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Understanding Scientific Methodology in the Historical and Experimental Sciences via Language Analysis

Abstract

A key focus of current science education reforms involves developing inquiry-based learning materials. However, without an understanding of how working scientists actually do science, such learning materials cannot be properly developed. Until now, research on scientific reasoning has focused on cognitive studies of individual scientific fields. However, the question remains as to whether scientists in different fields fundamentally rely on different methodologies. Although many philosophers and historians of science do indeed assert that there is no single monolithic scientific method, this has never been tested empirically. We therefore approach this problem by analyzing patterns of language used by scientists in their published work. Our results demonstrate systematic variation in language use between types of science that are thought to differ in their characteristic methodologies. The features of language use that were found correspond closely to a proposed distinction between Experimental Sciences (e.g., chemistry) and Historical Sciences (e.g., paleontology); thus, different underlying rhetorical and conceptual mechanisms likely operate for scientific reasoning and communication in different contexts.

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Notes

  1. The term “historical science” is used here to label sciences such as geology, paleontology and evolutionary biology that deal with either, or both the historical development of the physical and biological features of our planet (and beyond). In particular, the purpose of such sciences is to reconstruct such features and the processes, which created them (in a broad sense, similar to the idea of how the discipline of history tries to reconstruct the social and economic conditions which have influenced the development of human society). Indeed, there is some precedent within the research literature for labeling these sciences as “historical”. Thus, Cleland (2001, 2002), and Frodeman (1995), incorporate “historical science” directly within the title of their works (which deal in particular with the earth sciences) while contrasting its methodology with experimental sciences, such as chemistry. For an extensive treatment of the historical approach in evolutionary biology, specifically, one can turn to O’Hara (1988) and especially Goudge’s (1961) The Ascent of Life. Earlier philosophical work by Hull (1975) and Kitcher (1993) also refers to the distinction between historical and experimental science, as does Diamond’s (2002) more popular work on the development of human societies. Finally, we might cite the special case of Stephen J. Gould who has championed the idea of there being a distinct historical method amongst the sciences both in his professional writing (see for example, Gould (1986, 2002) and more popular works (such as Gould (1989)).

  2. Roth and Bowen (2001a) and especially Lynch (1993) provide an extensive review of the early and main ethnographic studies of science practice. In turn Lynch’s (1983) review is based on Knorr-Cetina and Mulkay’s (1983) earlier discussion in their collection Science Observed. In turn, Dunbar (1995, 1999) gives a good summary of many of the (early) cognitive studies of scientists in action.

  3. Exceptions to this rule are McKegney’s (1979; cited in Lynch 1993) early work on wildlife ecology as well as Roth and Bowen (2001a, b) and Bowen and Roth’s (2002, 2007) more recent work, which also focus on ecologists. However, many of the other field-based sciences are largely missing in action, with no large-scale studies of geologists, paleontologists, or archeologists found in the literature.

  4. This formulation is based on Diamond (2002, pp. 421–424), though he identifies the four dimensions as “methodology, causation, prediction, and complexity.” The restructuring, originally given in Dodick and Argamon (2004), makes the underlying issues clearer for our purposes.

  5. As Schumm (1999, p. 7) notes, the term prediction in science is used in two ways. “The first is the standard definition to foretell the future. The second is to develop a hypothesis that explains a phenomenon”. Based on the second definition such predictions have the typical form of: ‘if a given hypothesis is correct then we predict that the following process or phenomenon will occur’. Commonly, such predictions involve extrapolation, a specification of what will happen (based on initial data, or trends in measurements) and is a defining characteristic of experimental science. However Schumm (1999) argues that in some fields of historically oriented earth science (for example, geomorphology) predictive extrapolation is also part of their current methodology. Even so, we argue that such predictions are far less common and accurate in historical based sciences, than they are in experimental sciences, in large part due to the complexity of the phenomena studied in historical-based science; instead, historical science focuses on reconstructive explanations, via the method of retrodiction or postdiction, which might be defined as a specification of what did happen. As Ben-Ari (2005, p. 15) notes “retrodiction is essential if theories are to be developed for the historical sciences.” Indeed Schumm (1999) admits that it is only when the present conditions are understood and when the history of the situation has been established that predictions can be made with some degree of confidence in earth science. In other words, in historical based sciences, such as geology reconstructing the past conditions takes precedence, and as a method has greater validity than predicting (the future).

  6. For an opposing view to Cleland (2001; 2002) see Turner’s (2005) paper: Local Undetermination in Historical Science.

  7. SMO is an implementation of a widely used machine learning method known as Support Vector Machines (Cristianini and Shawe-Taylor 2000), which finds a linear function separating two classes of vectors (in our case, document vectors).

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Acknowledgements

Thanks to Martha Evens, Peter Greene, Richard Schultz, and the late Nambury Raju for helpful comments on earlier versions of this manuscript.

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Correspondence to Jeff Dodick.

Appendix A: The Corpus

Appendix A: The Corpus

This study analyzes a corpus of recent (2003) articles drawn from twelve peer-reviewed journals in both historical and experimental sciences, to which the Illinois Institute of Technology has electronic subscriptions. Scientific journals representative of the historical sciences were taken from the fields of geology, evolutionary biology, and palaeontology, comprising:

  • Journal of Geology includes research on the full range of geological principles including geophysics, geochemistry, sedimentology, geomorphology, petrology, plate tectonics, volcanology, structural geology, mineralogy, and planetary sciences.

  • Journal of Metamorphic Geology focuses on metamorphic studies (changes in mineral assemblage and texture in rocks that have been subjected to temperatures and pressures different from those under which they originally formed), from the scale of individual crystals to that of lithospheric plates.

  • Biological Journal of the Linnean Society publishes work on organic evolution in a broad sense, particularly research unifying concepts of evolutionary biology with evidence from genetics, systematics, biogeography, or ecology.

  • Journal of Human Evolution covers all aspects of human evolution, including both work on human/primate fossils and comparative studies of living species.

  • Palaeontologia Electronica publishes papers in all branches of palaeontology as well as related biological or paleontologically-related disciplines.

  • Quaternary Research published research in diverse areas in the earth and biological sciences which examine the Quaternary period of the Earth’s history (from roughly 1.6 million years ago to the present).

The experimental scientific fields considered are physics, physical chemistry, and organic chemistry; the journals used in our corpus are:

  • Physics Letters A publishes research in a wide range of areas, including condensed matter physics, theoretical physics, nonlinear science, statistical physics, mathematical and computational physics, atomic, molecular and cluster physics, plasma and fluid physics, optics, biological physics and nanoscience.

  • Physical Review Letters also covers a wide range of physics research, including: gravitation and astrophysics, elementary particles and fields, nuclear physics, atomic, molecular, and optical physics, nonlinear dynamics, fluid dynamics, plasma and beam physics, and condensed matter physics.

  • Journal of Physical Chemistry A publishes chemical research at the level of molecules (including dynamics, spectroscopy, gaseous clusters, molecular beams, kinetics, atmospheric and environmental physical chemistry, molecular structure, bonding, quantum chemistry, and general theory).

  • Journal of Physical Chemistry B publishes research on materials (including nanostructures, micelles, macro-molecules, statistical mechanics and thermodynamics of condensed matter, biophysical chemistry, and general physical chemistry), as well as studies on the structure and properties of surfaces and interfaces.

  • Heterocycles publishes research in the areas of organic, pharmaceutical, analytical, and medicinal chemistry of heterocyclic compounds.

  • Tetrahedron publishes general experimental and theoretical research results in the field of organic chemistry and applications in related disciplines especially bio-organic chemistry.

The numbers of articles used from each journal and their average (preprocessed) lengths in words are given in Table 1 above. The full list of features and lexical items used, as well as the processed document vectors, are available for review at http://www.lingcog.iit.edu/Science05data/index.htm.

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Dodick, J., Argamon, S. & Chase, P. Understanding Scientific Methodology in the Historical and Experimental Sciences via Language Analysis. Sci & Educ 18, 985–1004 (2009). https://doi.org/10.1007/s11191-008-9146-6

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Keywords

  • Scientific method
  • Historical science
  • Experimental science
  • Language
  • Computational linguistics
  • Scientific reasoning
  • Cognition