Data & Analysis
Three other articles by Stirling are relevant here(Stirling, 1992a), (Stirling,1992b), (Stirling,1988).
Finding a Metric: Indexes: Ethnography & Database.
When I first started to gather and analyse this data it was my intention that I should immerse myself in the works to gain the insights of familiarisation; try to get some ideas from a few speculative investigations and eventually incorporate many aspects of the 'wiring' diagram into a simulation. I could then experiment with it in a flexible way and 'test' a few of Stirling's models. I was looking for many variables. To these ends I was interested in household structures9; lineage relations45; kinship27relations; genealogies(Appendix C); inheritance rules2; cultivatable land area (Appendix C); growing patterns35; crop yields (Appendix C); types of crops grown44; animal usage; historically significant events23 i.e. the introduction of tractors and fertilizers; population demographic features (Chapter Three); marriage patterns26; land carrying capacity (Chapter Three); birth rates; death rates; infant mortality rates (Chapter Three) etc. I was also looking for index data i.e. some variable or variables in his data acting across the simulated time period that would act as an indicator against which to evaluate possible simulations. As the research progressed it became apparent that this in itself was a major undertaking, more than I could take on at the MA level. My ambitions became humbler. However by that time I had extracted a quantity of data already. This was not a wasted exercise and although I eventually used only a subsection of it I present my findings in (Appendix C) as they are of related interest. This data can still be used in a later extension of this project.
The first problem I tackled was Stirling's relational database. This repository of knowledge was in an incomplete state. Although much of the data had been loaded into the tables and the application interface written to do most of the ISQL processing and updating of tables, some of the data I needed was not in place. Over the years of its development several people had worked on it and the documentation was very fragmented. I spent a few weeks deconstructing this relational data base by examining its. OSQ 4 GL code files, in order to compile a current data dictionary and to understand how the tables were being modified by the application frontend. The results i.e. the 'Lifehist 'application frontend; diagrams and documentation are in Appendix E and the data dictionary in Appendix E1 -. I decided next to try to extract some population demographics out of the three lots of census data held within it. I was able to work directly with the table data using the data dictionary I had compiled via a SQL query program thus bypassing the normal user interface. The database was an excellent tool when used to generate new table data but terrible for analysing it. I transferred the new table data to various other programs for that. The resulting graphs are shown below:
This histogram shows an aggregated male and female age histogram for the census date of 1950. The age scale is set at 1 year increments (Bin = 1). This illustrates a standard demographic feature, that of age aggregation. A lot of the reported ages fall in years that end in 0 or 5, especially the older generation. Clearly, numerical age has not been that important for these people in the recent past. This graph lead to the decision to aggregate ages at Bin = 5 i.e. 5 yearly intervals in order to smooth out this artifact.
This aggregated age histogram shows male plus female age distributions for 1950. There is a significant population drop over the expected normal distribution in the 30 - 40 group.
This is the male age histogram for 1950. It shows the same population drop in the 30 - 40 year olds. The oldest members of the community seem to have been women.
This is the female age histogram for 1950. It shows the same population drop in the then 30 - 40 year olds. This corresponds with the fwars in Turkey from 1911 to 1922. The oldest members of the community seem to have been women.