Southern knowledge online? Climate change research discoverability and communication practices

The networked age promises global digital cultures with flattened power relations, given the affordances of information and communication technologies to collapse distance, enable easier cross-country collaborations and create new opportunities for knowledge production and sharing. In the academic domains, indications are that knowledge patterns continue to reflect physically based geopolitical realities – where knowledge from the South is still peripheral while knowledge from the North still dominates in terms of all the conventional metrics. This study explores the potential role of digital affordances to challenge structural Northern bias and generates questions about knowledge production and dissemination in the climate change knowledge domain. It is framed by the field of scholarly communication within an African setting and by the emergent field of climate change which is fraught with debates and contestations, particularly regarding mitigation and adaptation. It draws on Southern theory which interrogates the global dynamics of knowledge production and dissemination. It explores the intersection of the discoverability and visibility of local climate change research methodologically from the outside in, through an experiment of searches for ‘climate change/South Africa’ and from the inside out by reviewing the online presence of one climate change group in a top-ranked African university.     

The Last Rogue of History: Picaresque Elements in Sasha Sokolov’s Palisandriia

This article takes a detailed look at the way in which the Habsburg Monarchy’s policy towards Serbia subtly shifted between 1881, when the Monarchy forced a secret treaty of alliance on the Serbian government, and the end of the Serbo-Bulgarian War of November 1885. Gustav von Kálnoky, the Austro-Hungarian foreign minister, inherited a policy largely shaped by his Hungarian predecessor, Count Gyula Andrássy, which relied on controlling Serbia through the person of its ruler, the wayward Milan Obrenovi?. The Austrophile and highly unpopular Milan, however, was a disastrous instrument of Austro-Hungarian control, and by the end of the Serbo-Bulgarian conflict, by which point Milan was pleading to be allowed to abdicate, Kálnoky had come to the conclusion that this “personal policy” was a failure, and that the Monarchy was better off relying on the outright coercion of Serbia. The article reconsiders some of the key stages in this development, in particular Andrássy’s memorandum of 24 November 1885, and Kálnoky’s reassessment of the value of the secret treaty of 1881, which depended solely on the guarantee of the Serbian monarch and, as a result, threatened to become worthless without his presence on the throne.     

Vulnerable young people and substance misuse: expanding on the risk and protection‐focused approach using social psychology

This paper critically reviews recent research exploring risk and protective factors for the development of problematic substance use in populations of young people. Specific populations of young people who are most vulnerable to developing problematic patterns of use are identified, and alterations to methods of data collection which would improve the ability of local authorities to monitor these populations and more efficiently target them for early preventative interventions are highlighted. It is argued that social‐psychological research techniques and approaches should be used to complement a risk and protection‐focused approach in order to improve the design and evaluation of interventions, and provide decision‐aids for practitioners when assessing the needs of vulnerable young people. Examples are provided to demonstrate the utility of social psychology in this regard, and the paper concludes with specific recommendations for future research and services. Copyright © 2009 John Wiley & Sons, Ltd.     

Causality and interdependence analysis in linear econometric models with an application to fertility

This paper is an applied analysis of the causal structure of linear multi-equational econometric models. Its aim is to identify the kind of relationships linking the endogenous variables of the model, distinguishing between causal links and feedback loops. The investigation is first carried out within a deterministic framework and then moves on to show how the results may change inside a more realistic stochastic context. The causal analysis is then specifically applied to a linear simultaneous equation model explaining fertility rates. The analysis is carried out by means of a specific RATS programming code designed to show the specific nature of the relationships within the model.     

Totally tall sounds totally younger: Intensification at the socio‐semantics interface

In two social perception experiments, we explore the relationship between the social meaning and the semantic/pragmatic properties of the intensifier totally in American English. In Experiment 1, we show that totally is perceived as a more salient index of social identity categories – measured in terms of Age, Solidarity and Status attributes – when it targets a scalar dimension grounded in the speaker's attitude, as opposed to when it occurs in contexts where the scale is provided by the subsequent predicate. In Experiment 2, we show that the social indexicality of totally is even more salient in contexts in which the intensifier, by virtue of its pragmatic contribution, invites a stance of heightened proximity and convergence between the interlocutors. These results point to a principled connection between the semantic, pragmatic and personality‐based social meanings of totally, providing new insights into the dynamics whereby different layers of meaning conspire to determine what an expression ‘says’ when deployed in interaction.     

‘No,living well does not mean being rich’: Diverse understandings of well-being among 11–13-year-old children in three Ethiopian communities

Participatory research into how people living in material poverty define and experience well-being and ill-being is increasingly common in developed and developing countries. Such research highlights the importance of experiential aspects, such as being respected and able to preserve one's dignity, and having meaningful choices. Nevertheless, these findings rarely cover children's experiences and are often not contextualized or triangulated with other data. The paper will extend this exploration using data from qualitative research with a sub-sample of children aged 11–13 in three urban and rural communities, drawn from Young Lives, a long-term international research project investigating the changing nature of childhood poverty in four countries, including Ethiopia. Firstly, it addresses how understandings of a good life and what is needed to achieve one varies between communities and amongst children of different backgrounds living in those communities; for example, boys and girls and children from richer or poorer households. Secondly, the study examines how one's place in social relationships also contributes to how children perceive and understand what a good life is. The paper confirms the importance of allowing children to take at least a ‘partial role’ in measuring and monitoring their well-being (Ben-Arieh 2005, 575) and provides examples of how this might be done.     

A Comparison of Hierarchical Methods for Clustering Functional Data

Functional data analysis (FDA)—the analysis of data that can be considered a set of observed continuous functions—is an increasingly common class of statistical analysis. One of the most widely used FDA methods is the cluster analysis of functional data; however, little work has been done to compare the performance of clustering methods on functional data. In this article, a simulation study compares the performance of four major hierarchical methods for clustering functional data. The simulated data varied in three ways: the nature of the signal functions (periodic, non periodic, or mixed), the amount of noise added to the signal functions, and the pattern of the true cluster sizes. The Rand index was used to compare the performance of each clustering method. As a secondary goal, clustering methods were also compared when the number of clusters has been misspecified. To illustrate the results, a real set of functional data was clustered where the true clustering structure is believed to be known. Comparing the clustering methods for the real data set confirmed the findings of the simulation. This study yields concrete suggestions to future researchers to determine the best method for clustering their functional data.