Saudi Cultural Missions Theses & Dissertations
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Item Restricted “A light was seen to dart from eyes | That mortal never own’d”: Gender and Power Dynamics in Gothic Nuns(University of Sheffield, 2024-08-28) Alharbi, Afnan; Wright, AngelaThis dissertation investigates the representation of ghostly nuns in Gothic literature, examining how these spectral figures reflect and critique the dynamics of gender and power in a patriarchal society. Through an analysis of both fictional and poetic works, this study demonstrates that the figure of the ghostly nun is a powerful symbol of repressed desires, social transgression, and supernatural agency. In Chapter One, the discussion focuses on Matthew Lewis’s The Monk (1796) and Charlotte Brontë’s Villette (1853), highlighting how the spectral nun embodies themes of corruption, forbidden desire, and psychological repression. In The Monk, the bleeding nun represents the consequences of repressed female sexuality and societal transgression, destabilising traditional gender and moral hierarchies. Meanwhile, in Villette, the spectral nun blurs the boundaries between reality and imagination, symbolising the psychological tensions tied to female autonomy and societal constraints. Chapter Two shifts to an exploration of Gothic poetry, focusing specifically on Anne Bannerman’s Tales of Superstition and Chivalry (1802). The analysis covers the poems: ‘The Perjured Nun’, ‘The Dark Ladie’, and ‘The Prophetess of the Oracle of Seam’, revealing how these spectral figures serve as metaphors for patriarchal oppression and the enduring power of suppressed forces. ‘The Perjured Nun’ delves into themes of guilt, retribution, and betrayal, using the ghostly nun to reflect on the consequences of breaking moral and societal codes. While ‘The Dark Ladie’ and ‘The Prophetess of the Oracle of Seam’ do not depict literal nuns, their spectral female figures challenge traditional gender roles, highlighting the tension between submission and rebellion within a patriarchal system. The central argument of this dissertation posits that the ghostly nun is a site of both vulnerability and power, embodying the unresolved anxieties surrounding female autonomy and transgression. By examining a range of Gothic texts—from The Monk and Villette to Bannerman’s poetry—this study demonstrates that the ghostly nun trope serves as a critical space for the Gothic genre’s interrogation of societal norms. Ultimately, the spectral nun emerges as a potent symbol of resistance against patriarchal structures, haunting the boundaries of life, death, and gendered expectations.11 0Item Restricted Inside the Innovation: A Qualitative Study of Challenges Faced by Inventors in Implementing Artificial intelligence (AI) in Healthcare(City, University of London, 2024-04-16) Alharbi, Afnan; Stavropoulou, CharitiniThe potential of Artificial Intelligence (AI) innovations in healthcare to enhance healthcare outcomes and improve efficiency has sparked widespread interest. However, the implementation of AI in healthcare settings has not yet reached its full potential. While studies have explored challenges faced by patients and healthcare professionals in adopting AI, there is a gap in understanding the challenges and facilitators experienced by inventors when implementing AI innovations into the healthcare industry. Employing a pragmatic qualitative design, this research uses semi-structured interviews with professionals at a start-up healthcare technology company. We used thematic analysis to analyse the data. Key findings reveal challenges such as physician acceptance, data quality and training, integration with existing systems, as well as financial and resource constraints. The study emphasizes the importance of co-creation and collaboration between AI developers and healthcare professionals to enhance effectiveness and acceptance in these settings. This research adds to a limited literature on AI spread in healthcare by offering insights from inventors' perspectives and emphasizing the need for policy and organizational strategies that promote sustainable implementation of AI in healthcare.107 0