Glen E. P. Ropella wrote: > To be clear, the process works this way: > > 1) casual observation and psychological induction leads to a (usually > mental) model > 2) an experiment is designed based on that model > 3) data are taken from the experiment > 4) a more rigorous model is derived from the data (perhaps regulated by > the prior model) > 5) repeat as necessar That can happen, but it isn't necessary. An extreme example is study of financial instruments, where it is very clear how the `thing' works, and the process of measurement has nothing to do with modelers that might find the thing useful or interesting to study. The data from trading systems is complete and precise. The psychology or motives of the people using the system of course aren't directly measured, but at least this is not an example of a pathological circularity of data collection being biased by a mental model of the system.
In practice, I think often 1-3 are decoupled from 4, especially for `big science' where a lot of competitive people are involved. Even if it they were often tightly coupled, it strikes me as absurd to equate the value of multiple perspectives with experiment. (Not that you are..) If a whole range of mechanisms or parameterizations can reproduce an inadequate validation data set, and there is no way to imagine a way to measure a better one, then that's a clue the modeling exercise may lack utility. ============================================================ 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
