Creating Knowledge Together

Several years ago, I had the chance to tag along on a European tour with Missouri’s University Singers.  My friend, Paul Crabb, the choral director, talked with his students in the group about the pleasure of “making music together.”  The idea that they were “making” the music may seem odd at first considering that they were “merely” performing music that others had composed.  Of course, they truly created music in every performance (and even every rehearsal).  And it was a collaborative production of all the individual students and the director.  (Click here if you want to see one of my favorite songs they performed on the tour.)

Similarly, by contributing to the University of Missouri “Stone Soup” Case Database, students and faculty can have the pleasure of creating knowledge together.  Individually, students learn from interviews that they conduct about actual cases.  Collectively, classes can conduct related interviews that combine to create group knowledge about particular issues.  Students’ written case reports would result in tangible data that could be shared through the database.

Building Blocks of Knowledge

Individual Stone Soup case reports could be the building blocks of larger bodies of knowledge.  In addition to conducting class discussions about different interviews, faculty could write summaries of interviews with citations and links to individual case reports.  At the most basic level, these could be summaries of a single class’s interviews with some theoretical analysis.  At the next higher level, faculty could write analyses of interviews conducted by several classes, perhaps in coordination with colleagues in different schools.  Some papers could use the case reports and summaries as the basis of detailed analyses of theoretical issues.  Students, faculty, and others could post papers with these analyses on the Stone Soup database and/or SSRN, enabling others to incorporate the data and analyses into their work.

In this way, students and faculty truly would be creating knowledge together.  Indeed, this would be a collaborative effort that also includes practitioners, civilians, scholars, educational institutions, and professional associations in the process of generating, disseminating, and using this knowledge.

This list includes civilians (i.e., people not acting as professionals in the cases) as a potentially valuable source of knowledge.  For example, it would be useful for law students to interview legal clients and self-represented parties to complement the perspectives they would get from interviewing lawyers.  This would not only be useful for students, but it would provide a useful perspective for users of the data.

If enough faculty assign students to conduct interviews in their courses, students could conduct a variety of interviews during their course of study and develop their own, individualized body of empirical knowledge tailored to their particular interests.  Indeed, some students might conduct multiple interviews as part of independent study courses or for theses and dissertations.

Creating Valid and Useful Data

Many faculty wonder about the empirical realities of subjects they teach.  A Stone Soup assignment would enable them to assign a team of interviewers to explore particular questions of interest.  Faculty know from their own experience and others’ experience that practitioners don’t strictly follow doctrinal and theoretical prescriptions.  These faculty may want to use a Stone Soup assignment to analyze some of these differences.  This may be particularly relevant for some debates based on questionable empirical assumptions.  For example, in the dispute resolution world, people differ about the effects of integrative and distributive negotiation, “facilitative” and “evaluative” mediator interventions, and some arbitrations triggered by pre-dispute arbitration clauses.  Issues like these often are at the heart of our courses and students would benefit from learning about actual experiences relevant to these issues.

As I described in my post, What Me–A Social Scientist?, many people wrongly assume that social scientific knowledge comes only from large-scale quantitative studies with random selection of subjects.  In fact, research based on qualitative interviews is an important source of social science data, which generally is much easier to collect and analyze and which has some advantages compared with quantitative research.

In Case Studies and Theory Development in the Social Sciences, Professors Alexander L. George and Andrew Bennett wrote, “Case studies are generally strong precisely where statistical methods and formal models are weak.  We identify four strong advantages of case methods that make them valuable in testing hypotheses and particularly useful for theory development:  their potential for achieving high conceptual validity;  their strong procedures for fostering new hypotheses;  their value as a useful means to closely examine the hypothesized role of causal mechanisms in the context of individual cases;  and their capacity for addressing causal complexity.”

The Stone Soup project has developed detailed guidance for faculty  to develop assignments taking advantage of the benefits of qualitative case studies.  It also provides a document with guidance for students to conduct and document the interviews that carefully protect confidentiality and produce credible data.

Students would practice interviewing, documenting the interviews, and assessing the validity of the data, which are critical skills for lawyers and other practitioners.  In particular, this assignment would require students to develop rapport with their subjects, elicit sensitive information, and protect confidentiality.  They would then have to write up the interview data as a coherent narrative and consider possible alternative explanations, noting possible other perspectives, limitations of subjects’ memory, subjects’ desire to present themselves favorably, etc.  Their papers summarizing and analyzing the interviews generally should be of good quality because telling stories is a common way of understanding the world and students would be motivated to do a good job because it would be a required course assignment.

All social science data and studies are imperfect.  Even large-scale randomized experiments producing quantitative data are subject to error and alternative interpretations.  Consumers of social science data, especially scientists themselves, should evaluate research reports and consider alternative explanations of the data.  Thus to produce confident conclusions about particular issues, one must consider multiple studies, ideally including studies using varied sources of data and research methodologies.  Like all data, Stone Soup case reports would be subject to some errors.  The protocol for documenting the interviews is designed to help readers evaluate the credibility of the data.

Stone Soup data could be very helpful in complementing other sources of data.  This data could be particularly valuable considering the limited funding generally available for social science research and the fact that this project would involve no cost to students, faculty, or consumers of the data.

So the Stone Soup database would be part of a wiki project, somewhat like Wikipedia, in which many people would contribute to a valuable fund of knowledge.  Like Westlaw, it would include accounts of actual cases but it would focus on empirical accounts of the events in cases, not analyses of legal issues limited to legally-relevant facts.  Like SSRN, it would depend on contributions by our community, though the basic contributions would be reports and analyses of cases rather than other types of scholarly articles.  With enough participation over time, the pedagogy, research methodology, and theory content would become increasingly sophisticated.

The Stone Soup project could also promote learning and interaction across disciplinary boundaries.  Using a single database with a standard set of search variables would enable people from different disciplines and countries to share primary data, encourage cross-fertilization of ideas, and facilitate collaboration of academics.

I hope you will join me and other colleagues in creating knowledge together.


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