Society5.0 時代における大学院教育 : その将来像と課題 第52 回（2024年度）研究員集会の記録
Notice bibliographique
Résumé
Summary Report of the Research Institute for Higher Education Annual Study Meeting, 2024 The 52nd Researchers' Meeting was held on November 8, 2024, with the theme of "Graduate School Education in the Society 5.0 Era: Its Future Vision and Challenges." This researchers' meeting was co-hosted by the Chugoku-Shikoku Branch of the IDE University Association, of which the President of Hiroshima University serves as the branch chair. In the 2021 "6th Science, Technology and Innovation Basic Plan," Society 5.0 was redefined as "a society that is sustainable and resilient, ensures the safety and security of the people, and enables each individual to realize diverse well being." In order to realize such a society, strengthening research capabilities that will open up the frontiers of knowledge and become a source of value creation was presented as one of the important policies. In addition, the "Basic Act on Science, Technology and Innovation," which came into effect in April 2021, stated that "integrated knowledge" that combines all "knowledge," including humanities, social sciences and natural sciences, will contribute to a comprehensive understanding of humans and society and problem solving. In this way, the nature of knowledge is becoming important in society, and expectations for graduate schools, which are at the forefront of knowledge, are increasing. Despite this, the number of Japanese graduate students in master's and doctoral programs in humanities and social sciences, and in doctoral programs in science, engineering, and agricultural sciences has been declining in recent years. It is difficult to say that Japanese graduate schools are living up to expectations. At this year's researchers' meeting, the following experts involved in graduate school practice and research provided information on the expectations, current situation, and challenges for graduate schools in countries around the world, especially Asian countries including Japan, and how they are trying to address these challenges. Professor Glen Jones of the University of Toronto and Professor Hiromi Yokoyama of the University of Tokyo gave keynote speeches, and information was provided by Professor Masanori Hanawa of Yamanashi University, Professor Jung Cheol SHIN of Seoul National University, Associate Professor Wenqin Shen of Peking University, and Professor Mari Kawamura of the Ministry of Education, Culture, Sports, Science and Technology's National Institute of Science and Technology Policy. In response to these keynote speeches and information provided, Professor Hisakazu Matsushige, Professor Emeritus of Osaka University and currently Professor at Takamatsu University, and Professor Yosuke Yamamoto, Professor Emeritus of Hiroshima University, provided comments. Many people participated in the meeting both in person and online. We would like to thank all the speakers and everyone who took time out of their busy schedules to take part in the discussion. We have compiled a record of the day's proceedings as a publication by the Hiroshima University Center for Research and Development of Higher Education. We hope that this book will contribute to the development of graduate schools in Japan.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,003 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,003 | 0,002 |
| Communication savante | 0,005 | 0,003 |
| Science ouverte | 0,000 | 0,002 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,029 | 0,008 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».