Defending the city

Abstract

In ‘Defending the City’ George Pattison seeks to defend the modern city against the charge — made, for example, by Graham Ward — that it is a merely secular phenomenon. Instead, he argues that, in its essence, it is multi‐dimensional and pluralistic, representing a range of diverse possibilities, creative as well as destructive. Also, the modern city is shown to anticipate the essential features of the postmodern city. The argument is illustrated by references to Pugin's critique of architectural eclecticism, to Dostoevsky's invocation of the fantastical reality of St. Petersburg, to Kierkegaard and to Murnau's film Sunrise. It is claimed that the best Christian response to the city is to defend, not to subvert, its pluralism.     

Short- and long-term stability in organizational networks: Temporal structures of project teams

Network research focuses on patterns of stable relationships, where stability represents the unfolding of social processes over long time frames. We argue that social interactions exhibit important regularities in different time frames (short and long term), reflecting distinct social processes. We illustrate the value of this distinction through a comparative case study of technology-mediated communication, within two project teams in a digital marketing agency. We examine how the embedding of interpersonal interactions in processes of reciprocity and closure over different time horizons enables the emergence of cohesion in the face of constant compositional changes. We propose that the time frames in which stable patterns of interactions develop are the key to understanding the nature of the underlying social processes with short-term patterns of closure and reciprocity representing adaptation to change while longer term patterns indicate cohesion. Our results are supportive of this argument and show that the two teams exhibit the same regularities in interactions but across different time horizons. We discuss the implication of our findings and argue that distinguishing between short- and long-term stability of social networks offers a novel and promising avenue for network research.     

Neighborhood–Based Models For Social Networks

We argue that social networks can be modeled as the outcome of processes that occur in overlapping local regions of the network, termed local social neighborhoods. Each neighborhood is conceived as a possible site of interaction and corresponds to a subset of possible network ties. In this paper, we discuss hypotheses about the form of these neighborhoods, and we present two new and theoretically plausible ways in which neighborhood–based models for networks can be constructed. In the first, we introduce the notion of a setting structure, a directly hypothesized (or observed) set of exogenous constraints on possible neighborhood forms. In the second, we propose higher–order neighborhoods that are generated, in part, by the outcome of interactive network processes themselves. Applications of both approaches to model construction are presented, and the developments are considered within a general conceptual framework of locale for social networks. We show how assumptions about neighborhoods can be cast within a hierarchy of increasingly complex models; these models represent a progressively greater capacity for network processes to "reach" across a network through long cycles or semipaths. We argue that this class of models holds new promise for the development of empirically plausible models for networks and network–based processes.     

Keeping People ‘In the Tent’: Governance in the New Zealand Outdoor Activity Sector

The purpose of this research was to examine governance in the New Zealand outdoor activity sector. We conducted 35 interviews with key personnel from organisations with responsibility for national co-ordination, education, and membership services. Using Brandsen and Pestoff’s (Public Manag Rev 8(4):493–501, 2006) co-processes framework, we describe and analyse governance of the outdoor sector. In so doing, we provide insight into the challenges facing this complex sector with regard to funding and stakeholder relationships, programme delivery, and personality conflicts. We also contribute by highlighting some of the shortcomings of the co-processes model, and offer constructively critical insights for its development.     

Analysing exponential random graph (p-star) models with missing data using Bayesian data augmentation

Missing data are often problematic in social network analysis since what is missing may potentially alter the conclusions about what we have observed as tie-variables need to be interpreted in relation to their local neighbourhood and the global structure. Some ad hoc methods for dealing with missing data in social networks have been proposed but here we consider a model-based approach. We discuss various aspects of fitting exponential family random graph (or p-star) models (ERGMs) to networks with missing data and present a Bayesian data augmentation algorithm for the purpose of estimation. This involves drawing from the full conditional posterior distribution of the parameters, something which is made possible by recently developed algorithms. With ERGMs already having complicated interdependencies, it is particularly important to provide inference that adequately describes the uncertainty, something that the Bayesian approach provides. To the extent that we wish to explore the missing parts of the network, the posterior predictive distributions, immediately available at the termination of the algorithm, are at our disposal, which allows us to explore the distribution of what is missing unconditionally on any particular parameter values. Some important features of treating missing data and of the implementation of the algorithm are illustrated using a well-known collaboration network and a variety of missing data scenarios.     

Reflections on the absence of formal reflection in public relations education and practice

This content analysis is a part of wider research into the value of reflective practice in public relations education and practice. Examination of this topic is important given that reflective practice is widely recognised as an essential element for claims of professionalism (Dewey, 1933; Schön, 1983, 1987), and professionalism remains an elusive goal for PR practitioners (L’Etang, 2009). This article examines the extent to which the terms and processes associated with reflective practice are formally included in the contents of a range of widely used and well regarded public relations textbooks. The aim is to provide insight into the significance (or lack of it) of reflective practice in contemporary public relations curricula. Given that textbooks are highly influential teaching media that both reflect and shape curricula, conclusions about the emphasis of reflective practice in public relations teaching can be drawn as a result of this analysis. The findings indicate that – based on the content of the textbooks analysed – reflective practice is not formally included in the public relations teaching curriculum. Further research is needed to determine whether this omission also reflects the situation in public relations practice. This research has relevance for public relations educators given that they play a significant role in influencing future generations of public relations professionals. It concludes with a call for a shift in public relations education that includes greater emphasis on reflective practice.     

Closure,connectivity and degree distributions: Exponential random graph (p*) models for directed social networks

The new higher order specifications for exponential random graph models introduced by Snijders et al. [Snijders, T.A.B., Pattison, P.E., Robins G.L., Handcock, M., 2006. New specifications for exponential random graph models. Sociological Methodology 36, 99–153] exhibit substantial improvements in model fit compared with the commonly used Markov random graph models. Snijders et al., however, concentrated on non-directed graphs, with only limited extensions to directed graphs. In particular, they presented a transitive closure parameter based on path shortening. In this paper, we explain the theoretical and empirical advantages in generalizing to additional closure effects. We propose three new triadic-based parameters to represent different versions of triadic closure: cyclic effects; transitivity based on shared choices of partners; and transitivity based on shared popularity. We interpret the last two effects as forms of structural homophily, where ties emerge because nodes share a form of localized structural equivalence. We show that, for some datasets, the path shortening parameter is insufficient for practical modeling, whereas the structural homophily parameters can produce useful models with distinctive interpretations. We also introduce corresponding lower order effects for multiple two-path connectivity. We show by example that the in- and out-degree distributions may be better modeled when star-based parameters are supplemented with parameters for the number of isolated nodes, sources (nodes with zero in-degrees) and sinks (nodes with zero out-degrees). Inclusion of a Markov mixed star parameter may also help model the correlation between in- and out-degrees. We select some 50 graph features to be investigated in goodness of fit diagnostics, covering a variety of important network properties including density, reciprocity, geodesic distributions, degree distributions, and various forms of closure. As empirical illustrations, we develop models for two sets of organizational network data: a trust network within a training group, and a work difficulty network within a government instrumentality.     

Pregnancy, work and women's well-being: A review

Pregnancy is potentially a stressful period for working women for ergonomic, psychological and organizational reasons, yet the well-being of women is seldom the focus of research on working during pregnancy. This paper reviews the literature on women's experience of being pregnant at work. It concludes that, while working conditions are usually not well suited to pregnant women, the majority of women encounter only minor difficulties and regard working in a positive way. However, for a minority of women working during pregnancy adversely affects their well-being. These are likely to be women working during pregnancy adversely affects their well-being. These are likely to be women who are most at risk from work-related stress at other times. The literature suggests that working during pregnancy has still to be accepted and accommodated by employers and colleagues.     

Exponential random graph models for multilevel networks

Modern multilevel analysis, whereby outcomes of individuals within groups take into account group membership, has been accompanied by impressive theoretical development (e.g. Kozlowski and Klein, 2000) and sophisticated methodology (e.g. Snijders and Bosker, 2012). But typically the approach assumes that links between groups are non-existent, and interdependence among the individuals derives solely from common group membership. It is not plausible that such groups have no internal structure nor they have no links between each other. Networks provide a more complex representation of interdependence. Drawing on a small but crucial body of existing work, we present a general formulation of a multilevel network structure. We extend exponential random graph models (ERGMs) to multilevel networks, and investigate the properties of the proposed models using simulations which show that even very simple meso effects can create structure at one or both levels. We use an empirical example of a collaboration network about French cancer research elites and their affiliations (0125 and 0120) to demonstrate that a full understanding of the network structure requires the cross-level parameters. We see these as the first steps in a full elaboration for general multilevel network analysis using ERGMs.