Bibliometric Evidence for a Hierarchy of the Sciences

PLoS One. 2013 Jun 26;8(6):e66938. doi: 10.1371/journal.pone.0066938. Print 2013.

Abstract

The hypothesis of a Hierarchy of the Sciences, first formulated in the 19(th) century, predicts that, moving from simple and general phenomena (e.g. particle dynamics) to complex and particular (e.g. human behaviour), researchers lose ability to reach theoretical and methodological consensus. This hypothesis places each field of research along a continuum of complexity and "softness", with profound implications for our understanding of scientific knowledge. Today, however, the idea is still unproven and philosophically overlooked, too often confused with simplistic dichotomies that contrast natural and social sciences, or science and the humanities. Empirical tests of the hypothesis have usually compared few fields and this, combined with other limitations, makes their results contradictory and inconclusive. We verified whether discipline characteristics reflect a hierarchy, a dichotomy or neither, by sampling nearly 29,000 papers published contemporaneously in 12 disciplines and measuring a set of parameters hypothesised to reflect theoretical and methodological consensus. The biological sciences had in most cases intermediate values between the physical and the social, with bio-molecular disciplines appearing harder than zoology, botany or ecology. In multivariable analyses, most of these parameters were independent predictors of the hierarchy, even when mathematics and the humanities were included. These results support a "gradualist" view of scientific knowledge, suggesting that the Hierarchy of the Sciences provides the best rational framework to understand disciplines' diversity. A deeper grasp of the relationship between subject matter's complexity and consensus could have profound implications for how we interpret, publish, popularize and administer scientific research.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Bibliometrics*
  • Science*
  • Statistics as Topic
  • Time Factors

Grants and funding

DF was funded by a Leverhulme Early-Career fellowship. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.