** A significant gap exists in the systematic exploration of ethical frameworks and regulatory implications surrounding large language models, particularly concerning their deployment in sensitive areas such as healthcare and education. Additionally, studies centered on enhancing transparency and interpretability of these models in practical applications remain underexplored.
2. **
THE OPPORTUNITY
** The combination of high publication activity and available job roles indicates a robust and competitive landscape for researchers, suggesting both a growing demand for innovative solutions and the potential for impactful contributions. New entrants have the opportunity to carve out unique niches by addressing underexplored areas or contributing to interdisciplinary applications of large language models.
3. **
Develop methodologies for evaluating the ethical implications of deploying large language models in healthcare settings, focusing on informed consent and data privacy.
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Investigate techniques for enhancing the interpretability of large language models in educational applications to improve trust and user engagement among educators and students.
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Create frameworks for the integration of large language models with human feedback mechanisms that prioritize user input in order to improve model performance and usability in real-time applications.
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DISCLOSURE:This paper presents the author's own original philosophical framework, refined through hudreds of iterative exchanges and adversarial critiques, with the author directing each stage of revision. The final text was generated with the assistance of Large Language Models, under the author's direct supervision. Every substantive idea, argument, and synthesis is the author's alone.Constraint...
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========================================ZENODO RECORD UPDATE======================================== Title:When the Machine Is Not Enough: An Autoethnography of AI-Assisted Amateur Research and the Boundaries of Epistemic Authority Description:Replication dataset for a manuscript submitted to AI & Society. This deposit contains the analysis code, coded datasets, and tone classification results sup...
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The full abstract for this thesis is available in the body of the thesis, and will be available when the embargo expires.
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Do heritage-making projects resist or advance gentrification in Southeast Asia? Like other Global South cities, contested urbanisms chequer Jakarta’s postcolonial urban landscape. Competing ideas about urban development manifest in various ways of seeing and producing the city, as demonstrated by evictions, revitalisation projects, and informal housing. Increased evictions of urban villages (urban...
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Student motivation is a well-established predictor of academic engagement and achievement. Despite its importance, motivation is difficult to assess accurately, as it is shaped by multiple, overlapping constructs and contextual factors. This complexity continues to pose challenges for researchers and practitioners seeking measurement tools with valid and reliable scores. While open-ended responses...
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This dissertation presents a computational framework for analyzing media framing through event-based methods, addressing limitations of traditional topic-level classification approaches that fail to capture the nuanced mechanisms by which news sources construct divergent narratives. The research has been organized around four phases, each contributing novel datasets, models, and analytical tools. ...
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This study examined the impact of portfolio assessment on evaluating the English language skills of pupils with hearing impairment in Fako Division, Cameroon. Portfolio assessment, as an informal and learner-centred approach, was explored within the framework of inclusive education, where traditional assessment methods often fail to adequately reflect the abilities of learners with hearing loss. T...
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Static moral question-answering benchmarks do not test whether a model's decision distribution remains stable when the same dilemma is rephrased without changing the underlying facts. This paper introduces Moral Consistency Variance (MCV), a pilot benchmark metric that measures the average Kullback-Leibler divergence between a baseline binary decision distribution and the distributions induced by ...