Robert Raeside

Workplace learning and employee‐led innovation are related. For example, mistakes made when learning may spur innovation. Investigated in this paper is the role of information literacy in the learning of innovative work behaviour in the workplace, and the associated information behaviours that allow for innovative work behaviour to develop. Thus, interactions between people, information and innovation are a main focus. The findings derive from analysis of data generated in twelve semi‐structured interviews conducted within a Finnish organisation. Employee perceptions on the role of information in the workplace, and its role in supporting the learning of innovative work behaviour, are explored. The analysis reveals that: (1) information literacy skills serve as a prerequisite for workplace learning; (2) information behaviours support the learning of innovative work behaviour and; (3) a variety of information sources support employees as they learn to behave innovatively.

A workforce mapping project was carried out in the UK between August 2014 and October 2015. It was commissioned by the Chartered Institute of Library and Information Professionals (CILIP) and the Archives and Records Association (ARA) to enhance understanding of the nation's workforce in Library, Archives, Records, Information Management, Knowledge Management and related professional roles. Based on the statistical analysis of secondary data sources such as the UK Labour Force Survey , as well as responses to an online survey, a long‐needed data baseline was produced by a project team of six from Edinburgh Napier University. Key findings relate to an estimated population of 86,376 workers, their general demographics, qualifications and memberships and the diversity of the population as a whole. Of particular interest are the findings on pay differences and seniority according to gender, and the low ethnic diversity of the population surveyed.

Aims and objectives.  The aim of this paper is to raise the awareness of social network analysis as a method to facilitate research in nursing research. Background.  The application of social network analysis in assessing network properties has allowed greater insight to be gained in many areas including sociology, politics, business organisation and health care. However, the use of social networks in nursing has not received sufficient attention. Design.  Review of literature and illustration of the application of the method of social network analysis using research examples. Methods.  First, the value of social networks will be discussed. Then by using illustrative examples, the value of social network analysis to nursing will be demonstrated. Results.  The method of social network analysis is found to give greater insights into social situations involving interactions between individuals and has particular application to the study of interactions between nurses and between nurses and patients and other actors. Conclusion.  Social networks are systems in which people interact. Two quantitative techniques help our understanding of these networks. The first is visualisation of the network. The second is centrality. Individuals with high centrality are key communicators in a network. Relevance to clinical practice.  Applying social network analysis to nursing provides a simple method that helps gain an understanding of human interaction and how this might influence various health outcomes. It allows influential individuals (actors) to be identified. Their influence on the formation of social norms and communication can determine the extent to which new interventions or ways of thinking are accepted by a group. Thus, working with key individuals in a network could be critical to the success and sustainability of an intervention. Social network analysis can also help to assess the effectiveness of such interventions for the recipient and the service provider.

The purpose of this paper was to explore group drug taking behaviour in a slum area of Dhaka, Bangladesh. We set out to examine the relationships between those who met, at least weekly, to take illegal drugs together, and how these relationships might shape their drug behaviour. Sociometric and behavioural data were collected using questionnaires via semi-structured interviews. We found that the likelihood of injecting drugs and sharing needles increased with age, duration of group membership and length of drug use. Drug users were classified into two clusters: one was more cohesive and comprised longer-term users, who were more likely to inject drugs and had poorer physical and mental health. The other cluster comprised younger, better educated members who were more transient, less cohesive, less likely to inject drugs and had better health. Qualitative data suggested that members of the first cluster were less accepting of outsiders and confirmed more to group norms. We conclude that emotionally bonded cohesive subgroups acquire norms, which reinforce problematic drug-using behaviour. Thus, health initiatives need to consider group relationships and norms and those initiatives which work with networks may be more effective and more appropriate for low-income countries.

This article explores the characteristics, destinations and progression routes of early school leavers – specifically ‘exceptional entry winter leavers’ – in Scotland. Exceptional entry allows students to enter college in the term before their statutory school leaving date – such young people attend college while formally remaining the responsibility of their school. Such arrangements represent an innovative model of supporting transitions to further education among a specific, potentially vulnerable client group, while also offering lessons for the development of school–college collaboration in other areas. Based on an analysis of official data, new survey research with schools and colleges, and in‐depth case studies, this article identifies how schools and colleges work in partnership to support these early school leavers. We find that schools and colleges have developed a range of innovative approaches to engaging with winter leavers, and that the majority complete their programmes or achieve other positive end‐of‐year outcomes. However, the most disadvantaged young people remain least likely to progress. The article concludes by identifying lessons for good practice in school–college partnership‐working and considering implications for policies to prevent young people from finding themselves not in employment, education or training.

Background  Child deaths are decreasing throughout South East Asia, yet the rate remains high and is a cause of considerable anguish. In Bangladesh, there is also a great deal of variation in child mortality between different regions.Method  Reported in this paper is the analysis of a survey of 613 Bangladeshi women who live in six rural villages and have reported on their experience of child death. Factors obtained from an interview based questionnaire were investigated to ascertain their association with child death. Multilevel Poison regression models were developed to relate these factors to the number and proportion of child deaths to children ever born while allowing for variation between the villages.Results  It was found that communicative action, especially women's power as the degree of social connectedness, is important in reducing child mortality. Also important in reducing child mortality is the level of women's education. No evidence could be found of sex preference when comparing male and female child deaths.

Several models have been created over the years that are used in simulation packages to predict pedestrian speed and flow on sidewalks. However, the predictive power of these models has been weak. In this paper the results of a modeling exercise in the United Kingdom is reported. A number of video surveys of pedestrian movement on sidewalks, which are representative of different levels of service, have been made. These videos have been analyzed to yield data on pedestrian flows and speeds and a variety of other variables. From this data regression models have been constructed and the predictive performance of these models assessed and found to perform reasonably well. The value of the models to designers is then discussed.