A methodology for identifying prehistoric local learning communities is proposed. We wish to test possible relationships among communities based on continuity and variability in lithic reduction sequence technological traits with different visibility and malleability. Quantitative features reflecting different technological traits are measured on 3-D models of flint cores in different scales: the ratio between core thickness and reduction surface width, the angle between subsequent bands of production blank scars to the relative striking platform, and the average curvature of the ridge between each blank scar striking platform pair. Continuity and variability in these features are used to establish the relations among lithic assemblages on different hierarchical levels: local learning communities and geographically widespread cultural lineages. The Late Upper Palaeolithic and the Epipalaeolithic of the Southern Levant (ca. 27,000–15,000 cal BP) provide an opportunity to test our method. A progressive increase in territoriality is hypothesized throughout this timespan, yet the precise timing and modes of this phenomenon need to be defined. The present study analyzes six core assemblages attributed to different cultural entities, representing chronologically separated occupations of the Ein Gev area and the coastal Sharon Plain. Continuity in technological traits between the Atlitian (ca. 27,000–26,000 cal BP) and Nizzanan (ca. 20,000–18,500 cal BP) occupations of the Ein Gev area suggests that the same learning community repeatedly settled there during a long time span. Two geographically separate learning communities were defined in the study areas within the Kebaran cultural entity (ca. 24,000–18,000 cal BP); the group occupying the Ein Gev area possibly continued to settle there during the Geometric Kebaran (ca. 18,000–15,000 cal BP). Continuity in more conservative traits of the reduction sequence allows to tie these two communities to the same cultural lineage. The ability to track prehistoric learning communities based on quantitative features helps increase the objectivity and the resolution in the reconstruction of past cultural dynamics.
Read full abstract