This article outlines and tackles two inter-related puzzles regarding the comparatively much less robust human rights impact that the ECOWAS Court (in effect, West Africa’s international human rights court) has had on the generally more democratic legislative/judicial branch of decision-making and action in Nigeria vis-à-vis the generally more authoritarian executive branch within Nigeria, the country that is the source of most of the cases filed before the court. The article then discusses and analyzes the examples and extent of the court’s human rights impact on legislative/judicial branch decision-making and action in that key country. This is followed by the development of a set of analytical, multi-factorial, explanations for the two inter-connected puzzles that animate the enquiry in this article. In the end, the article argues that several factors have combined to produce the comparatively much less robust human rights impact that the ECOWAS Court has had on domestic legislative and judicial decision-making, process, and action in Nigeria, through restricting the extent to which the latter could mobilize more robustly the court’s human rights-relevant processes and rulings.
Category: 4/ Fellow”s Projects
Aula Fellow Project
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‘We Condemn the Sin, not the Sinner’: Understanding the Attitudes of Adventist and Baptist Believers in Montenegro towards Sexuality
Although we have seen studies on religion and sexuality in the West come to dominate the relevant scholarship, the postsocialist environment with a predominantly Orthodox population has received less attention. This paper fills the gap by examining the attitudes of Adventist and Baptist believers in Montenegro, with a particular focus on abortion, premarital sexual activities and non-heteronormative sexuality. Because we were dealing with a minority population, we opted for a qualitative methodology and conducted semistructured interviews with 17 Adventist and 15 Baptist believers. As observed, our research participants’ position towards sexuality is closely related to the teachings found in the Bible. However, it is possible to observe certain differences between the two groups; for example, the interviewed Adventists tend to be more conservative than the interviewed Baptists. In addition, the male Adventists seem slightly more liberal than female Adventists, whereas the situation is different among Baptists, where women come across as more liberal than men.
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Advancements in Modern Recommender Systems: Industrial Applications in Social Media, E-commerce, Entertainment, and Beyond
In the current digital era, the proliferation of online content has overwhelmed users with vast amounts of information, necessitating effective filtering mechanisms. Recommender systems have become indispensable in addressing this challenge, tailoring content to individual preferences and significantly enhancing user experience. This paper delves into the latest advancements in recommender systems, analyzing 115 research papers and 10 articles, and dissecting their application across various domains such as e-commerce, entertainment, and social media. We categorize these systems into content-based, collaborative, and hybrid approaches, scrutinizing their methodologies and performance. Despite their transformative impact, recommender systems grapple with persistent issues like scalability, cold-start problems, and data sparsity. Our comprehensive review not only maps the current landscape of recommender system research but also identifies critical gaps and future directions. By offering a detailed analysis of datasets, simulation platforms, and evaluation metrics, we provide a robust foundation for developing next-generation recommender systems poised to deliver more accurate, efficient, and personalized user experiences, inspiring innovative solutions to drive forward the evolution of recommender technology.
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From Crisis Management to the crisis of management: Accountability and Liberal Democracies in the Outbreak of the Covid-19 Pandemic
The outbreak of the COVID-19 pandemic shocked societies around the world. In their efforts to tailor their responses to the crisis to their own conditions for survival, from the outset governments tended to resort to arguments that limited accountability before their populations. Liberal democracies were no exception to this approach. In this context, their leaders used the metaphor of war to describe their position as guarantors of the population’s survival in the face of the new threat. Caught between uncertainty and the need to predict the nature and evolution of the invisible enemy, their responses called into question the political, professional and personal responsibility of leaders. This article offers a reflection on the level of responsibility of governments in liberal democracies in managing the pandemic. During the crisis, decision-makers tended to be driven by the narratives that were most beneficial to them in order to escape their responsibilities, thereby underpinning their short-term political needs through the use of bellicose metaphors, the blame game, competition with other countries, and the dispersion of sources in the decision-making process. This reality now calls for reflection by social actors, including experts, intellectuals and the media, to transcend the prevailing rhetoric in management of the pandemic and the “new normal” that followed, so that the dynamics of constant alterations in the rules of the game and responsibilities can give way, in the future, to a scenario with less arbitrariness and more accountability.
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GenAI and Religion: Creation, Agency, and Meaning
This paper explores the parallels between Generative Artificial Intelligence (GenAI) and religious systems in three domains: creation, agency, and meaning-making. Both offer frameworks for human engagement but differ in intent, autonomy, and moral accountability. Despite these differences, GenAI and religion share roles as creators, influencers, and meaning facilitators. We address and counter rebuttals to these parallels, highlighting GenAI’s co-constructed outputs and its impact on modern meaning-making. The paper concludes with the societal implications of these parallels in shaping future thought and action.
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Generative AI through the Lens of Institutional Theory
This study examines the adoption of Generative AI (GenAI) systems through the lens of Institutional Theory. Using a mixed-methods approach, we analyze how coercive, normative, and mimetic pressures influence GenAI integration in organizations. Key findings reveal:(1) regulatory frameworks significantly shape GenAI adoption strategies, with variations across industries and regions;(2) organizations balance conformity to institutional norms with innovation, often through strategic decoupling;(3) GenAI’s unique capabilities challenge traditional institutional pressures, necessitating new governance models; and (4) early GenAI adopters emerge as new sources of mimetic pressure, accelerating industry-wide adoption. We propose a novel framework capturing the interplay between GenAI characteristics and institutional dynamics, contributing to both Institutional Theory and AI adoption literature.
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Qualitative Insights Tool (QualIT): LLM Enhanced Topic Modeling
Topic modeling is a widely used technique for uncovering thematic structures from large text corpora. However, most topic modeling approaches e.g. Latent Dirichlet Allocation (LDA) struggle to capture nuanced semantics and contextual understanding required to accurately model complex narratives. Recent advancements in this area include methods like BERTopic, which have demonstrated significantly improved topic coherence and thus established a new standard for benchmarking. In this paper, we present a novel approach, the Qualitative Insights Tool (QualIT) that integrates large language models (LLMs) with existing clustering-based topic modeling approaches. Our method leverages the deep contextual understanding and powerful language generation capabilities of LLMs to enrich the topic modeling process using clustering. We evaluate our approach on a large corpus of news articles and demonstrate substantial improvements in topic coherence and topic diversity compared to baseline topic modeling techniques. On the 20 ground-truth topics, our method shows 70% topic coherence (vs 65% & 57% benchmarks) and 95.5% topic diversity (vs 85% & 72% benchmarks). Our findings suggest that the integration of LLMs can unlock new opportunities for topic modeling of dynamic and complex text data, as is common in talent management research contexts.
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Skills Lab Panel “Building Bridges”, for the Culture and Cohesion Summit.
Join Victoria Kuketz for an intercultural Skills Lab Panel “Building Bridges”, for the Culture and Cohesion Summit.
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The Climate Imperative: How AI Can Transform Africa’s Future
Africa contributes minimally to global greenhouse gas emissions but bears a disproportionate burden of climate change impacts. This article explores how artificial intelligence (AI) can bolster conservation and sustainability efforts across the continent. While challenges such as technological import reliance and digital divides persist, AI offers transformative potential by enhancing early prediction, disaster preparedness, and environmental management. Examples like Rwanda’s Wastezon, Ghana’s Okuafo Foundation, and Kenya’s Kuzi illustrate successful AI-driven initiatives. The article proposes adapting a public health prevention model-primary, secondary, and tertiary prevention-to structure AI-based environmental interventions. This approach would enable early detection of climate risks, timely mitigation efforts, and rehabilitation of damaged ecosystems. The authors also caution about AI’s environmental costs, including energy-intensive operations and resource extraction, advocating for ethical and Africa-centered AI solutions. Overall, the article argues that innovative, community-driven, and preventive uses of AI are essential for building climate resilience in Africa.
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Trustworthy and Responsible AI for Human-Centric Autonomous Decision-Making Systems
Artificial Intelligence (AI) has paved the way for revolutionary decision-making processes, which if harnessed appropriately, can contribute to advancements in various sectors, from healthcare to economics. However, its black box nature presents significant ethical challenges related to bias and transparency. AI applications are hugely impacted by biases, presenting inconsistent and unreliable findings, leading to significant costs and consequences, highlighting and perpetuating inequalities and unequal access to resources. Hence, developing safe, reliable, ethical, and Trustworthy AI systems is essential. Our team of researchers working with Trustworthy and Responsible AI, part of the Transdisciplinary Scholarship Initiative within the University of Calgary, conducts research on Trustworthy and Responsible AI, including fairness, bias mitigation, reproducibility, generalization, interpretability, and authenticity. In this paper, we review and discuss the intricacies of AI biases, definitions, methods of detection and mitigation, and metrics for evaluating bias. We also discuss open challenges with regard to the trustworthiness and widespread application of AI across diverse domains of human-centric decision making, as well as guidelines to foster Responsible and Trustworthy AI models.
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Unravelling socio-technological barriers to AI integration: A qualitative study of Southern African newsrooms
This study explores the socio-technological barriers to the adoption of artificial intelligence (AI)-powered solutions in three countries of the global south – South Africa, Lesotho, Eswatini, Botswana and Zimbabwe. Through 20 in-depth interviews with key stakeholders, it examines the distribution and circulation of AI technologies within selected newsrooms. Furthermore, the article explores socio-technological obstacles to the integration of AI among journalists. Lastly, it examines the consequences of these socio-technological obstacles to journalism. The article specifically seeks to answer three questions: How are AI technologies integrated in southern African newsrooms? What are the socio-technological barriers attendant to the use of AI in selected news organisations of sub-Saharan Africa? What are the implications of these socio-technological barriers to the process of news production in these newsrooms?
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Path to Personalization: A Systematic Review of GenAI in Engineering Education
This systematic review paper provides a comprehensive synthesis across 162 articles on Generative Artificial Intelligence (GenAI) in engineering education (EE), making two specific contributions to advance research in the space. First, we develop a taxonomy that categorizes the current research landscape, identifying key areas such as Coding or Writing Assistance, Design Methodology, and Personalization. Second, we highlight significant gaps and opportunities, such as lack of customer-centricity and need for increased transparency in future research, paving the way for increased personalization in GenAI-augmented engineering education. There are indications of widening lines of enquiry, for example into human-AI collaborations and multidisciplinary learning. We conclude that there are opportunities to enrich engineering epistemology and
competencies with the use of GenAI tools for educators and students, as well as a need for further research into best and novel practices. Our discussion serves as a roadmap for researchers and educators, guiding the development of GenAI applications that will continue to transform the engineering education landscape, in classrooms and the workforce.