An investigation on the skewness patterns and fractal nature of research productivity distributions at field and discipline level

TL;DR

This study empirically analyzes research productivity distributions across fields and disciplines, revealing skewness patterns and the limited presence of fractal structures, based on a large dataset of scientists and using advanced distribution analysis techniques.

Contribution

It provides a detailed empirical comparison of productivity distribution patterns across fields and disciplines, highlighting skewness variability and fractal characteristics.

Findings

Research productivity distributions are asymmetrical at the field level.

Skewness varies substantially among different fields.

Fractal nature is generally not observed in productivity distributions.

Abstract

The paper provides an empirical examination of how research productivity distributions differ across scientific fields and disciplines. Productivity is measured using the FSS indicator, which embeds both quantity and impact of output. The population studied consists of over 31,000 scientists in 180 fields (10 aggregate disciplines) of a national research system. The Characteristic Scores and Scale technique is used to investigate the distribution patterns for the different fields and disciplines. Research productivity distributions are found to be asymmetrical at the field level, although the degree of skewness varies substantially among the fields within the aggregate disciplines. We also examine whether the field productivity distributions show a fractal nature, which reveals an exception more than a rule. Differently, for the disciplines, the partitions of the distributions show skewed patterns that are highly similar.