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The Voice of Faculty Doing Research – The Provost Podcast Series

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In talking with alumni and even some of our current students, I’ve detected a weakness in the Georgetown community culture. While most are fully aware of the performance of our faculty in the classroom and during office hours, they have little knowledge about the research or scholarship lives of our faculty.

At the extreme, some alumni assert that they don’t see the value of faculty doing any other task than teaching and mentoring students. From one perspective, such reactions seem quite understandable among those encountering faculty primarily in classroom. For many undergraduate alumni, their memories of faculty are dominated by interactions surrounding formal courses.

In contrast, faculty deeply understand that their research lives are important necessary ingredients to providing students the most up-to-date learning environments. Most faculty are deeply motivated to push the frontiers of their field. Their scholarship is an essential feature of their identity. They are ongoing students of their area of expertise. They are members of a global community of scholars who study similar phenomena.

Some students do report that they can perceive when faculty are describing areas in which they are actively doing research. They report that the instructors’ eyes widen, their voices become more animated, and they express a sense of excitement that is infectious. Not all classes, however, allow faculty to reveal these passionate interests to all students.

Because of this mismatch between what students see of faculty in the classroom and what faculty do in their research lives, there seems to be an opportunity for the provost office to help communicate to students and alumni more about the research lives of faculty.

Toward that end, the provost office has built a podcast series, labeled “Faculty in Research.” Each episode of the podcast is a short conversation (15-20 minutes) about why the interviewed faculty member finds his/her research area fascinating. It reviews how they choose projects to pursue. It describes how their interests change over time.

If you’re interested in learning about the inner research lives of our faculty colleagues, you can access the podcast here. Subscribing to soundcloud.com will facilitate your keeping up with new episodes of the podcast.

The first podcast welcomes Professor Deborah Tannen as guest; she reviews her work in sociolinguistics.

Let me know how you like the podcast.

Announcing the Provost Innovation in Teaching Awards

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Last August I posted an announcement that described an attempt to fill a void in recognition of exemplary performance among our faculty colleagues. It noted that while Georgetown has multiple awards for classroom teaching performance, we were not recognizing the amazing examples of innovating in pedagogy that are occurring around campus.

The awards could serve two purposes. First, we could thank those who have created and refined such innovations. Second, we could describe and highlight their innovations for other faculty encouraging similar innovations in their own work.

Well, given the great work of Vice Provost Bass and a set of faculty reviewers, I am absolutely overjoyed to note that we have completed the nominations and review process of the first annual awards.

As the nomination process evolved, some new insights emerged. It became clear that the invention of different types of awards had merit. Some of the nominations identified a group of faculty who worked together to redesign multiple courses or program curricula. They worked as an integrated team to achieve the innovation. Other nominations described the work of an individual faculty member, inventing new ways to enrich the learning in their own classes. Finally, especially in this first year, the reviewers recognized that some nominees merited recognition for consistent innovation over many years – in some sense, a career achievement of innovation.

The second change over the year was that generous donors, hearing about Georgetown’s desire to reward innovation, wanted to help us do so. We can now announce the Bill and Karen Sonneborn Innovation Fund, which permits us to offer monetary awards connected to the Provost Innovation in Teaching Awards. We will hold an event in September 2019 where the awardees will make presentations on their work in a celebration of teaching and innovation.

The awardees, in the three categories, are the following:

The Program Category Award: The Disability Studies Program

The Disability Studies Program has become a model of at least three innovations: 1) interdisciplinary coordination across the boundaries of the entire University that connects course, events, faculty and students; 2) cross-curricular coordination that links courses through “clusters” and shared assignments, projects and end of semester events that links students and student work; 3) making use of pedagogical techniques inspired by principles of universal design for learning.

Each semester, the Disability Studies (DS) program’s “cluster” approach creates a community of learning and practice by bringing together courses from fields as varied as biology, literary and cultural studies, bioethics, nursing, healthcare administration, women’s and gender studies, and anthropology around common readings and visits by scholars, performers, and advocates. The Program extends its interdisciplinary reach across GU’s campuses through new collaborations with the Med Center and The National Rehabilitation Hospital and into the community with a host of immersive learning opportunities, including internships and community-engaged experiences in conjunction with the Center for Social Justice.

Individual Category: James Freericks

Dr. Freericks’ specific innovation is how to translate complex physics classrooms from a conventional lecture format to an online format suitable for either a MOOC or a flipped classroom. Jim has been involved in both, producing GeorgetownX’s course Quantum Mechanics for Everyone, which was named a 2018 edX prize finalist, ranked ninth on Class Central’s top 50 MOOCs of all time, and was one of Class Central’s best MOOCs of 2017, and producing the flipped classroom experience for Physics 155, Mathematical and Computational Physics, for students on the hilltop.

The first project was undertaken to teach the complex subject of quantum mechanics to a wide group of students and brought part of the Georgetown course Physics 008, The Quantum World Around Us, from the classroom to the internet. The second was orchestrated to fit the specific need students have for more practice in learning the complex math required to major in Physics. Flipping the class moved the lectures outside the classroom, which is now filled with problem-solving sessions and demonstrations that actively engage the students.

Career Achievement Category: Elizabeth Hervey Stephen

Dr. Stephen is being recognized not because of one innovation, but rather for the arc of innovation over her 31-year career at Georgetown. Dr. Stephen’s innovations all center on developing a Community of Scholars. In one extended innovation, Dr. Stephen experimented with keeping her first-year proseminar students together as a cohort across four years. Assembling the four years of work starting with the students’ papers as freshmen up through the senior year, Dr. Stephen was able to analyze the inflection points at which their writing and thinking improved.

She was able to apply her knowledge studying student progress from the proseminar forward by serving as the first-ever coordinator of all 22 proseminars taught each fall in the SFS. As coordinator, she created a community of scholars among the faculty by developing shared proseminar learning goals, syllabus alignment, regular luncheons, and shared web-based resources for proseminar faculty.

Dr. Stephen’s other set of innovations include a series of experiments with online teaching that led her to teach one of the first on-line course during the academic year for undergraduates at Georgetown. She designed a course, “Border and Security Concerns,” with three interconnected sections: one section on the main campus, one section at Georgetown’s Villa Le Balze in Fiesole, Italy, and one section at GU-Q. Her reasoning was that the topic of Borders transcended campuses and that by combining the three sets of students into discussion groups that they would learn from one another.

Please join me in congratulating our colleagues on their achievements!

Infusing Ethics into Computer Science Education

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Georgetown (through the leadership of Professors Nitin Vaidya and Maggie Little) were awarded an important innovation grant from the Mozilla Foundation.  It will permit the collaboration of EthicsLab in the Kennedy Institute of Ethics and various computer science courses.

I’ve written earlier about the promise that Georgetown has in building a bridge between technology and larger societal issues . This new grant is another signal that Georgetown is recognized as having unique institutional strengths in this domain.

What’s it all about? The amplification of every thought and word that is possible through the netting together of billions of people on internet platforms has no historical precedent. The instantaneous nature of the amplification exceeds the speed of all prior ages of human interaction. Unfortunately, the good intentions of a garage startup are difficult to maintain when billions of persons are affected by its activities.

Institutions touching myriad parts of societies throughout the world encounter unique challenges. We have already seen both deeply harmful effects and wondrous benefits of new technologies. Looking forward, it seems appropriate to rewrite Dickens a bit to note it can be the best of times; it can be the worst of times. Attention to the societal impact of new technology, guided by explicit values, is required for “the best of times.”

There has been much discussion of the slowness of regulatory behavior to ameliorate some of the harmful emergent behaviors on the internet. However, even before one begins to conceptualize rules and regulations, societies need norms (unwritten standards of behavior) to guide the rulemaking.

Some of the capabilities of internet platforms are so unprecedented that even norms cannot keep up with the changes. My behavior can affect the fate of others in ways for which no norms have been articulated. Rumors that were shared in private in side conversations can now be instantly known by all. Many can trace the location of others minute by minute. “Private” behaviors are routinely public.

Further, empirical analytic techniques can use vast volumes of data to predict events and outcomes of processes second by second. Machine learning algorithms can control devices and vehicles sufficiently well that human intervention is less frequently needed. Completely autonomous processes are imagined.

But all such algorithmic approaches require data to build the predictive models. Such data must be collected before it can be used. What data to collect? Deep understanding of the processes is required to collect data to build good algorithms. Common examples of failure from using flawed data abound. Arrest data-based algorithms for where police should be deployed exacerbates any racial or socioeconomic bias in police behavior. Using mortgage default geo-data to build decision algorithms for loan applications suffers the same biases that produced the geographical spread of defaults in the original design. Biased data sets to train algorithms produce biased algorithms. Data use without explicit values can bring on “the worst of times.”

So, circling back to the good news about an innovation grant to Georgetown – as we educate the next generation of leaders in technology, Georgetown must confront the central questions of how to use technology for good. New ethical puzzles confront us right now. Others will confront us with each new development.

Society is now facing the effects of too much technology developed without attention to the ethical implications of its uses. With its decades of contributions to applied ethics and its growing bench of talent in computer science, Georgetown can lead in designing technical curricula that raise questions of values and norms at the point of development.

Appreciation of Uncertainty Grows with Deeper Knowledge

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“Although this may seem a paradox, all exact science is dominated by the idea of approximation. When a man tells you he knows the exact truth about anything, you are safe in inferring that he is an inexact man. … It is characteristic of those matters in which something is known with exceptional accuracy that, in them, every observer admits that he is likely to be wrong, and knows about how much wrong he is likely to be.”

The Scientific Outlook, Bertrand Russell, 1931, Norton, pp 63-64.

Except for the gendered pronouns, this 1930’s quote still rings true. But the limitation of the observation to science is probably not legitimate. For example, scholars in the humanities who are investigating the intended meaning of texts usually hold uncertainties about the currently favored interpretations. Indeed, deep understanding of any field generally entails knowledge of all the disputed truths, rejected theories, and partial replications of prior findings. This knowledge leavens one convictions.

In this regard, scholarly cultures are quite distinct from much of modern society. It would be unusual for an entrepreneur pitching a new idea to a set of venture capitalists to emphasize the unknowns in their startup’s plans. In place of that, the “fail fast” culture argues to react quickly to counter-evidence and morph the idea to adapt to the new knowledge. But the “fail fast, break things, disrupt” culture rewards certainty of action. As another example, today’s modern media presentations tend not to emphasize uncertainties. The talking heads on cable news speak with certainty on all their views. Their “opponent” talking head speaks opposite points with equal certainty. Rare is the politician who details the uncertainties surrounding any policy position. Indeed, the admission of ignorance about some facet of the topic at hand is not often seen in the public sphere.

In this regard, it is interesting to note the social psychological literature on persuasive conversations. A common finding is that speakers are judged more persuasive when, on their own, they introduce a counter argument to their own argument and then refute it. This is judged more influential in discerning what is true than speaker attempting to rebut the counterargument after another raises it first. This finding doesn’t seem to have penetrated public discourse. However, it is common in scholarly work to actively discuss the limitations of a study’s findings prior to reporting the findings themselves.

This mismatch between the larger society’s norms of persuasive behavior and that of scholars seems, however, in some situations to limit scholars’ influence. Decisions must be made. They must be made on the facts available at the time of the decision regardless of how inadequate they might be. Decisions under uncertainty are the most common to be made. Enumerating all the sources of uncertainty about current knowledge often doesn’t lead to effective decisions.

So much of these differences are a matter of style of dialogue. Wouldn’t be interesting if media moderators would ask their talking head guests what uncertainties they have about their opinions, what could happen that makes their predictions of the future wrong, what information would be required to change their minds?

And then on the scholarly side, despite all the attention that is given to the uncertainties in their findings, wouldn’t be interesting to force those well-versed in the uncertainties to make the decision based on the current state of knowledge?

Finally, how precious to all of us are the minds that can move back and forth between these two domains with equal facility!

Imprinting by Mentors

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I often have the privilege of talking with faculty about their research lives. In most of these conversations, some talk about their graduate student experiences. I’m struck at the important role that mentors play in the early career of many PhD’s.

Many faculty, looking back at the formative pre-PhD time, remember individual moments when the mentor taught them what level of rigor was required in their field. These are memories that were sometimes painful – returned drafts filled with markups, pointed critiques of flawed logic, directives to write more succinctly, or attacks on the superficiality of the work. They are also memories of deep pleasure, when the young student first earned the praise of the mentor, a moment when the mentor said that the student had accomplished something worthwhile.

Another common memory was how the mentor shaped the PhD student’s assessment of what was a good problem to pursue in their own research. A common guidance was, “If you were completely successful in the project, what would we know that we don’t know now?” Of special import is whether the target of the project had promise of generating several follow-up projects. “What are the different outcomes of this project? Can you imagine a follow-up project that would result from each of those outcomes?” This kind of guidance was viewed as key in helping the student conceptualize an integrated set of projects over time. For some faculty, these discussions defined several years of work.

Some faculty also point out the weakness of their mentor on this score: “My mentor gave me the problem for my dissertation.” In retrospect, such mentees had to teach themselves how to identify a good research question. Some remember feeling somewhat lost in the early years of their independent scholarship. Similar problems arise sometimes with mentors who co-publish with their mentees over many years. At the worst, these sometimes stifle the increasing ability of the young scholar to develop their own skills at discerning good research questions to pursue.

A few faculty remember their pre-doc days under the influence of two mentors, with possibly different perspectives on the research project of the student. They recall navigating between the two, sometimes attempting to blend together the two viewpoints. They remember sometimes awkward meetings of the three of them. They remember getting contradictory advice from the two. Some think that they own careers have blended the two perspectives together in some way.

Some of the relationships between a PhD mentor and mentee last for years. For some faculty looking back, they can remember a moment when their mentor began to treat them more as a colleague than a student. Mentees often develop expertise in new methods or techniques in the field. They then teach these new methods to their mentor. So, sometimes the teaching and guidance becomes mutual for the two. Gradually, the pair becomes more complementary of one another.

What is notable in these discussions is how impactful these mentoring experiences are to entire lifetimes of scholars. The imprinting of mentors on the lives of the mentee is deep and long-lasting.

The Three-Story Structure of Theory and Applications

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I’m told that one country’s government weather service is a three-story building. On the top floor are theoretical climatologists and meteorologists. They are striving to elaborate the theory that underlies human understanding of the earth’s weather systems and how they change over time. Their work is highly technical and at times has no stated purpose other than satisfying the curiosity of the scientist attempting to find answers to puzzling questions. As they do their work, they are searching for fundamentally new insights. The failure rate of the top floor is high, but the payoff of new developments can be transformative.

The second story of the building is populated by modelers of real weather components across the globe. They are attempting to use newly formulated theories to design new procedures for forecasting weather and modeling climate. They test their models on real data assembled over time, indirectly evaluating new theoretical developments. As they attempt to improve on current techniques, they are pushing the frontier of practice. Many times, they examine historical data as the evidentiary base on which to make their judgments. The success rate of the second floor generally exceeds that of the third floor, but its successes tend most often to be incremental improvements. When the second-floor researchers are successful, they tend to solve some weakness of the existing body of practice, through testing new practices against the old.

The ground floor is populated by weather forecasters, applied meteorologists, who provide the public, the government, and companies the daily prediction of temperature, precipitation, wind, humidity, and cloud coverage throughout the country. When they perform at their peak, they are implementing newly proven innovations from the second floor. To the general population, they are the face of the weather service. Hence, the staff on the first floor receive the vast majority of the appreciation for correct predictions and almost all criticisms for incorrect ones.

Thus, the three stories move from theory to application. One building. Vastly different enterprises. I’ve assumed the bottom floor was chosen to be application-oriented because it is the group with the greatest outreach to diverse publics. They respond to “walk-in” trade.

Of course, the value of the three floors depends on the use of the stairways linking them together. Is there movement across floors? Is the movement uni-directional? Are the theoreticians made aware of failures on the first floor? Are the first-floor forecasters aware of the assumptions in the newest model promoted by the second floor? Are there any people who work on multiple floors?

Finally, the variation in visibility of the three floors can affect a superficial evaluation of the product of the building. It’s easy for someone who knows nothing about climate and weather to assume that the first floor houses the most important group in the building. After all, that floor delivers the products and services of the entire building. If there are funding pressures, following that logic, the first floor must be privileged over the higher floors.

Such logic ignores the knowledge that the third floor is the origin of what the first floor accomplishes in future years. Emptying out the second and third floors is not unlike a struggling farm unit deciding to preserve only the harvesting equipment and stopping purchase of seeds. It might be cost efficient for one season, but then it’s out of business. Similarly, with each new introduction of devices and platforms from technologists, it’s tempting to view them as autonomously produced inventions. We can easily make the mistake by judging that only such visible innovation work is of importance. Yet many of those innovations depend on basic science developments years earlier.

Much of basic research and scholarship is academia’s third floor. While it’s easy to criticize a publication that is read by only 100’s of people, publications exactly like that can be identified as the seed of new ideas and new ways of thinking that transform the lives of large populations decades later. There is value in the constant pursuit of pushing the edges of human knowledge. Future populations will live at that edge.

We don’t do well with a one-story building.

Data, Information, Knowledge, Wisdom

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As we all try to make sense of the world day by day, we are increasingly reminded that we can learn something about almost every topic faster than ever before. But a few clicks on a keyboard generates more than we can consume fully.

It might be useful, however, to make some distinctions among “data,” “information,” “knowledge,” and something perhaps labeled “wisdom.” Data consist of documentation of individual attributes of people, households, businesses, organizations, events, images, texts, and transactions. Increasingly these come from streams of digital bits from internet-connected devices. Sometimes the data are quantitative; sometimes, words; sometimes, images or sounds; sometimes, even smells. The popular phrase, “data exhaust,” invokes the correct image because it implies a material residue of something that was real and often complex.

To people outside the processes, these data themselves often have no real meaning. Their first purpose is simple — to permit interactions to proceed in a manner that fulfills the designs of those in charge of the process. Each of us derives benefits from many of these processes; in the internet world, we pay for them generally by providing data on our behaviors that have value to those running such processes.

But the haphazard collection of our Alexa speech, tweets, credit card transactions, search terms, mobile phone GPS transmissions, facial images, and other exhaust can also, given a specific purpose, produce information. By “information” might mean an assembly of data with a purpose. Hence, different types of information can be assembled from the same collection of data. Our exhaust, when assembled into information, can answer many specific questions.

So, the distinction between data and information in this sense is the added value of connections among data. In some sense, subsetting and combining data invents information in the hands of one seeking an answer to a question.

Most academic fields are vast collections of information. There are millions of answers to individual questions that are themselves collections of data. The work of academic fields is both discovering new information, but also to reassemble pieces of information into novel coherent wholes. The development of new theory in individual fields seems often to depend on discovering some new information (sometimes merely a new assembly of old data) that reinterprets whole bodies of information. With such assemblies, the use of the term, “knowledge” becomes attractive. Knowledge might be viewed an interrelated network of different pieces of information.

(An interesting assembly of information that is of growing interest in the academy is the story or narrative. These are assemblies of information that often gain their memorability by evoking emotions through the careful selection of pieces of information. Any story manipulates related pieces of knowledge to emphasize purposeful themes.)

So, how does the notion of wisdom come into this cumulative collection of data? A cognitive psychologist friend thinks of wisdom as the result of networks of networks of knowledge. When we label a remark as a wise observation, we often express surprise by a new assembly of knowledge. In my friend’s view, this is evidence of an unusual connection between different knowledge nodes built from experience. A testament to that is the “I never thought of it that way” comment that we make to ourselves.

Many cultures associate wisdom with age. The wise elder may attain that status by networks of knowledge that only years of experience can provide. Seemingly unrelated knowledge domains are found to be related because of millions of life episodes experienced over time.

All of us are overwhelmed with data each day. The individual pieces, scattered about in our minds, are far distant from a state of wisdom. Using our life experiences to constantly probe new mixes of seemingly unrelated knowledge is our route to building networks of networks of knowledge that might be called wisdom. This is always intellectually courageous, but often fun.

Philosophy in the Financial Sector

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The eco-system of knowledge development in the modern university is a permanent fascination to me. A key feature of this eco-system is the mix of discovery versus application that occurs.

Some scholars within the academy are totally curiosity-driven. They find themselves interested in an issue and begin to use their discipline’s perspective to explore it. They are driven to seek an answer to the motivating question. Rarely are they interested in any day-to-day applications of their work.

Other research efforts seek a solution to a practical problem. The researchers are made aware of an unsolved problem and seek to apply knowledge to discover and test a solution to the problem. This is the movement from the lab to the clinic in a biomedical context. It is the move from a classroom experiment to a whole school curriculum reform. It is the move from the engineering lab to a real-world build-out.

There are some academics who move back and forth between curiosity driven scholarship and real-world applications. In my estimation, there are few who do both well.

Some of the current discussion about the humanities, the social sciences, and the natural sciences, on one hand, and the job market, on the other, gets conflated with issues of theory and application. The humanities often get labeled as purely curiosity-driven exercises. From that observation, some commentators then extrapolate that the humanities have no value in today’s job market.

In this regard, I read with interest a recent interview  of the investor Bill Miller, a man who achieved unusual success designing and running investment funds. Miller is an ABD in philosophy at Hopkins. The interview focused on how he reconciled his great success in financial markets with his humanistic studies.

He reported that “Philosophy steered me away from confirmation bias.  In any philosophical assessment, you’re trying to figure out the validity of an argument, working to pinpoint ways to make it stronger.  You’re not necessarily trying to win an argument, and you’re not taking an adversarial position.  You’re really trying to look at things from a wide variety of perspectives.”

A mind that approaches an unsettled issue with a pure disinterest in the final resolution is truly liberated to find new solutions. Miller believes that he acquired those cognitive skills in his philosophy courses. Those skills, in his belief, were key to choosing companies for his investments. One gets the impression that it was his ability to remove emotion from his assessments that was key to his taking different perspectives on the same investment possibility. The ability to attack the same set of facts from different perspectives permitted him to detect the potential value of a new investment opportunity in ways that a traditional approach would not.

Further, the skill in deep analysis of information, dissecting it, reassembling its components in different ways, led to his success. Miller claims the habits of mind that his philosophical study gave him provided superior tools in his investment management life.

He predicts that these skills will be some of the scarcest resources in the future. Young people, aspiring to leadership in the new world, should strive to acquire them.

What are the Civic Obligations to Provide Personal Data for Common Good Statistical Information?

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Some time ago, I mused about a notion of “data ethics,” in a set of posts that was focused most on the obligations data collectors and data analysts had to the persons who data they were handling. Most of principles that I discussed had to do with protection of the privacy of individuals whose data were being collected and assurances that no individual harm could come directly from their provision of personal data.

This post takes a different perspective on personal data. It ruminates on the question of what obligations do residents of a society have to provide data to produce statistical information for common good purposes.

Most countries of the world have some system of institutions that collect data from individuals, aggregate them to produce statistical summaries, in order to inform the populace about its own characteristics. These generally inform about the welfare of the national population and various subgroups. For example, they describe the income distribution of households, educational achievements across subgroups, labor force participation, incarceration rates, agricultural production levels, cost of living changes, and a host of different attributes.

These basic indicators collectively provide the nation with a sense of how it’s doing. They inform us how the benefits of the society are shared across different subgroups. By comparing the same indicators over time, the country can judge whether things are getting better or getting worse.

Indeed, such indicators are a foundational component of a democracy. They help the people judge whether the performance of elected officials merits the continuation of their service or whether the country needs new leadership.

In these days of data breeches, we are reminded nearly daily of misuse of personal data to harm individuals, profiteering from personal data without full consent of those who supplied the data, and numerous other events that heighten our concerns about personal privacy. One is tempted to react to these events by avoiding sharing any personal data with anyone, as a way to maximize one’s own privacy protections.

However, obviously, none of the statistical indicators that the democracy needs to guide decisions of residents would be available to the nation if individuals chose not to agree to supply their personal data for such statistical purposes.

So, in parallel with our discussions about protecting our own privacy, I’d like to see us all engage in a discussion about what civic obligations we have to contribute to common good statistical indicators. When asked by a government statistical agency to participate in a survey that produces such statistical indicators, for what reasons to people frame the request as an unwarranted intrusion into their private lives? In what way, can such requests be viewed as a chance for public service to the common good?

Scholarship and Storytelling

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Recently, Georgetown had the honor of hosting Ken Burns, the documentary filmmaker. He met with students, participated in discussions about educational activities among the incarcerated, and showed some of his film product.

Mr. Burns made one suspect a common tendency to overemphasize distinctions between academic scholarship and the kinds of documentary films he makes.

Regarding depth of archival research, Mr. Burns reviewed the making of several films that took over ten years of work, not unlike the length of time to produce a university press book. He cited the cataloging and digitization of hundreds of thousands of images (photographs, documents). He noted the aggregation of materials from multiple sites over many years. That feature of his work seemed very similar to what many academics do in the beginning stages of a research product.

Increasingly, modern academic scholarship involves interdisciplinary teams. His description of the close ties of his group and his respect for their diverse skills reminded me of interdisciplinary research teams describing their cross-functional strengths.

Regarding the rigor of review and rewrite, he cited the numerous iterations in the design and execution of the video product. He described the time and effort in the editing phase of a project, continuously squeezing the content to extract the most meaningful components of the overall message. It reminded me of precisely the same apparently-endless process of drafting any scholarly work, whether it be an article or a book.

Much of academic scholarship is devoted to assuring a balanced presentation of alternative arguments. Much scholarship clearly describes limitations on conclusions or presents conflicting perspectives. Mr. Burns repeatedly noted how he felt obliged to show both the good and bad of every character, even those for whom he had great sympathy. His goal was to make it difficult for a viewer to know how he felt about a character or an event.

Academic scholarship produces the raw material for teaching. Mr. Burns’ films produce the attention that all lecturers seek in the classrooms but few of us ever achieve. The awe that viewers feel in his films imprints permanent memories of their content.

Mr. Burns has another point of view quite consistent with that of many academics – true understanding takes time. The fleeting, mediated interactions of the modern world limit the likelihood of true insight into complex, elaborated, and interwoven pieces of knowledge. Indeed, at one point, he uttered a common refrain of a truly wise scholar – when you really understand a phenomenon, you have finally identified what the key questions really are, or when you really have deep knowledge of a field, you are focused more and more on what you don’t know. All of this takes time.

Finally, Mr. Burns knows deeply what many scholars are now just discovering. A very common discussion among the science and social science community these days is how the use of storytelling can motivate understanding of technical research findings. It is the stories that generate emotions, and the emotions that generate attention and memory. When stories generate the attention, more complicated facts can be communicated and remembered more effectively. On this, his mastery is unrivaled.

So, stepping back from the day, I find myself a little more puzzled about the perceived differences between academic research products and those products that share so many of attributes of academic work, but are designed for a broader audience. It seems to me that both sides are at least intellectual cousins, if not intellectual siblings. The goals are the same; the methods have more overlap than we sometimes may think.

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