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Understanding educators' networks can inform the field of school psychology by offering insight into how the structure of social relationships supports the implementation of school-based programs. However, the difficulties of collecting and modeling network data remain barriers to using network methods in school psychology. To overcome these barriers, we provide a step-by-step tutorial for collecting, modeling, and visualizing network data from educators. We draw on an example from a study designed to understand advice networks among middle and high school educators involved in implementing a system-level intervention to prevent school dropout.

Principals' efforts to support the implementation of interventions involve coordination among multiple actors in their social networks. However, less is known about how distinct features of these social networks are associated with principals' perceptions of the social validity of interventions. In this paper, we used Neal and Neal (Implement Sci 14:16, 2019. 10.1186/s13012-019-0860-z) implementation capital framework to test hypotheses about the associations between two features of principals' social networks (i.e., bonding and bridging social capital) and three aspects of social validity (i.e., acceptability, understanding, and feasibility). Specifically, we tested these hypotheses in a statewide representative sample of 180 Michigan secondary school principals supporting the implementation of early warning signs (EWS), a systems-level intervention to prevent student dropout. Consistent with our hypotheses, we found that bonding social capital was positively associated with acceptability and bridging social capital was positively associated with understanding. But, contrary to our hypotheses, bonding and bridging social capital were not associated with feasibility. Drawing on these findings, we discuss future directions for research and practice implications to improve principals' perceptions of the social validity of mental health interventions.

Social cognitive mapping (SCM) is a common approach to identifying peer groups in developmental research. However, this approach involves three stages that each implies a unique conception of peer group. This article aims to bring conceptual clarity to the identification of peer groups using SCM by demonstrating how the meaning of peer groups differs at each stage of SCM. First, in the data collecting stage, interaction groups identify sets of children that hang out together. Second, in the data aggregating stage, co-membership groups identify sets of children who are members of many of the same interaction groups. Third, in the data analyzing stage, similarity groups identify sets of children with similar patterns of relationships with their peers. After reviewing these three conceptions of peer groups, we briefly discuss some potential problems with using SCM as a tool to measure children's social networks and peer groups. Finally, we conclude by arguing that despite these issues, SCM remains a valuable methodology, and indeed one with untapped potential. Thus, we offer suggestions for the appropriate application of these theoretically and empirically distinct conceptions of peer group, noting that developmental researchers using SCM must identify which conception of peer group is used and justify why this conception is the appropriate one. (Contains 1 table and 6 figures.)

As cities develop more and longer‐range external relations, some have challenged the long‐standing notion that population size indicates a city's power in its urban system. But are population size and network centrality really independent properties in practice, or do larger cities tend to be more central in urban networks? To answer this question, we conducted a systematic literature search and meta‐analysed 41 reported correlations between city size and degree centrality. The results show that population size and degree centrality are significantly and positively correlated for cities across various urban systems (r = 0.77), but the correlation varies by network scale and type. The size‐centrality association is weaker for global economic and transportation networks (r = 0.43), and stronger for non‐global social and communication networks (r = 0.91). This clarifies seemingly contradictory predictions in the literature regarding the association betweensize and centrality for cities. [ABSTRACT FROM AUTHOR]

Objective: The overall goal of this work is to produce a set of recommendations (SoNHR–Social Networks in Health Research) that will improve the reporting and dissemination of social network concepts, methods, data, and analytic results within health sciences research. Methods: This study used a modified-Delphi approach for recommendation development consistent with best practices suggested by the EQUATOR health sciences reporting guidelines network. An initial set of 28 reporting recommendations was developed by the author team. A group of 67 (of 147 surveyed) experienced network and health scientists participated in an online feedback survey. They rated the clarity and importance of the individual recommendations, and provided qualitative feedback on the coverage, usability, and dissemination opportunities of the full set of recommendations. After examining the feedback, a final set of 18 recommendations was produced. Results: The final SoNHR reporting guidelines are comprised of 18 recommendations organized within five domains: conceptualization (how study research questions are linked to network conceptions or theories), operationalization (how network science portions of the study are defined and operationalized), data collection & management (how network data are collected and managed), analyses & results (how network results are analyzed, visualized, and reported), and ethics & equity (how network-specific human subjects, equity, and social justice concerns are reported). We also present a set of exemplar published network studies which can be helpful for seeing how to apply the SoNHR recommendations in research papers. Finally, we discuss how different audiences can use these reporting guidelines. Conclusions: These are the first set of formal reporting recommendations of network methods in the health sciences. Consistent with EQUATOR goals, these network reporting recommendations may in time improve the quality, consistency, and replicability of network science across a wide variety of important health research areas. [ABSTRACT FROM AUTHOR]

Networks are useful for representing phenomena in a broad range of domains. Although their ability to represent complexity can be a virtue, it is sometimes useful to focus on a simplified network that contains only the most important edges: the backbone. This paper introduces and demonstrates a substantially expanded version of the backbone package for R, which now provides methods for extracting backbones from weighted networks, weighted bipartite projections, and unweighted networks. For each type of network, fully replicable code is presented first for small toy examples, then for complete empirical examples using transportation, political, and social networks. The paper also demonstrates the implications of several issues of statistical inference that arise in backbone extraction. It concludes by briefly reviewing existing applications of backbone extraction using the backbone package, and future directions for research on network backbone extraction. [ABSTRACT FROM AUTHOR]

• Two-thirds of educators cannot reach a researcher through their social networks. • Educators using itinerant brokerage were 5 times less likely to reach a researcher. • Educators using liaison brokerage were 3.4 times more likely to reach a researcher. • Interventions to narrow the research-practice gap should leverage liaison brokers. The presence of a research-practice gap is recognized across multiple fields including education, psychology, and public health. In this paper, we examine which of five structural types of brokerage are most and least effective in bridging this research-practice gap in the context of education. Using a small world survey design, we tracked how a statewide random sample of 247 K-12 principals and superintendents in Michigan seek information about social skills programs from brokering individuals and organizations. We find that some triadic brokerage structures are more effective than others in closing the communication gap between practitioners and researchers. Specifically, educators relying on itinerant brokerage, which circulates information between members of the same community, were five times less likely to obtain information from a researcher. In contrast, educators relying on representative or liaison brokerage, which facilitate information transfer between members of different communities, were more than twice as likely to obtain information from a researcher. We conclude by discussing implications for the development of interventions designed to facilitate information sharing between practitioners and researchers. [ABSTRACT FROM AUTHOR]

In the March 2014 issue of American Journal of Community Psychology, we published an article that examined the tension between two core values in the field of community psychology: promoting contextual conditions that foster respect for diversity and promoting contextual conditions that foster sense of community. We concluded that processes of social network formation could help explain why diversity and sense of community are seemingly incompatible goals. The study's findings initially disseminated through the usual academic channels, and later through mainstream media outlets. However, they also eventually appeared on blogs and discussion forums devoted to white nationalism. The findings were viewed there as having demonstrated the evils of diversity, and thus having vindicated the white nationalist agenda. As a result, we were forced to consider whether and how to set the record straight. In this first-person narrative, we describe our study's journey from AJCP to white nationalist blogs, discussing how we ultimately responded to the situation, and concluding with some lessons learned. [ABSTRACT FROM AUTHOR]

Over the past couple of years, a debate has played out in the pages of the American Journal of Community Psychology concerning the relationship between two of Community Psychology's core values: promoting diversity and promoting a sense of community. This special section is to continue a discussion about diversity and community, both among the debate's initial contributors (Alex Stivala, Greg Townley, and Zachary Neal), as well as among others whose own work has touched on these issues (Anne Brodsky, Richard Florida, Jean Hill, and Roderick Watts). In this essay, I address some broad questions that have emerged through this discussion. First, because much has been written on the relationship between diversity and community, both in community psychology and in other disciplines, what do we know, or at least think we know? Second, since the constructs of diversity and sense of community are complex and multi-faceted, how can definitions get in the way and how can we avoid talking past one another in this discussion? Finally, looking across the original papers that initiated this discussion, as well as the contributions in this special section, what path(s) forward do we have? [ABSTRACT FROM AUTHOR]

Addressing complex problems in communities has become a key area of focus in recent years (Kania & Kramer, 2013, Stanford Social Innovation Review). Building on existing approaches to understanding and addressing problems, such as action research, several new approaches have emerged that shift the way communities solve problems (e.g., Burns, 2007, Systemic Action Research; Foth, 2006, Action Research, 4, 205; Kania & Kramer, 2011, Stanford Social Innovation Review, 1, 36). Seeking to bring clarity to the emerging literature on community change strategies, this article identifies the common features of the most widespread community change strategies and explores the conditions under which such strategies have the potential to be effective. We identify and describe five common features among the approaches to change. Then, using an agent-based model, we simulate network-building behavior among stakeholders participating in community change efforts using these approaches. We find that the emergent stakeholder networks are efficient when the processes are implemented under ideal conditions. [ABSTRACT FROM AUTHOR]

The implementation of effective community interventions can be challenging for many reasons, including financial and time costs, lack of infrastructure, local contextual variations, and barriers to fidelity. But, prior to all of these is the challenge of limited information exchange between the researchers developing interventions and the practitioners implementing them, or the so-called research-practice gap. In this paper, we use network theory and review a dozen small world experiments to understand the research-practice gap, identifying three key lessons: (1) spatial and social distances are related to the severity of the gap, (2) social boundaries may lead to echo chambers and closed loops, and (3) wider gaps reduce the likelihood of successful information exchange. From these lessons, we recommend that researchers and practitioners should rely on the assistances of information brokers who know people they do not know and who are different from themselves. [ABSTRACT FROM AUTHOR]

The analysis and visualization of weighted networks pose many challenges, which have led to the development of techniques for extracting the network's backbone, a subgraph composed of only the most significant edges. Weighted edges are particularly common in bipartite projections (e.g. networks of co-authorship, co-attendance, co-sponsorship), which are often used as proxies for one-mode networks where direct measurement is impractical or impossible (e.g. networks of collaboration, friendship, alliance). However, extracting the backbone of bipartite projections requires special care. This paper reviews existing methods for extracting the backbone from bipartite projections, and proposes a new method that aims to overcome their limitations. The stochastic degree sequence model (SDSM) involves the construction of empirical edge weight distributions from random bipartite networks with stochastic marginals, and is demonstrated using data on bill sponsorship in the 108th U.S. Senate. The extracted backbone's validity as a network reflecting political alliances and antagonisms is established through comparisons with data on political party affiliations and political ideologies, which offer an empirical ground-truth. The projection and backbone extraction methods discussed in this paper can be performed using the -onemode- command in Stata. [ABSTRACT FROM AUTHOR]

Using social network data, this study examines which features of social and spatial proximity predict self-reported, or 'real,' and peer-reported, or 'inferred,' relationships among 2,695 pairwise combinations of African American second- through fourth-grade students (aged 7-11). Relationships were more likely to exist, and more likely to be inferred to exist by peers, between pairs of children who were the same sex, sat near one another, shared a positive academic orientation, or shared athletic ability. Sex similarity had a dramatically larger effect on peers' inferences about relationships than on self-reported real relationships, suggesting that children overestimate the importance of gender in their inferences about relationships. Results were stable across different grade levels in middle childhood and for boys and girls. [ABSTRACT FROM AUTHOR]

Bronfenbrenner's ecological systems theory ( EST) is among the most widely adopted theoretical frameworks for studying individuals in ecological contexts. In its traditional formulation, different levels of ecological systems are viewed as nested within one another. In this article, we use Simmel's notion of intersecting social circles and Bronfenbrenner's earlier writing on social networks to develop an alternative 'networked' model that instead views ecological systems as an overlapping arrangement of structures, each directly or indirectly connected to the others by the direct and indirect social interactions of their participants. We redefine each of the systems discussed by EST-micro, meso, exo, macro, and chrono-based on patterns of social interaction, and then illustrate how this alternative model might be applied in the classic context of the developing child. We conclude by discussing future directions for how the networked model of EST can be applied as a conceptual framework, arguing that this approach offers developmental researchers with a more precise and flexible way to think about ecological contexts. We also offer some initial suggestions for moving a networked EST model from theory to method. [ABSTRACT FROM AUTHOR]