Security governance and networks: New theoretical perspectives in transatlantic security

The end of the Cold War has not only witnessed the rise of new transnational threats such as terrorism, crime, proliferation and civil war; it has also seen the growing role of non-state actors in the provision of security in Europe and North America. Two concepts in particular have been used to describe these transformations: security governance and networks. However, the differences and potential theoretical utility of these two concepts for the study of contemporary security have so far been under-examined. This article seeks to address this gap. It proposes that security governance can help to explain the transformation of Cold War security structures, whereas network analysis is particularly useful for understanding the relations and interactions between public and private actors in the making and implementation of national and international security policies

Stratifying comatose postanoxic patients for somatosensory evoked potentials using routine EEG

Introduction: Multimodal neurological prognostication is recommended for comatose patients after cardiac arrest. The absence of cortical N20-potentials in a somatosensory evoked potential (SSEP) examination reliably predicts poor outcome, but presence of N20-potentials have limited prognostic value. A benign routine electroencephalogram (EEG) may identify patients with a favourable prognosis who are likely to have present N20-potentials. Objective: To investigate whether a routine EEG can identify patients where SSEP is unnecessary to perform. Methods: In a multi-centre trial, comatose patients after cardiac arrest were randomised to a controlled temperature of 33 °C or 36 °C. A routine EEG was protocolised and SSEP performed at the clinicians’ discretion, both during normothermic conditions. EEGs were categorised into benign, malignant or highly malignant based on standardised terminology. A benign EEG was defined as a continuous normal-voltage background without abundant discharges. The N20-potentials were reported as absent (bilaterally) or present (bilaterally or unilaterally). Results: Both EEG and SSEP were performed in 161 patients. EEG was performed before SSEP in 60%. A benign EEG was seen in 29 patients and 100% (CI 88–100%) had present N20-potentials. For the 69 patients with a malignant EEG and the 63 patients with a highly malignant EEG, 67% (CI 55–77%) and 44% (CI 33–57%) had present N20-potentials, respectively. Conclusions: All patients with a benign EEG had present N20-potentials, suggesting that SSEP may be omitted in these patients to save resources. SSEP is useful in patients with a malignant or highly malignant EEG since these patterns are associated with both present and absent N20-potentials

A Principal Component Logistic Analysis of the Mobility Decision in Transitional Neighborhoods

This study represents an extension of the literature that examines the factors affecting a household's decision to make an intrametropoli-tan move by emphasizing the importance of neighborhood characteristics in addition to the traditional life-cycle variables on the decision to move. Because of the dichotomous nature of the dependent variable and the collinearity among the independent variables, we employ both principal component and logit analysis. The primary data base is drawn from a sample of households moving into and out of two areas in St. Louis.The results indicate that many of the traditional life-cycle variables are significant, although some behave differently than in the usual case because of the transitional nature of the neighborhoods we examine. The results also suggest that a household's perceptions regarding the quality of the neighborhood are also important determinants of mobility. Finally, when the maximum likelihood logit analysis results are compared with the principal component logit results, we find that the principal component logit technique performs better in almost all instances. Copyright American Real Estate and Urban Economics Association.

Explaining socio-spatial patterns in South-East Queensland, Australia: Social homophily versus structural homophily

Model simulations of residential segregation have shown that even modest levels of social homophily (or wishing to live near residents with similar social characteristics) gives rise to distinct spatial patterns of residential segregation. However, this proposition has been contested where social homophily is modest. This paper contrasts two explanations for urban sociospatial patterns (socio-economic and demographic spatial patterns) in a region where social homophily is modest - South East Queensland (SEQ). The research question is whether sociospatial patterns are better explained by social homophily or by structural homophily. In other words, are they better explained by residents wishing to live in neighborhoods with similar people (social homophily), or by residents with similar social characteristics finding similar neighborhood physical attributes important, and thus moving to neighborhoods with similar people (structural homophily). SEQ residents were asked how important various reasons were in choosing their neighborhood. The survey data were linked to neighborhood social characteristics from census data with the aid of geographic information systems. Six neighborhood social characteristics in SEQ were investigated. Social homophily explained a small, though statistically significant, level of spatial variation in socioeconomic and ethnic (non-Western) environments. However, it did not explain any variation in the other four neighborhood social characteristics which related to household structure: that is, younger nonnuclear household environments; nuclear family environments; and older nonnuclear household environments, or disadvantaged environments. Moreover, structural homophily explained much more variation than did social homophily in all six neighborhood social characteristics. In regions such as SEQ, spatial patterns can largely be explained by structural homophily. Thus, modest levels of social homophily are not necessarily important in explaining sociospatial patterning