Global research collaboration: the UKIERI India-UK initiative – lessons from practice for sustainable international partnerships

As knowledge development is claimed to underpin the development of globalisation, interest in research collaboration and its internationalisation has become more widespread. This paper looks at the motivations behind, and development of, higher educational collaborations with a focus on research collaboration, and also compares some of the key issues surrounding academic collaborations. It employs current thinking on strategic alliances and in particular on social network and social capital theories to judge how collaborations can best be encouraged and managed. The paper uses the specific case of India-UK relationship as an example and looks at the context and motivation for collaboration in these two countries. It presents the UK India Education and Research Initiative (UKIERI) and reviews how this initiative deals with the issues discussed by current writers in relation to collaboration, as well as drawing lessons from the initiative for research collaboration more widely.

ReaderBench: An Integrated Cohesion-Centered Framework

Dascalu, M., Stavarache, L.L., Dessus, P., Trausan-Matu, S., McNamara, D.S., & Bianco, M. (2015). ReaderBench: An Integrated Cohesion-Centered Framework. In G. Conole, T. Klobucar, C. Rensing, J. Konert & É. Lavoué (Eds.), 10th European Conf. on Technology Enhanced Learning (pp. 505–508). Toledo, Spain: Springer.

Recent advances in the analysis of behavioural organization and interpretation as indicators of animal welfare

While the incorporation of mathematical and engineering methods has greatly advanced in other areas of the life sciences, they have been under-utilized in the field of animal welfare. Exceptions are beginning to emerge and share a common motivation to quantify 'hidden' aspects in the structure of the behaviour of an individual, or group of animals. Such analyses have the potential to quantify behavioural markers of pain and stress and quantify abnormal behaviour objectively. This review seeks to explore the scope of such analytical methods as behavioural indicators of welfare. We outline four classes of analyses that can be used to quantify aspects of behavioural organization. The underlying principles, possible applications and limitations are described for: fractal analysis, temporal methods, social network analysis, and agent-based modelling and simulation. We hope to encourage further application of analyses of behavioural organization by highlighting potential applications in the assessment of animal welfare, and increasing awareness of the scope for the development of new mathematical methods in this area.

Mass media and polarisation processes in the bounded confidence model of opinion dynamics

This paper presents a social simulation in which we add an additional layer of mass media communication to the social network 'bounded confidence' model of Deffuant et al (2000). A population of agents on a lattice with continuous opinions and bounded confidence adjust their opinions on the basis of binary social network interactions between neighbours or communication with a fixed opinion. There are two mechanisms for interaction. 'Social interaction' occurs between neighbours on a lattice and 'mass communication' adjusts opinions based on an agent interacting with a fixed opinion. Two new variables are added, polarisation: the degree to which two mass media opinions differ, and broadcast ratio: the number of social interactions for each mass media communication. Four dynamical regimes are observed, fragmented, double extreme convergence, a state of persistent opinion exchange leading to single extreme convergence and a disordered state. Double extreme convergence is found where agents are less willing to change opinion and mass media communications are common or where there is moderate willingness to change opinion and a high frequency of mass media communications. Single extreme convergence is found where there is moderate willingness to change opinion and a lower frequency of mass media communication. A period of persistent opinion exchange precedes single extreme convergence, it is characterized by the formation of two opposing groups of opinion separated by a gradient of opinion exchange. With even very low frequencies of mass media communications this results in a move to central opinions followed by a global drift to one extreme as one of the opposing groups of opinion dominates. A similar pattern of findings is observed for Neumann and Moore neighbourhoods.

Impulsivity as a predictor of newly diagnosed depression

Depression is a severe mental disorder, whose onset has been related to environmental, genetic and personality factors. This study examined the association between impulsivity and incidence of depression. Logistic regression models were related to prospective data from two surveys (2-year time lag) conducted in a large cohort of hospital employees (N = 4,505). Only respondents with no history of depression at baseline were included. Impulsivity was predictive of the onset of depression (OR = 1.95, CI 95% = 1.28-2.97) after adjustment for age, sex and education. This association remained statistically significant after additional adjustment for a variety of baseline characteristics, such as smoking, alcohol consumption, and size of social network. A measure of mental distress (GHQ-12 responses), which may serve as a proxy measure for undiagnosed depression, was also associated with impulsivity. Impulsivity appears to be a distinct personality factor that may contribute to the onset of depressive illness in adults.

The level playing field: the impact of assessment practice on professional development

Context: The effects of assessment practice on students’ learning are unclear, particularly regarding professional development. Corralling in objective structured clinical examinations (OSCEs) is designed to reduce illicit passing of examination information. Candidates completing an examination are kept secluded until the next cohort of examinees has begun. We used the introduction of corralling as a context in which to explore social influences on examination misconduct, with the aims of improving understanding of the hidden effects of assessment, and evaluating the acceptability of corralling from the student perspective.

Methods: A questionnaire was administered to students corralled post-OSCE for the first time. Eleven semi-structured interviews were subsequently conducted. Questionnaire data were analysed for descriptive statistics and thematic analysis of interview transcripts was carried out.

Results: The questionnaire response rate was 95.4% (251/263). Before corralling, 80.9% (203/251) of students were aware of the sharing of information among peers and 78.5% (197/251) agreed that such misconduct was unprofessional. The majority were in favour of corralling (90.8%, 228/251). Four themes emerged from the semi-structured interviews: the student network versus the individual; assessment-driven culture; the deferring of professionalism, and the ‘level playing field’. Students saw interaction within the student network, on a background of assessment-driven culture, as the key driver in examination misconduct. Conforming to the rules of the social network was prioritised over individual agency, although the mismatch between the rules of the network and the dominant professional discourse caused some conflict for individuals. Deferred professionalism (described as the practice of taking on the norms of professional behaviour only when qualified) was a rationalisation used to minimise this conflict. Corralling provided a ‘level playing field’ in which the influences of the network were minimised.

Conclusions: Examination misconduct is thus a complex social construction with implications for individual learners in terms of professional development. Corralling is one mechanism for addressing misconduct that is acceptable to students, but assessment processes have important hidden effects which educators should acknowledge.

Do hens have friends?

Recent interest in positive welfare has encouraged consideration of the formation of socio-positive relationships in farmed species which may provide a means by which to manage positive states. We investigated in detail the existence of dyadic preferential associations in small groups of domestic laying hens. Spatial and temporal associations were examined in two contexts (day activity and evening roosting), within 8 identical pens of 15 laying hens over 8 weeks. Little aggression was observed. Social network analysis was performed to investigate correlations in who associated with whom using weighted degree (number) and binary (presence or absence) data for shared resource areas and proximity to other individuals. No consistent evidence was found for hens actively preferring others in their choice of resource area, or in companion proximity. Perch-roosting positions chosen by the hens were compared with data generated from a random-choice model. Hens showed no position preferences. Most dyads were never observed roosting together and, although some apparently perched together frequently, the low number of nights perching and proportion of nights spent together indicates these findings should be interpreted with caution. Overall, we found no convincing evidence of dyadic preferential relationships expressed by close active and resting proximities. Further work is required to confirm whether these findings hold true in other experimental contexts, are affected by social experience and if they hold in common with the progenitor sub-species. © 2012 Elsevier B.V.

Evaluating the effectiveness of community-based dementia care networks:The Dementia Care Networks' Study

Purpose: The Dementia Care Networks' Study examined the effectiveness of four community-based, not-for-profit dementia networks. The study involved assessing the relationship between the types of administrative and service-delivery exchanges that occurred among the networked agencies and the network members' perception of the effectiveness of these exchanges. Design and Methods: With the use of a case-study method, the evolution, structure, and processes of each network were documented. Social network analysis using a standardized questionnaire completed by member agencies identified patterns of administrative and clinical exchanges among networked agencies. Results: Differences were found between the four networks in terms of their perceptions of service-delivery effectiveness; perceptions of administrative effectiveness did not factor significantly. Exchanges between groups of agencies (cliques) within each of the four networks were found to be more critical than those between individual agencies within each network. Implications: Integration-measured by the types of exchanges within as opposed to across networks-differentiated the four networks studied. This research contributes to our understanding of the use of multiple measures to evaluate the inner workings of service delivery and their impact on elder health and elder health care. Copyright 2005 by The Gerontological Society of America.

Improving Patient Safety Through Formal and Informal Learning Networks

This paper explores a novel perspective on patient safety improvements, which draws on
contemporary social network and learning theories. A case study was conducted at a Portuguese
acute university hospital. Data collection followed a staged approach, whereby 46 interviews
were conducted involving 49 respondents from a broad array of departments and professional
backgrounds. This case study highlights the importance of two major interlinked factors in
contributing to patient safety improvements. The first of these is the crucial role of formal and
informal, internal and external social networks. The second is the importance and the possible
advantage of combining formal and informal learning. The analysis suggests that initiatives
rooted in formal learning approaches alone do not necessarily lead to the creation of long-term
grounded internal safety networks, and that patient safety improvements can crucially depend on
bottom-up initiatives of communities of practice and informal learning. Traditional research on
patient safety places a strong emphasis on top-down and managerialist approaches and is often
based on the assumption that „safety? learning is primarily formal and context-independent. This
paper suggests that bottom-up initiatives and a combination of formal and informal learning can
make a major contribute to patient safety improvements.

Location-Awareness for Radios and Networks: Part I

The papers in this special issue focus on the topic of location awareness for radio and networks. Localization-awareness using radio signals stands to revolutionize the fields of navigation and communication engineering. It can be utilized to great effect in the next generation of cellular networks, mining applications, health-care monitoring, transportation and intelligent highways, multi-robot applications, first responders operations, military applications, factory automation, building and environmental controls, cognitive wireless networks, commercial and social network applications, and smart spaces. A multitude of technologies can be used in location-aware radios and networks, including GNSS, RFID, cellular, UWB, WLAN, Bluetooth, cooperative localization, indoor GPS, device-free localization, IR, Radar, and UHF. The performances of these technologies are measured by their accuracy, precision, complexity, robustness, scalability, and cost. Given the many application scenarios across different disciplines, there is a clear need for a broad, up-to-date and cogent treatment of radio-based location awareness. This special issue aims to provide a comprehensive overview of the state-of-the-art in technology, regulation, and theory. It also presents a holistic view of research challenges and opportunities in the emerging areas of localization.

This is Abuse… Or is it? Domestic abuse perpetrators’ responses to anti-domestic violence publicity

Social marketing has become a key component of policy initiatives aimed at reducing the incidence of domestic abuse. However, its efficacy remains debated, with most measures of effectiveness being somewhat crude. More subtle effects of social marketing, such as the boomerang effect whereby the message engenders the opposite effect to that intended, have been detected, suggesting a need for modes of analysis sensitive to the multiple ways in which viewers react to social opprobrium. This article attempts to deliver just this. It begins with a short history and critique of the concept of social marketing. It then proceeds to explore the utility of the more complex notion that viewers often identify with the subject positions thrown open by social marketing on a quite temporary basis, before reconfiguring them. Using the responses of domestic abuse perpetrators exposed to the UK Government’s This is Abuse campaign film, the article shows how contradictory identifications with both anti-violence messages and victim-blaming discourses are negotiated by those young men prone to perpetrating domestic abuse. The article concludes by exploring how effectiveness might be better conceptualised and assessed with regard to the impact of anti-violence social marketing that speaks to domestic abuse perpetrators.

Finding Relevant Tweets

When a user of a microblogging site authors a microblog
post or browses through a microblog post, it provides cues as to what
topic she is interested in at that point in time. Example-based search
that retrieves similar tweets given one exemplary tweet, such as the one
just authored, can help provide the user with relevant content. We investigate
various components of microblog posts, such as the associated
timestamp, author’s social network, and the content of the post, and
develop approaches that harness such factors in finding relevant tweets
given a query tweet. An empirical analysis of such techniques on real
world twitter-data is then presented to quantify the utility of the various
factors in assessing tweet relevance. We observe that content-wise similar
tweets that also contain extra information not already present in the
query, are perceived as useful. We then develop a composite technique
that combines the various approaches by scoring tweets using a dynamic
query-specific linear combination of separate techniques. An empirical
evaluation establishes the effectiveness of the composite technique, and
that it outperforms each of its constituents.

Inferring and Exploiting Categories for Next Location Prediction

Predicting the next location of a user based on their previous visiting pattern is one of the primary tasks over data from location based social networks (LBSNs) such as Foursquare. Many different aspects of these so-called “check-in” profiles of a user have been made use of in this task, including spatial and temporal information of check-ins as well as the social network information of the user. Building more sophisticated prediction models by enriching these check-in data by combining them with information from other sources is challenging due to the limited data that these LBSNs expose due to privacy concerns. In this paper, we propose a framework to use the location data from LBSNs, combine it with the data from maps for associating a set of venue categories with these locations. For example, if the user is found to be checking in at a mall that has cafes, cinemas and restaurants according to the map, all these information is associated. This category information is then leveraged to predict the next checkin location by the user. Our experiments with publicly available check-in dataset show that this approach improves on the state-of-the-art methods for location prediction.

A compendium of modelling techniques

This Integration Insight provides a brief overview of the most popular modelling techniques used to analyse complex real-world problems, as well as some less popular but highly relevant techniques. The modelling methods are divided into three categories, with each encompassing a number of methods, as follows: 1) Qualitative Aggregate Models (Soft Systems Methodology, Concept Maps and Mind Mapping, Scenario Planning, Causal (Loop) Diagrams), 2) Quantitative Aggregate Models (Function fitting and Regression, Bayesian Nets, System of differential equations / Dynamical systems, System Dynamics, Evolutionary Algorithms) and 3) Individual Oriented Models (Cellular Automata, Microsimulation, Agent Based Models, Discrete Event Simulation, Social Network
Analysis). Each technique is broadly described with example uses, key attributes and reference material.