When community change theory meets practice: Exploring some of the challenges to information sharing networks for community change

Networked community change (NCC) efforts focus on building and supporting networks of stakeholders in communities to address complex problems, with a particular focus on tie formation among stakeholders and organizer facilitation of an information-sharing network (Lawlor & Neal, 2016). NCC approaches include, for example, systemic action research (Burns, 2007), Collective Impact (Kania & Kramer, 2011), and network action research (Foth, 2006) and can be understood as community-level interventions supporting change (Bess, 2015). Previous research demonstrates the promising nature of NCC efforts under ideal circumstances for efficient information sharing in community change efforts. However, these efforts frequently operate in non-ideal conditions, needing to adapt to a variety of community challenges. This article extends the agent-based simulation model presented in Lawlor and Neal (2016) to reflect the challenges that arise when stakeholders implement these approaches to community change and identify how they can impact information-sharing networks. First, we review literature to establish common challenges that arise in these efforts. Second, we employ the Lawlor and Neal (2016) model to examine these challenges and report on the resulting structure of the information-sharing networks that emerge from implementing them in the simulation model. We conclude with implications of common networked community change challenges on network formation and future directions for addressing these real-world challenges as communities work on complex problems.

Assessing information-sharing networks within small-scale fisheries and the implications for conservation interventions

The effectiveness of behavioural interventions in conservation often depends on local resource users' underlying social interactions. However, it remains unclear to what extent differences in related topics of information shared between resource users can alter network structure—holding implications for information flows and the spread of behaviours. Here, we explore the differences in nine subtopics of fishing information related to the planned expansion of a community co-management scheme aiming to reduce sea turtle bycatch at a small-scale fishery in Peru. We show that the general network structure detailing information sharing about sea turtle bycatch is dissimilar from other fishing information sharing. Specifically, no significant degree assortativity (degree homophily) was identified, and the variance in node eccentricity was lower than expected under our null models. We also demonstrate that patterns of information sharing between fishers related to sea turtle bycatch are more similar to information sharing about fishing regulations, and vessel technology and maintenance, than to information sharing about weather, fishing activity, finances and crew management. Our findings highlight the importance of assessing information-sharing networks in contexts directly relevant to the desired intervention and demonstrate the identification of social contexts that might be more or less appropriate for information sharing related to planned conservation actions.

Assessing information-sharing networks within small-scale fisheries and the implications for conservation interventions

The effectiveness of biodiversity conservation interventions is often dependent on local resource users' underlying social interactions. However, it remains unclear how fine-scale differences in information shared between resource users can influence network structure and the success of behaviour-change interventions. We investigate this knowledge gap by comparing information-sharing networks in a fishing community in Peru where a trial conservation intervention is underway to reduce the incidental capture of sea turtles (bycatch). We show that the general network structure detailing information sharing about sea turtle bycatch differs from other fishing-related information sharing, specifically in degree assortativity (homophily) and eccentricity. This finding highlights that fine-scale differences in the information shared between resource users may influence network structure.

Assessing information-sharing networks within small-scale fisheries and the implications for conservation interventions

The effectiveness of biodiversity conservation interventions is often dependent on local resource users' underlying social interactions. However, it remains unclear how fine-scale differences in information shared between resource users can influence network structure and the success of behavior-change interventions. Using network null models that incorporate a pre-network data permutation procedure, we compare information-sharing networks in a Peruvian fishing community where a trial conservation intervention is underway to reduce the incidental capture of sea turtles (bycatch). We show that the general network structure detailing information sharing about sea turtle bycatch differs from other fishing-related information sharing, specifically in degree assortativity and eccentricity. This finding highlights the importance of assessing social networks in contexts directly relevant to the desired intervention and that fine-scale differences in the information shared between resource users may influence network structure. Our findings also demonstrate how null model approaches developed in the ecological sciences can elucidate important differences between human networks and identify the social contexts which might be more or less appropriate for information-sharing related to conservation interventions.

Dynamic core periphery structure of information sharing networks in entorhinal cortex and hippocampus

ABSTRACTNeural computation is associated with the emergence, reconfiguration and dissolution of cell assemblies in the context of varying oscillatory states. Here, we describe the complex spatio-temporal dynamics of cell assemblies through temporal network formalism. We use a sliding window approach to extract sequences of networks of information sharing among single units in hippocampus and enthorinal cortex during anesthesia and study how global and node-wise functional connectivity properties evolve along time and as a function of changing global brain state (theta vs slow-wave oscillations). First, we find that information sharing networks display, at any time, a core-periphery structure in which an integrated core of more tightly functionally interconnected units link to more loosely connected network leaves. However the units participating to the core or to the periphery substantially change across time-windows, with units entering and leaving the core in a smooth way. Second, we find that discrete network states can be defined on top of this continuously ongoing liquid core-periphery reorganization. Switching between network states results in a more abrupt modification of the units belonging to the core and is only loosely linked to transitions between global oscillatory states. Third, we characterize different styles of temporal connectivity that cells can exhibit within each state of the sharing network. While inhibitory cells tend to be central, we show that, otherwise, anatomical localization only poorly influences the patterns of temporal connectivity of the different cells. Furthermore, cells can change temporal connectivity style when the network changes state. Altogether, these findings reveal that the sharing of information mediated by the intrinsic dynamics of hippocampal and enthorinal cortex cell assemblies have a rich spatiotemporal structure, which could not have been identified by more conventional time- or state-averaged analyses of functional connectivity.AUTHOR SUMMARYIt is generally thought that computations performed by local brain circuits rely on complex neural processes, associated to the flexible waxing and waning of cell assemblies, i.e. ensemble of cells firing in tight synchrony. Although cell assembly formation is inherently and unavoidably dynamical, it is still common to find studies in which essentially “static” approaches are used to characterize this process. In the present study, we adopt instead a temporal network approach. Avoiding usual time averaging procedures, we reveal that hub neurons are not hardwired but that cells vary smoothly their degree of integration within the assembly core. Furthermore, our temporal network framework enables the definition of alternative possible styles of “hubness”. Some cells may share information with a multitude of other units but only in an intermittent manner, as “activists” in a flash mob. In contrast, some other cells may share information in a steadier manner, as resolute “lobbyists”. Finally, by avoiding averages over pre-imposed states, we show that within each global oscillatory state a rich switching dynamics can take place between a repertoire of many available network states. We thus show that the temporal network framework provides a natural and effective language to rigorously describe the rich spatiotemporal patterns of information sharing instantiated by cell assembly evolution.

Dynamic core-periphery structure of information sharing networks in entorhinal cortex and hippocampus

Neural computation is associated with the emergence, reconfiguration, and dissolution of cell assemblies in the context of varying oscillatory states. Here, we describe the complex spatiotemporal dynamics of cell assemblies through temporal network formalism. We use a sliding window approach to extract sequences of networks of information sharing among single units in hippocampus and entorhinal cortex during anesthesia and study how global and node-wise functional connectivity properties evolve through time and as a function of changing global brain state (theta vs. slow-wave oscillations). First, we find that information sharing networks display, at any time, a core-periphery structure in which an integrated core of more tightly functionally interconnected units links to more loosely connected network leaves. However the units participating to the core or to the periphery substantially change across time windows, with units entering and leaving the core in a smooth way. Second, we find that discrete network states can be defined on top of this continuously ongoing liquid core-periphery reorganization. Switching between network states results in a more abrupt modification of the units belonging to the core and is only loosely linked to transitions between global oscillatory states. Third, we characterize different styles of temporal connectivity that cells can exhibit within each state of the sharing network. While inhibitory cells tend to be central, we show that, otherwise, anatomical localization only poorly influences the patterns of temporal connectivity of the different cells. Furthermore, cells can change temporal connectivity style when the network changes state. Altogether, these findings reveal that the sharing of information mediated by the intrinsic dynamics of hippocampal and entorhinal cortex cell assemblies have a rich spatiotemporal structure, which could not have been identified by more conventional time- or state-averaged analyses of functional connectivity.

Roles of Ego Social Networks for Community Development in Southern Ethiopia: The Case of Tullo Community

This article explores the roles of Ego social networks for community development in the Tullo community of southern Ethiopia. By employing qualitative research methods, data were collected through semi-structured in-depth interviews and participatory mapping. The analysis revealed that social networks contribute to community development as communication channels and forums of information sharing. Networks also provide economic and social support to the members and beyond. Individuals known as Egos loom large in social networks and play a pivotal role in leading the functions of Ego networks for community development. The study draws important lessons about functions of the Ego networks to sustain the peaceful and meaningful life of the studied community.