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Exploring strategic turnaround in English Local Authorities
This thesis explores the nature of strategic turnaround in English local authorities during the period of Comprehensive Performance Assessment (CPA) between 2002 and 2008. This period was unique in that it allowed the comparative performance of local authorities and their management practices using the holistic performance management framework of the CPA. Specifically, this study focuses on a group of local authorities that were poorly performing at the start of CPA era, but had sustained improved performance by the end. It aims to establish the turnaround approaches adopted by this group of local authorities, the impact of leadership and the extent to which the approaches adopted promoted sustained turnaround. Publicly available CPA information and interviews with senior officers of turnaround councils and government lead officials are used to classify and analyse the changes in strategic processes. The thesis adopts a case study approach within a managerialist perspective and identifies ten approaches to turnaround that can be related to a longitudinal "7Rs"ďż˝ framework adapting the work of Boyne (2004) and others. This has been developed to include Realisation and Reinforcement at either end of the turnaround period.
Realisation is required to kick-start the turnaround process and Reinforcement to embed the organisational changes necessary to sustain improvement over the longer term. Leadership is a key aspect throughout the process, both in terms of introducing new leaders and the adoption of new leadership approaches to support and underpin sustainable organisational improvement. Sustained improvement was found to be achievable by poorly performing councils. The study also concludes that there was a continuing influence of managerialism, originally associated with new public management, throughout the CPA era
Detection and Prevention of Cyberbullying on Social Media
The Internet and social media have undoubtedly improved our abilities to keep in touch with friends and loved ones. Additionally, it has opened up new avenues for journalism, activism, commerce and entertainment. The unbridled ubiquity of social media is, however, not without negative consequences and one such effect is the increased prevalence of cyberbullying and online abuse. While cyberbullying was previously restricted to electronic mail, online forums and text messages, social media has propelled it across the breadth of the Internet, establishing it as one of the main dangers associated with online interactions. Recent advances in deep learning algorithms have progressed the state of the art in natural language processing considerably, and it is now possible to develop Machine Learning (ML) models with an in-depth understanding of written language and utilise them to detect cyberbullying and online abuse. Despite these advances, there is a conspicuous lack of real-world applications for cyberbullying detection and prevention. Scalability; responsiveness; obsolescence; and acceptability are challenges that researchers must overcome to develop robust cyberbullying detection and prevention systems. This research addressed these challenges by developing a novel mobile-based application system for the detection and prevention of cyberbullying and online abuse. The application mitigates obsolescence by using different ML models in a âplug and playâ manner, thus providing a mean to incorporate future classifiers. It uses ground truth provided by the enduser to create a personalised ML model for each user. A new large-scale cyberbullying dataset of over 62K tweets annotated using a taxonomy of different cyberbullying types was created to facilitate the training of the ML models. Additionally, the design incorporated facilities to initiate appropriate actions on behalf of the user when cyberbullying events are detected. To improve the appâs acceptability to the target audience, user-centred design methods were used to discover stakeholdersâ requirements and collaboratively design the mobile app with young people. Overall, the research showed that (a) the cyberbullying dataset sufficiently captures different forms of online abuse to allow the detection of cyberbullying and online abuse; (b) the developed cyberbullying prevention application is highly scalable and responsive and can cope with the demands of modern social media platforms (b) the use of user-centred and participatory design approaches improved the appâs acceptability amongst the target audience