870 E. Corbera et al.
TABLE 1 Social network measures considered in this research. Social measures
Explanation
Network Nodes
Components Density
Centralization index
Individual Degree centrality
Betweenness centrality
Size or number of nodes in the social network. The minimum number of nodes is two. When visually represented, larger nodes in a network mean they have a higher degree of connections in the network than smaller nodes.
Refers to the number of connected subgraphs in which all nodes are in contact with each other. The minimum number of components is one,&the fewer the number of components in a social network, the more connected such a network is. A large number of components indicates the existence of subnetworks that may or not be connected to each other.
The number of links in a social network, expressed as a proportion of the maximum possible number of links. A density score of 1 indicates all nodes are directly tied to one another, & a density score of 0 indicates no nodes are connected.
Expresses the tendency for a few nodes in a social network to have many ties (expressed as a per cent). A central- ization score of 100% indicates that all ties link to one node, & a score of 0% indicates a fully connected network, where all nodes are directly connected to each other.
Indicates the number of direct ties a node has to another node.
Indicates the number of times a node rests on the geodesic (shortest path) between two other nodes. Theoretically, if a node in a network rests between many other nodes, then this node has the chance to withhold or distort any information it receives, thereby influencing the whole network.
problems of using this method and binary classification, but authors’ pronouns were not generally available. We recorded each author’s PhD granting institution and coun- try, with countries further coded using the United Na- tions country group categories: EU, North America, Latin America (including Mexico), Sub-Saharan Africa, Middle East and North Africa, Asia, and Oceania. We recorded the authors’ academic discipline based on their PhD sub- ject area, as ecology and conservation biology, biological sciences (other than ecology and conservation biology), physical sciences, humanities, social sciences (excluding economics), economics, and engineering. We collected data on both past and current employment institutions, including name and country, as well as participation in international research initiatives, such as IPBES. Authors for whom we could not locate data on their PhD country, PhD region or PhD discipline were treated as missing data (recorded as ‘no data’ in the results, below). In the case of 23 authors we were unable to locate a complete history of post-PhD employment institutions. To examine co- authorship patterns, we identified the number of publica- tions that each of the 401 authors had written with others from within the sample of 401 authors. We also classified the outlets where the articles of the primary search had been published and ranked these in terms of occurrences and the total number of citations received by the articles of each outlet (Supplementary Material 1). We used Ucinet6 (Borgatti et al., 2002) and Netdraw
(Borgatti, 2002) to examine how the 401 authors collabo- rated with each other, and which institutions and career pathways the authors shared. We calculated four network- level measures (Table 1), examining the level of cohesion or fragmentation and the existence of leaders in terms of connectivity (Borgatti et al., 2009). We also calculated two
individual-level centrality measures, widely recognized as reliable indicators of prestige: degree centrality (Wasserman & Faust, 1994) and brokering capability (betweenness cen- trality; Burt et al., 2013). In social network theory, nodes with high degree centrality in the network are those with a high number of ties and that are key in mobilizing the net- work and bringing other nodes together. Nodes with high betweenness centrality are those thatmore frequently bridge across two other nodes. Here, authors with high degree cen- trality represent those who have more connections with other authors in the network (e.g. in terms of shared publi- cations), and institutions with high betweenness centrality are those that more often connect two other institutions through the authors’ career pathways. These authors and institutions can be considered as important individuals and places in terms of knowledge production, circulation and dissemination, and in the formation of epistemic commu- nities (Phelps et al., 2012). We developed three types of network: the co-authoring network of the 401 authors, by gender; the co-authoring network of the 30 highest-ranked authors in terms of the total citations to their papers in the primary search sample, by gender and employment region; and the network of the 30 institutions thatmore often act as key bridges in the authors’ career pathways, by betweenness score (Supplementary Material 1).
Results
Authors' publishing outlets, disciplines and institutional backgrounds
The total sample of searched articles shows an exponential growth in publication volume, particularly from 2009 onwards (Fig. 1). These articles have been published in a
Oryx, 2021, 55(6), 868–877 © The Author(s), 2021. Published by Cambridge University Press on behalf of Fauna & Flora International doi:10.1017/S0030605320000940
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