A ‘Divergence Problem’ of global explanatory models in-between science and humanities

Abstract

Models are fundamentals in science, and particularly in archaeology (Clarke 1972 ; Drost and Vander Linden 2018 ; Lake 2014 ). Building on reconstructions of past human behaviour, all interpretations of archaeological records are ultimately models, i.e. simplifications of potential past ‘realities’, or more meaningfully interpreted as individually perceived life-worlds. Inherent in this concept is, however, that all models are never real but abstractions of interconnected variables that best describe an assumption, another variable, or a particular pattern. A simple version of a model that is used for explanatory or predictive purposes is a linear model in which a variable is best predicted by another or a combination of predicting variables. At best, this results in a simple equation that integrates a series of covariates into an explanatory model. Simplicity is the key to maintain physiological sense without overfitting the model with an increasing number of parameters or variables. But these models work well only within a particular spatio-temporal window of operation and in regional or local context. Major problems emerge on the global scale. System interconnectivity, including ecosystem functionality, resource availability, and (planetary) climate systems, increases rapidly with increasing scale of the analyses. And basic geographic factors, such as latitudinal and altitudinal gradients, continental and oceanic climate zones, or interregional connectivity and permeability prevent push-button global model comparability. Consequently, environmental explanatory parameters are unlikely to work similarly in different locations of the earth and can eventually generate feedbacks that further amplify a regionalisation trend of the model. Fitting a larger number of variables to the model in search for more significance of the power of the model only increases complexity but not comprehensiveness of the model.

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