Bradford Scholars
Bradford Scholars is the University of Bradford online research archive. Access is free to anyone interested in research being conducted at Bradford. In the repository you will find a range of materials from journal articles and conference papers to research reports and theses.
Contact the repository team via openaccess@bradford.ac.uk with any queries about Open Access or how to deposit your research papers.
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Publication What were the effects of the post-colonial experience of counterinsurgency on UK forces in southern Iraq? Were the lessons absorbed and implemented?(2021)This thesis examines the British army and its legacy of counterinsurgency from the 20th century. It analyses the effects of post-colonial counterinsurgency and the army’s ability to learn from previous counterinsurgency conflicts to create new doctrine from earlier examples that could have had lessons for the UK forces in southern Iraq. Doctrine (both official and unofficial) ranges from endorsed army field manuals to theory written by experts while on defence fellowships. The army’s ability to create new doctrine from previous campaigns lessons and how it is diffused across the armed forces is also assessed. The conflicts used as post-colonial counterinsurgencies scrutinise Oman and Northern Ireland. These two case studies provide mixed lessons, that should advance and expand British counterinsurgency theory and models. The previous historical occurrences of counterinsurgency have created a British approach which has established a four-pillar framework which encompasses minimum force, civil-military co-operation, use of intelligence and tactical flexibility. This approach could identify lessons for a modern British army deployed to Iraq. If lessons and previous outcomes are analysed to create new doctrine, strategy and tactics that encompass the four pillars framework, what went wrong in southern Iraq? Could lessons from earlier campaigns have assisted British efforts?Publication Saturday night and Sunday morning: the 2001 Bradford riot and beyond(2011)Saturday Night and Sunday Morning marks the tenth anniversary of the Bradford riot of Saturday 7 to Sunday 8 July 2001. The day began with a peaceful demonstration against a banned Far Right march but ended in one of the most violent examples of unrest in Britain for 20 years. More than 320 police officers were injured as they battled rioters who hurled missiles and petrol bombs, pushed burning cars towards them and torched buildings. Criminal acts of looting characterised the final hours. Riot damages amounted to GBP7.5 million. In the aftermath, nearly 300 arrests took place and nearly 200 were charged with riot leading to prison sentences of four years or more. Images of the riot, and of a smaller disturbance which followed on one of its traditionally 'white' estates, have haunted Bradford ever since. Nine years later, in August 2010, Bradford faced another Far Right provocation. The English Defence League came in force to demonstrate against Bradford's Muslim population. Bradford braced itself. However this time, Asian lads mostly stayed off the streets and the police worked with the council, communities and local activists to keep order against the threat of violence. Saturday Night and Sunday Morning traces Bradford's journey over the decade, beginning with the voices of rioters, police and others interviewed after the 2001 riot and ending with those of former rioters, citizens, police and politicians following the EDL protest. The authors argue that while 2001 reflected a collective failure of Bradford District to address a social legacy of industrial decline in a multicultural context, 2010 revealed how leadership from above combined with leadership from below restored its confidence and opened up possibilities for a new era in Bradford's history and prospects. Saturday Night and Sunday Morning is written by two authors from the University's renowned Department of Peace Studies who balance research with an active commitment to peace, economic regeneration and social justice in Bradford.Publication Sex talk: Mutuality and power in the shadow of HIV/AIDS in Africa.(University of Bradford, 2007)Bids for mutuality in sexual partnerships are key to AIDS campaigning slogans such as `negotiate¿, `know your partner¿ and `use condoms¿. This paper explores the contradiction between more mutuality in sexual relations and the gender power politics that render such mutuality difficult to achieve in Africa, as well as the caricatures of `African sexuality¿ that have pervaded some of the literature. It looks at the new discourses of sexuality delivered via NGOs and the state as well as the ways in which customary silences about sex are being broken by ordinary people. It asks whether, given the threat of HIV infection, people are talking in new ways about sexual relationships, and how this talk is gendered. It also addresses the challenge to African feminism of sexuality discourses and how these need to be rethought in the context of AIDS. It concludes that the prospect of death by sex is transforming discourses, challenging customary sexual practice and putting gendered inequalities in question.Publication Early Diagnosis and Personalised Treatment: Classification Modelling of Immunotherapy Data Utilising Machine Learning and Deep LearningEarly diagnosis and personalised treatment are emerging in health, due to machine learning and deep learning playing a vital role in the treatment of cancer, infections and immunotherapies. However, immunotherapy faces obstacles as medical data are typically small, imbalanced and contain irrelevant features, resulting in suboptimal classification performance. Therefore, the following contributions are proposed, addressing the data challenges. A comprehensive immunotherapy literature review is presented to uncover gaps in published studies by exploring application domains, datasets, algorithms and software tools. Studies on imbalanced immunotherapy datasets are reproduced to identify gaps in applications. Novel personalised experiments are conducted based on converting original data to artificially big data, to consider the impact on classification evaluating simulations of observations and features, manual classification, visualisations and correlations. Random Forest and Generative Adversarial Network are mainly used for classification and synthetic data generation, respectively, because of their better performance. A visual learning approach is proposed considering data, algorithm and human levels to improve the quality of a dataset relative to the expected classification performance. Numerous experiments including statistical features, cumulative sums, histograms, correlation matrix, mean squared error and principal component analysis are performed comparing visualisations of original and synthetic data. An adaptable synergy between data quality and classification performance is obtained while preserving statistical characteristics. For original and synthetic immunotherapy data, the Random Forest performs best with precision, recall, f-measure, accuracy, sensitivity and specificity.