Theories of scientific development
Science is a complex system with dynamic elements (e.g., disciplines and research fields) that develop over time. The evolution of science is critical to explain human progress. The most prevalent theories of scientific development are:
- theory of the accumulation of knowledge
- theory of scientific paradigm shifts by Khun
- theory of research programme by Lakatos
- theory by Tiryakian
- theoretical revisionism by Alexander Jeffrey
theory of openness, closure and branching described by Mulkay.
The cumulative theory of knowledge
Science is an activity of accumulation (Science, 1965). The cumulative theory states that scientific development is due to a gradual growth of knowledge based on a sum of facts accumulated by scholars, institutions and other actors (Haskins, 1965; Godin, 2001). In particular, Seidman (1987, pp. 121-122) argues that: “The cumulative addition of facts and verified propositions, conceptual refinements, or analytical developments dislodge erroneous theories, and propels us toward theories which are closer to the truth about society…. virtually every current social scientific theory strives to achieve legitimacy and dominance by reconstructing the past as a cumulative development crystallizing in its own systematization”. In this context of the accumulation of knowledge, basic and applied sciences evolve and converge creating a deeper unity within the overall structure of science (Coccia and Wang, 2016; Haskins, 1965). Moreover, in this approach the evolution of science is irreversible and can never go back (Science, 1965).
The model of scientific paradigm shifts by Khun
The scientific development is due to accumulation of “normal science”[1], interrupted by discontinuous transformations generated by new theoretical and empirical approaches that support the transition from an existing scientific paradigm to an emerging one. In fact, paradigm shifts are the major source of scientific change in society (Kuhn, 1962). Moreover, in this theory, scientific paradigm shift can be major in the presence of discontinuity with previous theoretical framework (e.g., target therapy vs. chemotherapy in cancer treatments; cf. Coccia, 2012b, 2012c, 2014a, 2015a, 2016a), and minor whether it generates continuity between successive paradigms (e.g., nanoparticle-delivered chemotherapy in oncology that combines traditional chemotherapy and emerging nanotechnologies; Coccia and Wang, 2015; cf., Clark, 1987). In general, major or minor paradigm shifts support the long-run evolution of science, disciplines and research fields over time. [1] “ ‘normal science’ means research firmly based upon one or more past scientific achievements that some particular scientific community acknowledges for a time as supplying the foundation for its further practice’’ (Kuhn, 1962, p. 10, original emphasis).
The theory of scientific programme by Lakatos
Lakatos (1968, p. 168, original Italics and emphasis) argues that:
The programme consists of methodological rules: some tell us what paths of research to avoid (negative heuristic), and others what paths to pursue (positive heuristic)
Lakatos’ theory of research programme is based on a hard core of theoretical assumptions that cannot be abandoned or altered without abandoning the programme altogether. The evolution of science here is due to the creation of a research programme that guides the scientific development of one or more research fields and/or disciplines over time (Lakatos, 1978). Finally, Lakatos’ theory also argues that a research programme, in the presence of troublesome anomalies, remains progressive despite them.
The theory by Tiryakian for scientific development
Tiryakian (1979) argues that the scientific school is the unit of analysis for a model of scientific development. Major schools develop scientific disciplines by providing new methodologies or new conceptual schemes of social reality. Tiryakian (1979) rejects both the empiricist approach that discoveries initiate scientific change and the rationalist claim that conceptual refinements of theoretical models stimulate a scientific change. In short, the formation of a school offers new scientific directions to study social reality that initiates significant scientific advances over time (e.g., in economics, the Monetarism is a new school of thought based on control of money to affect price levels and economic growth versus Keynesian economics based on government expenditures with fiscal policy to support economic development).
The revisionism by Alexander Jeffrey for scientific development
Seidman (1987) argues that: “the discovery of anomalies or analytical criticisms of one or another dimension of a theory sets in motion a process of theoretical revision”. Unlike Kuhn (1962), Alexander (1979) proposes that scientific theories do not change in a revolutionary manner. Scientific theories are based on different autonomous entities, such as presuppositions, ideologies, models, laws, concepts, propositions, methodologies, etc. that shape science, articulate its problems, and have a distinctive mode of discourse with its own standards of assessment. In short, Tiryakian (1979) analyzes the tensions and dynamics of the social structure of the school and its relation to scientific community. By contrast, Alexander (1983, p. 349) argues that the engine of scientific change is due to new theoretical frameworks of scholars that generate a revision of current conceptual scheme in specific field of research, marking the life-history of a school.
Models of scientific progress: openness, closure and networking
The theories of openness in science
The theories of openness argue that science and technology are most likely to flourish in democratic society because science and technology have democratic values and democratic nations do not have barriers towards discoveries and new technology (cf., Coccia, 2010). In this context, scientific breakthroughs can be advances of knowledge if findings are made accessible to the critical inspection of other scholars in scientific community. In short, researchers have to communicate new results and data to other scholars, facilitating the reproducibility of results for validation of findings and/or new theories. Researchers, producing and sharing discoveries, are rewarded with a higher reputation and recognition in scientific communities, increasing the diffusion of their theories, the citations of their research articles and the funds for research, etc. (cf., Coccia, 2019; Merton, 1968; Bol et al., 2018). Hence, science, within open research communities and democratic settings, will grow rapidly because there is low resistance to new scientific ideas and technologies (De Solla Price, 1986; Kitcher, 2001; Merton, 1957; Mulkay, 1969; Coccia, 2010).
The theory of closure in science
Mulkay (1975, p. 514) argues that the advances of scientific knowledge in Kuhn’s theory are due to intellectual closure, rather than intellectual openness of scholars. In particular, the scientific evolution is due to an open rebellion against the existing paradigm created by intellectual orthodoxy (Cohen, 1952). In fact, scientific paradigm shift is mainly due to an accumulation of anomalies that cannot be answered within existing scientific rules or theories. These anomalies of existing paradigms lead to few scholars to think in wholly new directions, changing accepted paradigms in science and giving a new conceptual scheme (Boring, 1927).
The theories of networking and branching in science
Science can evolve with social and research networks of scholars (Adams, 2012, 2013). In this context, Mulkay (1975) argues that the exploration of new research fields generates a scientific migration of scholars from established research networks that are declining in terms of significant results to new research fields Coccia, 2018; Mullins, 1973; Wagner, 2008). In this approach, leading scholars create research teams investigating new topics that have international scientific collaborations in new research networks (cf., Coccia, 2018).
Finally, the determinants of breaching and scientific specialization can be due to a process of convergence between basic and applied sciences, from a specialization within applied or basic sciences or through the combination of multiple disciplines (cf., Coccia and Wang, 2016; Jamali and Nicholas, 2010; Jeffrey, 2003; Riesch, 2014; van Raan, 2000; Wray, 2005). In the evolution of scientific fields, Small (1999, p. 812) shows that: “crossover fields are frequently encountered.” To conclude, Sun et al. (2013) state that social interaction among groups of scientists is: “the driving force behind the evolution of disciplines” (cf., Wuchty et al., 2007).
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