Assigning fossil specimens to a given recent classification when the distribution of character variation is not normal

To help assign fossil material to Recent taxa we present a methodology that offers systematic quantitative tools to explore several continuous characters. It also enables the quantitative determination of which characters amongst several alternatives give results more consistent with a given classification. The Gini Mean Difference ('Gini') is the expected absolute difference between two randomly drawn observations. In a fossil assemblage comprising several taxa, the Gini of the overall assemblage may be decomposed into three components: the weighted sum of intra-taxon Gini, the index of overlap, and the inter-taxon Gini. The parameter that is additional to alternative methods is the overlap index, which serves as a quantitative measure for evaluating the quality of identification. The Gini is advantageous in that it does not require the assumption of a normal distribution in character variation. The Gini methodology is described in both mathematical and non-mathematical terms. We demonstrate it by application to a hypothetical gastropod genus consisting of five species, in which we show in orderly, quantitative terms that one character is better for identification of the various species than another character.