Note: This is an excerpt from a draft of my thesis, A Computer Model of National Behavior. The introduction and table of contents
are also available
3.9 Simple and Complicated Data
Robert Sargent wrote in 1997, â€œit is usually difficult, time consuming, and costly to obtain sufficient, accurate, and appropriate data.â€ Later in this thesis the data for this model, shown as attributes of entities, will be described. This â€œsimpleâ€ or â€œobjectiveâ€ data (e.g. population and population density) is very well established and has been tracked by governments in Europe for centuries.
However, some of the attributes are more obscure. Four of the attributes for one entity alone can be described as â€œcomplexâ€ or â€œsubjective,â€ and more attributes of other entities are
likewise.The need for values for these subjective attributes presents a challenge.
This problem is not new. In 1970, Clema and Kirkham reference Geutzkow and note â€œ[empirical] data, to a large extent, is lacking in the political sciences.â€ Because they are important they have to be accurate, otherwise there would be no sense in including them in the model. However, they are not objective so no value can be known for certain and good arguments might be made for dramatically different values for the same place by different experts. Several different options for getting values for these attributes are listed below. It goes without saying that whatever method is used should not allow picking-and-choosing, but must be coherent and fair.
One approach is to utilize a very small number of experts who agree with each other, so that their values will reflect one world view. It might not matter much which world view is reflected, so long as it is a developed and reasonable one. Different political philosophies might be equally valid given different facts and this approach would reflect that. This approach might be termed Bayesian because as Clema and Kirkham cite Kleinmuntz â€œ[experiments] have shown that human opinions do in fact change when new information is acquired in close accordance with Baye’s theorem and that human opinion change is a quite orderly process.â€ However, this method’s reliance on subjective data is a significant drawback.
Another possible approach is the Delphi method. In 1990, Roth and Wood noted â€œA major unresolved issue in the knowledge acquisition literature is the appropriateness of using several experts as knowledgeable sources.â€ For a research project, Roth and Wood used â€œa series of questionnaires to aggregate the knowledge, judgments, or opinions of experts in order to address to complex questions.â€ In other words, knowledgeable people could be polled on what they believe the correct values for attributes are, and their answers would be averaged. By incorporating the opinions of many leading thinkers in a field and giving greatest weight to what is most agreed on, the Delphi method is often successful.
However, for this model neither a small group of agreeing mostly experts nor the Delphi method will be used. Instead, values that can not be directly found will be derived from information that can be.
Orser and Zimmerman use a mathematical approach and make one variable dependent and one variable independent; for example, â€œ…and the formula Y= 15.06(X) + 194.23 for villages that contained over 88 lodges.â€ A similar tactic will be used for this model. However, given the wealth of European census information compared to century-old Arikara settlements, more than one independent variable may be used for each dependent variable.
These formulae will be determined during the construction of the model. Different values will be tried, and the final result will be the ones that give the most reasonable results. These values will not change during a run of the model because unlike a nation’s intelligence, these formulae effect the nature of the world, not how entities interact with the world.