time, a graduate degree certainly does not guarantee admission to the elite. Sixty-four percent of people with graduate degrees are not in the top tenth by occupational prestige.

Demographics: The elite was 93% white in 1970, six points whiter than the non-elite at the time. Both groups are now more diverse, but the change has been faster among the elite (who started at a very white baseline). In the 2010s, 80% of the elite was white, 8% was African America, and 12% belonged to other racial groups.

Party and ideology: Elites have not moved toward the Democrats. Including independents who lean toward either party, the elite has gone from 47% Democrat and 39% Republican in the 1970s to 47% Democrat and 37% Republican in the 2010s. They already leaned Democratic in the days of Richard Nixon, and still do by an almost identical margin.

However, non-elites are considerably less Democratic, down from 56% to 45% between the 1970s and 2010s, with most of that change happening during the 1980s. This trend may reflect Southern realignment more than ideology. The graph below shows ideological trends for elites and non-elites. It is true that elites have become somewhat more liberal since 2000, but the changes are small. Overall, elites were more liberal than non-elites in the 1970s and still are today. (To be sure, what it means to be “liberal” has changed, but this is still a reason to doubt a story of ideological realignment.)

Work-week: The elite worked a mean of 41.5 hours in a typical week in the 2010s– essentially the same as the 41.2 hours their predecessors had worked in the 1970s. The non-elite are down about two hours/week to 37.4 hours.

Geography: The elite have not diverged from the non-elite in geographic mobility. Both groups have become about 3-4 percentage points less likely to live in the same city where they lived when they were 16 years old. In each decade, the elites have lived in places with larger average populations than the non-elites, but community size has shrunk for both groups–presumably, as a result of movement to the suburbs and exurbs.

Marriage: Most non-elite adults (72%) were married in the 1970s. That proportion fell to just over half (54%) by the 2010s. Most of this large shift was to the “never married” category. Elites were less likely than non-elites to be married in the 1970s, and even less so in the late 1900s, dropping to 35% married by the 1990s. However, the marriage rates among the elite has risen to 46% in the 2010s, approaching the rate of the non-elites. A consistent one in four elites reports never being married in each decade.

Religion: In each decade, elites have attended religious services a bit more often than non-elites (on average), but religious attendance has fallen for both groups.

Sources: General Social Survey; Tom W. Smith & Jaesok Son, “Measuring Occupational Prestige on the 2012 General Social Survey,” NORC at the University of Chicago GSS Methodological Report No. 122, 2014. See also: why the white working class must organize; the Left between Obama and Hillary Clinton.

One way to think about the power of any legislature is the decisions it can make–for instance, to raise or lower taxes or to ban or legalize various things. Its power is almost always limited by other institutions, such as an executive or courts. And its power is finite, which means that the distribution of power within the body is zero-sum. If one party bloc makes a decision, the other parties do not. If the speaker, prime minister, or legislative leader gains influence, the rank-and-file loses power. If the committees are powerful, the whole body is weaker.

Given this model, it is puzzling why power sometimes centralizes within a legislature (as it has in the Massachusetts State House). Since each member has an equal vote, why would most members vote for leaders and rules that empower the leaders as opposed to the rank-and-file?

Perhaps the members of a large body face a classic coordination problem: they don’t really like the distribution of power but cannot organize themselves to challenge it. Perhaps they would rather have a strong leader than be walked over by the executive branch. Perhaps the party leadership obtains loyalty by influencing election outcomes. Or perhaps the average member is simply content without a lot of influence. There could be a vicious cycle, in which the kind of person who wants to influence legislation gets frustrated and leaves, and the remainder vote to empower the leadership.

The other way to think about this issue is in terms of capacity rather than power. A legislature does many things. It collects input from stakeholders, investigates the other branches of government and public problems, considers policy proposals, assimilates research, develops proposals, builds consensus within and beyond the body, amends and refines bills, and (finally) makes decisions by voting.

It can do more or less of this. At a minimum, it may barely scrape by, passing the laws that are constitutionally required, such as a budget (or may even fail to accomplish that). At the maximum, it can operate like the US Congress in 1965, which wrote, refined, and passed landmark bills to create Medicare and Medicaid (plus the NEH and NEA), enfranchise people of color, involve the federal government in K-12 and higher education, and open the US to mass immigration. Whether you like those laws or not, they represented much more lawmaking than usual. In fact, the year 1965 perhaps saw more federal lawmaking than has occurred during my entire lifetime, and I was born in 1967.

Power (in the sense of the first paragraph) is zero-sum. But capacity is not. Just because one group of legislators is working away on school reform does not mean that a different committee can’t be holding hearings on taxes.

Total legislative capacity can be expanded. That requires attracting talented and dedicated legislators. It may require a favorable climate beyond the legislature. It also requires nuts-and-bolts support. For example, legislators have more capacity if they have more staff, both in their own offices and shared by the body. In the Massachusetts legislature, the typical House member has one employee, which is not enough to do much legislative business.

Less capacity in the legislature can mean more power for the other branches, particularly the executive. That is a finding of Bolton & Thrower, “Legislative Capacity and Executive Unilateralism,” American Journal of Political Science, 60(3), (2016), pp. 649-663. However, it is also possible for an entire government to lose capacity.

Newt Gingrich cut congressional staff in Washington, especially the staff of the nonpartisan legislative-branch bureaus, which employ fewer than one third as many people as they did before 1990. This made sense for what he wanted to accomplish. If total capacity is smaller, it is easier for the leadership to control the body. (In that way, zero-sum power is related to capacity.) Besides, Gingrich’s legislative agenda was very simple–tax cuts, above all–and it didn’t require nearly as much capacity as center-left legislation would. Still, the result was a national legislature that cannot do much legislating of any kind.

There is an interesting wrinkle in the two graphs below, taken from Bolton & Thrower 2016. Congress was at its most active and ambitious while its staffing was rapidly rising, but not yet at its peak. The peak lagged a decade or so behind. That fits my general impression that the modern welfare state proved challenging to manage and sometimes overburdened our institutions–meaning all three branches of the federal government, states and localities, interest groups, and the press. After Congress enacted the major elements of the Great Society, it turned to managing those programs and gave that task serious attention for about fifteen years. Then conservatives tried to cut the programs (consistent with their principles and their mandate) but also cut the capacity to manage them without actually abolishing them. The result has been successively worse implementation.

Today’s Select Committee on the Modernization of Congress recognizes the problem. They call for increasing the capacity of Congress, “increas[ing] the funds allocated to each Member office for staff,” raising staff pay, and hiring “bipartisan [committee[ staff approved by both the Chair and Ranking Member to promote strong institutional knowledge [and] evidence-based policy making.”

This is an important agenda, and we need similar changes in Massachusetts.

See also: an agenda for political reform in Massachusetts; a different explanation of dispiriting political news coverage and debate; civic renewal in a state legislature; etc.

How long people expect to live could be important for at least two reasons.

First, individuals may know information about their own circumstances that affect their predictions. Maybe they know that they are sick or in frequent danger from gun violence. In that case, their prediction of their own life-expectancy might be a proxy for their social circumstances.

Second, their prediction may change some of their own cost/benefit calculations. There is, for example, no economic or other extrinsic reason to pursue education if you fear that your life is nearly over. Then again, you might procrastinate on getting more education if you think you have a very long time left to live.

Therefore I am interested in who makes optimistic or pessimistic estimates of their own life-expectancies. Of course, younger people will expect to live for more years, on average, than older people, and that doesn’t reflect optimism. So I adjusted for age by looking at the difference between how long people expect to live and how long the Social Security Administration (SSA) predicts that someone of their age and gender will live. If people give a higher number than the SSA, they are optimistic; a lower number reflects pessimism. Pessimism may be entirely warranted and reasonable, but it could still have negative effects on some important behaviors.

The scatterplot shows that individuals’ predictions correlate with what the SSA would say, but there is a lot of variation. One young dude expects to live for another 110 years, whereas the SSA would give him 58 years. Several people expect to die very soon. What accounts for these differences?

Using the Tufts equity research survey, I looked first at the factors that are incorporated in prominent actuarial models–the things that we’re told actually lengthen or shorten our lives. If you go to a “longevity calculator” like this one, it will ask you to enter your own year of birth, gender, race, education level, body mass index, income, whether you are retired, and your habits of exercise, smoking, and drinking alcohol. It will tell you how many years you probably have left to live, based on your answers and a significant body of research.

Some of those factors affect optimism, but some do not. Reporting results from a regression model that are significant at p<.05:

• Younger people are more optimistic, meaning not that they expect to live more years than older people but that their predictions for their lives are higher in comparison to the SSA’s predictions for them.
• White people are more optimistic than people of color, and they have a basis for that.
• Higher body mass index (BMI) correlates with pessimism.
• Regular vigorous exercise predicts more optimism.
• Education, gender, marital status, income, employment status, and drinking and smoking are not related to optimism, even though they are significant predictors of life expectancy in actuarial models.

I also went looking for measures that might predict optimism even though they are not in the actuarial models that I see online. Some of them are quite significant. When added to a regression model with the variables listed above …

• Frequency of attending religious services predicts optimism.
• People with better overall health (per their self-report) are much more optimistic.
• Stress about climate change comes close to predicting pessimism (p=.054).
• Whether you own a gun and whether you planned to vote for Trump or Biden are not related to optimism.

To some extent, people seem to be making accurate predictions based on life circumstances. For instance, they are right to worry about high BMIs. They seem to be missing some important factors, such as smoking and drinking. The correlation with religious participation could reflect the beneficial results of participating in communities, or perhaps religion makes one optimistic about one’s own life, or perhaps people who think they have a long time to live are motivated to attend services.

See also: how predictable is the rest of your life?; the aspiration curve from youth to old age