民主主義の不完全さを意識し、それ自体を見つめ直す重要性は近年高まっている。一方で政治経済学において、数理モデルにより民主主義を検討した研究は少ない。本研究は、民主主義社会を数学的に表現することで、①問題状況や安定をもたらす可能性や状況を示し民主主義の性質を捉え直す、②制度の運用や改善を考える、③関連する先行研究の補足・批判を行うことを目的とする。将来は大学の研究職に就くことを目標としている。
採択者紹介Selected person Introduction
Keywords
42人の学生が見つかりました
文学研究科 尾﨑 萌子
相互行為の社会言語学の観点から見た親子間会話の分析
大学教員および研究者を目指しています。
文学研究科 細谷 諒太
文学研究科 寒河江 陽
文学研究科 高萩 智也
政策・メディア研究科 温 雅芳
Exploring social resilience for urban flood disasters in China
My research directions are urban disaster risk reduction, social resilience, and community resilience. The research focuses on the combination of the humanities and natural sciences, and the integration of different research fields such as disaster education and economics, which contributes to improving the social resilience to urban disasters in Japan. For my career prospects, I hope to work in the disaster research institute in Japan or non-governmental organization such as the United Nations Office for Disaster Risk Reduction.
政策・メディア研究科 近藤 はるか
政策・メディア研究科 プーデル ナミータ
都市部の中心部と周辺部のつながりを分析し、集合的な災害回復力を確立する視点:ネパール、カトマンズの事例
My research explores innovative solutions in the food and water system, linking urban and rural areas from a disaster resilience perspective. Delving into disaster resilience through a robust food and water system, my findings aim to contribute significantly to all developing countries and cities. Looking ahead, my career prospects center around the food and water sector, driven by a passion for enhancing sustainability and disaster preparedness. With a solid foundation in research, analytical skills, and a commitment to resilience, I am poised to make meaningful contributions to the advancement of disaster-resilient food and water systems.
政策・メディア研究科 川島 寛乃
実空間における不規則かつ不完全なデータ増加に対応可能な継続学習
To effectively apply AI technology in the real world, AI models must continuously learn and grow by integrating new information while leveraging past knowledge. My research is Continual Learning and it aims to enable AI models to learn continuously in such environments. Specifically, I focus on the “Replay method”, akin to human note-taking, where a portion of learned data is retained for future learning. I investigate how much data should be retained for effective ongoing learning. Ultimately, I aim to apply this technology for societal benefit, contributing to the overall digitalization of society, including small-scale organizations and communities.