Hi Matt, >> For the social scientist, the approach raises two problems: >> >> 1) Too much reflection means too much attention to models of the world. >> To ask the right questions means having unbiased data on how people in >> some context of interest actually behave. >> > I take it that when you say context of interest you are inferring that > this is a model of the world. By context I mean some particular domain of human behavior that is believed to operate independently enough from others to name and study it. Societal impacts of science and technology would be an example of what I mean by context of interest. > I understand you as meaning that > context is unstable, always shifting, as a natural outcome of > reflection. The act of shifting contexts and perspectives and between > models of the world is reflexivity. Reflection on one's own experiences and comparing them with others (reflexivity) won't necessarily result in correct conclusions about why people do the things they do, or their larger social implications. Scientific work is incremental and academic departments usually operate more or less in parallel with others. So, by design there's a lot of correlated work (and I'd imagine thought too). Of course, focus can be good for punching through relevant problems in specific contexts..
To the point, it raises doubts in my mind just to what extent we can treat subjective reports of scientists and technologists as independent samples. > I'm, however, > unclear on the relationship of unbiased data to the framework you are > proposing. Suppose Bob's got an idea for an experiment and a paper to go with it. He runs the experiment and it fails to turn out the way he thought but reveals a better experiment which he also then runs and it results in an appealing outcome and insight. Now Bob writes the paper with a new plausible sounding hypothesis that nicely yields to the outcome and conclusion (as if the original hypothesis and experiment never had occurred). The paper is cited all over the place and Bob's a big hero. To understand problem solving in Bob's context, realizing their are potentially lots of Bobs, is it such a good idea to go on Bob's reflections and Bob's buddies? Wouldn't it be better to devise a way to monitor Bob's actual day to day work in some minimally intrusive way? One should worry about the accuracy of `reflections' and the reflexive cross comparison of them. It strikes me that research results in this area are vulnerable to self-aggrandizing delusions shared by the researcher and researched (both of the scientist type). >> 2) It's typically not possible to sufficiently influence or observe >> people to understand cause and effect across individuals or groups. >> The insights gained from reflexive participation will just be the kind >> of models we get living life (but with fancied-up language to sound more >> important than they are). Seems to me this kind of modeling is more the >> domain of the intelligence agencies than universities. >> > > I take it that when you say that there is an impossibility to > influence or observe then you are speaking from a particular model of > the world. I cannot understand what you mean by sufficiency until I > better understand where you are coming from. I don't think a cybernetic / control system approach to understanding human behavior is impossible, just expensive and something only certain governments could sustain in general form. One might imagine that.. 1) participants have models which may change in accordance to new observables 2) the models are shared to some extent (either to communicate or manipulate) 3) the participants are autonomous 4) the participants all have something at stake -- most aren't faking it 5) ..but some aren't what they seem -- they are there only to perturb and measure You can imagine that in this kind of scenario, you'll find individuals acting in authentic, motivated ways. If a set of participants in this situation had large (but invisible) cash resources to draw on, and were willing to tolerate risk (e.g. spies), they could in some sense facilitate the kind of data collection that would be needed to truly inform the agents in an agent based model and in turn make checkable predictions, and suggest further perturbations for refinement of a model. Overall I'm just saying it is plenty hard to make predictions about relatively simple physical dynamical systems, even when its possible to poke them to see how they react. Now let the particles have minds and layers of organizational insulation (receptionists, lawyers, etc.) and things get rather complicated when it comes to predicting things. ============================================================ FRIAM Applied Complexity Group listserv Meets Fridays 9a-11:30 at cafe at St. John's College lectures, archives, unsubscribe, maps at http://www.friam.org
