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What the Networks Study Shows?

In order to complement the speeches of the researchers, we next present the graphs that illustrate the production of these six researchers’ leaders over a period of 10 years (Fig. 4.1). Those illustrative sets of graphs are a rational choice or a theoretical sample (Pires, 2012, p. 157) made up of the articles’ coauthorship networks of six of the subjects considered in the

Coauthorship articles 2001-2010 from Brazil (PE, SSHEd) and Portugal (SSH). (Source

Fig. 4.1 Coauthorship articles 2001-2010 from Brazil (PE, SSHEd) and Portugal (SSH). (Source: The authors, 2016) original study. In Fig. 4.1, the first four graphs are related to Brazil and the last two are related to Portugal. The first two graphs (PE-BR1 and PE-BR2) represent articles’ coauthorships net of two researchers of excellence in Production Engineering, affiliated to different Brazilian universities. The other two graphs (SSHEd-Br1 and SSHEd-Br2) illustrate the net articles coauthored by researchers of excellence from the Education area in Brazil. Finally, there are two graphs (SSH-Pt1 and SSH-Pt2) of articles published by Social Sciences and Humanities researchers of excellence in Portugal.

When we observe those six graphs, important differences among areas of knowledge and between countries arise. The graphs that are complex and intense in collaboration are the first two, PE-Br1 and PE-Br2, and SSH-Pt1, showing a large number of articles published with several collaborators. On the other hand, the SSH-Pt2 and SSHEd-Br2 networks present few nodes and have more or less similarly lower intensity of collaboration as detected by the vertices’ average degree in each network. The SSHEd-BR 1 is a weak collaboration network.

The nodes of these six networks are represented by researchers and members from a variety of institutions, universities, agencies, foundations, corporations, and other entities. Some networks center on the leader and others show links between the members without passing through the leader; for example in PE-Br1 and SSH-Pt1 networks, we can see several nodal points that hold the web of knowledge. These are subgraphs that permit new combinations and partnerships to expand the network in new directions.

Notice that the information about the nodes allows us to classify the networks as national or international, and as endogenous or exogenous, regarding institutional affiliation. Therefore, we classified SSHEd-Br1 network as endogenous, unidirectional, and dyadic. It portrays the connection of the leader with their current and former advisees and students. This does not shows the network that is behind invisible college as appointed on interviews, an invisible college ofschool teachers who follow the leader and read his/her publications (Crane, 1972; Katz and Martin, 1997).

The SSHEd-Br2 network, likewise, shows one-directional ties between the leader (egocentric network) and the other nodes, closeness only between a few nodes, and a restricted number of stronger or dense nodes. The SSH-Pt2 network is similar to SSHEd-Br2 in terms of the position of the leader, unidirectional relations, a few nodes in isolation, and multiple-directional relations among coauthors.

As a counterpoint, the network of the PE-Br1 researcher is dense and decentralized, with researchers from the same country and from other countries representing several universities. The proximity and degree of intermediation show the possible leader power (degree of intermediation)3

his/her role in getting and connecting resources. Otherwise, the nodes would be separate and distant. This network confirms Newman’s (2001a) and Katz and Martin’s (1997) remarks about the differences among knowledge and disciplinary fields and about the interdisciplinary publications with a greater number of collaborators in the applied and experimental sciences.

Until now, we showed in this chapter selected data from a research that studied researchers of excellence, operating in consolidated research groups from leading universities. Next, we take another approach by using a single case study to show how science grows and also develops in new universities, with young research leaders, international match, and multivariate connections.

 
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