John Van Maanen, “Fieldwork on the Beat,” in John Van Maanen, James M. Dabbs, Jr., and Robert R. Faulkner (eds.), Varieties of Qualitative Research, Beverly Hills, CA: Sage, 1982, pp. 103-148

[p. 139]: “Fieldwork means both involvement and detachment, both loyalty and betrayal, both openness and secrecy, and, most likely, both love and hate. Some where in the space between these always personalized stances toward those one studies, ethnographies get written.”

I’m not sure if that description represents a false dichotomy or an acknowledgment of the complexity of human relationships. But if there is a dichotomy, I hear something that SPN might address. SPN at least challenges detachment and secrecy.

[145]: “Ethnography involves participant observation, but observation is the governing term because no matter how far the researchers may move in the opposite direction, they remain outsiders who will eventually leave the field, write reports, and move on in ways quite different from those studied.”

There’s a dividing line between SPN and ethnography (and a description that makes me wonder if autoethnography is oxymoronic). I won’t leave the field I study via SPN, at least not just because I’m done studying or have other research projects. I will continue equally as observer and participant, fellow constructor of the reality studied.

[147]: “I think it unavoidable that a reasonably well done study will make some people mad.”

Tee hee. Or should I say, uh oh?

[147-148]: Member and collegial tests are therefore hardly unequivocal or determinative. How far one chooses to respond to them is essentially a matter of reason, taste, and gut feeling. To use the elegant words of sociologist Egon Bittner (1973, p. 121), ethnographic research is based fundamentally on “passion and judgment”; thus, the accuracy of such reports can never be fully assessed. Perhaps the essential test as to whether one got it right or not is a most practical and heuristic one, a test based simply on the use the ethnography has for others who follow into the same field. Validity is then partially grounded in the return trip and established or denied only in close contact with those who were studied (and others “like those” who were studied). The original concepts and descriptions are then either rediscovered, altered, or abandoned on the basis of their ability to capture and give meaning to another’s observation and experience. Imperfect as this test may be, it is, in the final analysis, what is usually called science.

Ellingson, L. L., & Ellis, C. (2008). “Autoethnography as Constructionist Project.” In J. A. Holstein & J. F. Gubrium (Eds.), Handbook of Constructionist Research (pp. 445-465). New York: The Guilford Press.

I’m reading up on autoethnography, trying to get clear on how (and whether!) to distinguish it from scholarly personal narrative. Ellingson and Ellis (p. 450) talk about how Enlightenment ideals of scientific inquiry—remaining dispassionate, controlling conditions, converting observations to numerals, searching for the answer, separating truth from practice—”are rhetorically constructed to privilege the powerful elite and marginalize other voices” (they cite Gergen, 1999, pp. 91–93). Then this:

Autoethnography developed in large part as a response to the alienating effects on both researchers and audiences of impersonal, passionless, abstract claims of truth generated by such research practices and clothed in exclusionary scientific discourse (Ellis, 2004). It attempts to disrupt and breach taken-for-granted norms of scientific discourse by emphasizing lived experience, intimate details, subjectivity, and personal perspectives. Thus autoethnography as a method participates in the ongoing social construction of research norms and practices at the same time that it seeks to influence the social construction of specific phenomena (e.g., child abuse; Hacking, 1999).

Whether or not SPN and autoE are equivalent, it’s pretty clear they offer the same response to the “impersonal, passionless, abstract” research paradigm. SPN and autoE are a critique of the academic status quo. In a way, they are in-house action research: by advancing SPN and autoE, we call those marginalized voices back to the center.

Yahoo! Call it a dry run for MWAIS: here’s my slideshow on SPN in KM! It should have audio; if it doesn’t, contact me and complain, and I’ll fix it!

Practicing What We Preach: Narrative in Knowledge Management

Probably the maddest idea yet: Toby and I plan to co-author a paper on Robert J. Nash‘s scholarly personal narrative methodology and its possible application to information systems. Former debate coach and student affairs specialist submit paper to MWAIS — right.

Nash’s idea of moral conversation comes from the same convictions as his idea of scholarly personal narrative. There is much to think about here, not only for scholarly research and publication but also for teaching (and etymology reminds us that, if we’re Nash, we refer to it as education), blogging, and participatory democracy… in other words, pretty much everything I’m interested in.

Rehg, William, McBurney, Peter, and Parsons, Simon. (2005). “Computer Decision-Support Systems for Public Argumentation: Assessing Deliberative Legitimacy,” AI & Society (19), 203-229.

  1. “decision-support systems for public policy argumentation” so far focus more on reasoning, and inference — the dialectic process — than rely on knowledge database; thus “argumentation systems” rather than “knowledge systems”
  2. CAH hits the bullseye: “If appropriately designed, such systems should be able to assist debate by tracking various claims and arguments, by searching databases for relevant information, and by continually updating and assessing the overall state of the debate.” (204)
  3. gaps between formal design and practice show that AI researchers need to “engage in interdisciplinary experimentation;” hang with the poliSci, Soc, and other social scientists; and participate in the public discourse system themselves (205)
  4. Zeno system
    1. EC-funded, GMD urban planning
    2. developers (Gordon and Karacapilidis) call it “mediation system”
    3. formalized IBIS (issue-based information system) model (Rittel & Webber 1973)
      1. issue: topic (“Where should we put the airport?”)
      2. position: some relevant statement (“We should put it in Bob’s cornfield.”)
      3. argument: statements for or against positions (“Bob’s cornfield is too close to the hospital.”)
    4. actually labels positions as acceptable or not based on established constraints
    5. supports real-time debates
    6. intuitive, graphical interfaces
  5. Risk Agora (McBurney and Parsons)
    1. Proposed for scientific debate “over the potential health and environmental risks of new chemicals and substances and the appropriate regulation of these substances” (207)
    2. like Zeno, labels arguments, seeks to give snapshot of overall status of debate
    3. not meant for real-time
    4. no intuitive, graphical interfaces
  6. Three key roles for argumentation systems:
    1. support participants (help citizens, mediators, decision-makers find info)
    2. serve orrery role (keep records)
    3. provide forum for dialogue
    4. systems not close to being participants or decision-makers
  7. Problem with evaluation of SDSS: how do we know it’s producing any better decisions than the old way? How do we measure the effectiveness of the old decision-making process? “The precise problem that interests us here, however, is the lack of an inherent, or independently accessible, standard of truth or correctness for urban planning decisions” (212) or any social decision, for that matter. Closely tied to our political biases!
    1. Think of it this way: plug in the CLDS, let it run for five years. How can I tell if Russ is making better decisions now than he was pre-CLDS?
  8. Standards from Schmidt-Belz et al. (1998)
    1. efficiency
    2. transparency
    3. non-coerciveness
    4. equality of participation
  9. Legitimacy: Four dimensions of “reasonable deliberative transformation”
    1. “self-transformation”
      1. deliberation central, not bargaining (the latter is the “conventional pluralist model”)
      2. delib focuses more moving people from self-interest to conception of common good; bargaining about maximizing util.
      3. participants willing to share info, learn from each other, even change (transform!) position (negotiators usu. hold some info back)
    2. substantive dialectical quality
      1. “truth” a bad measure!
      2. address all relevant information
      3. arrive at msot justifiable/reasonable outcome
      4. combination of expertise and values
    3. inclusiveness
    4. non-coerciveness
      1. not enough to give everyone access; you also have to make sure there’s not some aspect of the system that limits some users ability to have their say and to learn from other participants
      2. watch those mediators!
  10. formal procedures can be coercive, inhibit knowledge flow! Check with these three questions, based on the above roles:
    1. “Do the participant-support mechanisms favor some parties over others?”
    2. “Is the tracking or record keeping genuinely neutral — that is, can each stakeholder perceive that the system has represented his or her or its position, interests, calues, and arguments accurately?”
    3. “And does the forum structure (e.g., the sequencing of links at the user-interface) give some participants greater opportunity to influence the deliberation?” (222)
  11. Note that determine whether there is coercion, the researcher must become a participant, talk to the other participants, understand things from their context

McBurney, Peter, and Parsons, Simon. (2001). Intelligent systems to support deliberative democracy in environmental regulation. Information & Communications Technology Law, 10(1), 79-89.

Ugh! Abstract only, no full text! Get it!

Among normative models for democracy, the Deliberative Model suggests that public policy decisions should be made only following rational, public deliberation of alternative courses of action. This article argues that such a model is particularly appropriate for the assessment of environmental and health risks of new substances and technologies, and for the development of appropriate regulatory responses. To give operational effect to these ideas, a dialectical argumentation formalism for an intelligent system within which deliberative debates about risk and regulation can be conducted is proposed. The formalism draws on various philosophies of argumentation, scientific and moral discourse, and communicative action, due to Toulmin, Pera, Alexy and Habermas. (!!!)