Describing and measuring leadership by applying a social network perspective 4 73 Spillane & Sun, 2020; Tuytens et al., 2019). These earlier studies indicate the promise of utilizing a social network perspective to depict relations and interactions. However, until now distributed leadership is studied less with such a social network perspective and thus D’Innocenzo et al. (2016) recommend, based on their meta-analysis on distributed leadership and team performance, to further explore the utility of other network measures in addition to the most often studied density and centralization to reveal different aspects of distributed leadership. In the current study, each of the three core aspects of distributed leadership that we dissected will be measured with their own social network measure, based on an advice seeking network of teachers and their school principal. Insights from previous studies indicate the potential relevance of the social network measures density and centralization (e.g., Carson et al., 2007; Liou et al., 2014). We recognize these measures to fit the collective and dynamic aspect respectively, and we will study these two measures in our bigger sample of school teams. Furthermore, our second goal is to include the third core aspect, namely relational, and to measure this with the social network measure reciprocity. In this way, we study the relevance of adding another social network measure and the coherence of the three measures. Below we briefly explain how the collective, dynamic, and relational core aspects are captured within the chosen social network measures (for an overview, see Table 4.1). Table 4.1 Overview of our Proposal How to Describe and Measure Distributed Leadership From a Social Network Perspective Aspect of distributed leadership Network Level Network measurement Name Figure Collective Network Density Dynamic Network and individual Centrality Relational Dyadic Reciprocity Firstly, collective describes the extent to which the team members are actively consulting each other, for instance for advice, which represents the cohesiveness of a network. The more team members consult each other, the more advice relationships evolve, which results in a more dense (i.e., cohesive) network (Borgatti et al., 2013). The social network measure density helps to study the collective aspect. It indicates how many ties
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