A new approach to concept basicness and stability as a window to the robustness of concept list rankings

Based on a recently published large-scale lexicostatistical database, we rank 1,016 concepts by their suitability for inclusion in Swadesh-style lists of basic stable concepts. For this, we define separate measures of basicness and stability. Basicness in the sense of morphological simplicity is measured based on information content, a generalization of word length which corrects for distorting effects of phoneme inventory sizes, phonotactics and non-stem morphemes in dictionary forms. Stability against replacement by semantic shift or borrowing is measured by sampling independent language pairs, and correlating the distances between the forms for the concept with the overall language distances. In order to determine the relative importance of basicness and stability, we optimize our combination of the two partial measures towards similarity with existing lists. A comparison with and among existing rankings suggests that concept rankings are highly data-dependent and therefore less well-grounded than previously assumed. To explore this issue, we evaluate the robustness of our ranking against language pair resampling, allowing us to assess how much volatility can be expected, and showing that only about half of the concepts on a list based on our ranking can safely be assumed to belong on the list independently of the data.