Machine Learning Methodologies

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Abstract

The purpose of this paper is to extend the UC Berkeley Statnews.org research program into the study of religion. Through synthesis of a precise semantic analysis conducted with the Statnews.org machine learning software and Barnesmoore’s History of Assemblages knowledge generation model, we present a mixed method approach for analysis of the relationship between causal discursive materials (in this case religious texts), ontological assumptions and epistemic mechanisms embedded in these discursive materials and norms of thought, behavior and being in societies socialized by analyzed texts. In so doing, we present a history of the dominant forms (ontological assumptions and epistemic mechanisms) embedded in the religious scriptures that have structured normative cognitive environments in the west. In so doing we hope to provide a point of entry for outlining the cognitive context in which forms manifest in the western world for future applications of the History of Assemblages methodology.