Heterodox concept features and onomasiological heterogeneity 33as a whole. Third, we calculate this proportion for each term in a concept
and then take the weighted average proportion. As before, we are weighting
terms by their token size within the onomasiological profile of the concept.
Figure 2. A schematic representation of geographical range
Once we have a measure for diversity, dispersion, and range, we can go
back to our earlier definition of heterogeneity as the product of diversity
and geographic fragmentation. Because geographic fragmentation rises as
dispersion increases, and diminishes as range increases, fragmentation may
now be defined as the proportion of dispersion and range. The overall for-
mula for heterogeneity then takes the following form:
heterogeneity = diversity x (dispersion / range)- Analyzing the data
The response variable and the five explanatory variables are subjected to a
multiple linear regression analysis. The results of the analysis are presented
in Table 2. The abbreviations used for the predictor variables as follows.
MISSING.PLACES: number of observational gaps
LACK.FAMIL: (assumed risk for) lack of familiarity
PROP.MULTIWORD: proportion of multiword answers
NON.UNIQUENESS: occurrences of names in other concepts
NEG.AFFECT: (assumed) negative affect