Measuring similarity of concentration between different informetric distributions: Two new approaches

Abstract

Abstract From its earliest days, much investigative work in informetrics has been concerned with inequality aspects. Beginning with the well‐known Gini coefficient as a measure of the concentration/inequality of productivity within a single data set, in this study we look at the problem of measuring relative inequality of productivity between two data sets. A measure originally proposed by Dagum (1987), analogous to the Gini coefficient, is discussed and developed with both theoretical and empirical illustrations. From this we derive a standardized measure—the relative concentration coefficient—based on the notion of “relative economic affluence” also introduced by Dagum (1987). Finally, a new standardized measure—the co‐concentration coefficient, in some ways analogous to the correlation coefficient—is defined. The merits and drawbacks of these two measures are discussed and illustrated. Their value will be most readily appreciated in comparative empirical studies.

Cite this work

No public copy is stored for this record, so only the metadata is cited.

Stored only when both papers are in the corpus — 14 citations exist upstream.

Papers that cite the same references — the relational fallback while embeddings are still backfilling.