The New Oxford Handbook of Economic Geography
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Notice bibliographique
Résumé
The first fifteen years of the 21st century have thrown into sharp relief the challenges of growth, equity, stability, and sustainability facing the world economy. In addition, they have exposed the inadequacies of mainstream economics in providing answers to these challenges. This volume gathers over 50 leading scholars from around the world to offer a forward-looking perspective of economic geography to understanding the various building blocks, relationships, and trajectories in the world economy. The perspective is at the same time grounded in theory and in the experiences of particular places. Reviewing state-of-the-art of economic geography, setting agendas, and with illustrations and empirical evidence from all over the world, the book should be an essential reference for students, researchers, as well as strategists and policy makers. Building on the success of the first edition, this volume offers a radically revised, updated, and broader approach to economic geography. With the backdrop of the global financial crisis, finance is investigated in chapters on financial stability, financial innovation, global financial networks, the global map of savings and investments, and financialization. Environmental challenges are addressed in chapters on resource economies, vulnerability of regions to climate change, carbon markets, and energy transitions. Distribution and consumption feature alongside more established topics on the firm, innovation, and work. The handbook also captures the theoretical and conceptual innovations of the last fifteen years, including evolutionary economic geography and the global production networks approach. Addressing the dangers of inequality, instability, and environmental crisis head-on, the volume concludes with strategies for growth and new ways of envisioning the spatiality of economy for the future. Contributors to this volume - Philip Auerswald, George Mason University. Harald Bathelt, University of Toronto. Michael Berry, RMIT University, Australia. Ron Boschma, Utrecht University. Kam Wing Chan, University of Washington. Karen Chapple, University of California, Berkeley. Susan Christopherson, Cornell University. Gordon L. Clark, University of Oxford. Jennifer Clark, Georgia Institute of Technology. Neil M. Coe, National University of Singapore. Stuart Corbridge, Durham University. Lokesh Dani, George Mason University. Mercedes Delgado, MIT Sloan School of Management. Danny Dorling, University of Oxford. Gilles Duranton, University of Pennsylvania. Gary A. Dymski, University of Leeds. Benno Engels, RMIT University, Australia. Maryann P. Feldman, University of North Carolina. Richard Florida, University of Toronto. Chris Forman, Cornell University. Koen Frenken, Utrecht University. Meric S. Gertler, University of Toronto. Amy Glasmeier, Massachusetts Institute of Technology. Johannes Gluckler, Heidelberg University. Avi Goldfarb, University of Toronto. Gernot Grabher, HafenCity University Hamburg. Shane Greenstein, Harvard Business School. Dieter Helm, University of Oxford. Cameron Hepburn, University of Oxford. Alex Hughes, Newcastle University. Simona Iammarino, London School of Economics and Political Science. Oliver Ibert, Freie Universitat Berlin. Natasha Iskander, New York University. Chacko G. Kannothra, University of Massachusetts Boston. William R. Kerr, Harvard Business School. Janelle Knox-Hayes, Massachusetts Institute of Technology. Karen P.Y. Lai, National University of Singapore. Marcus M. Larsen, BI Norwegian Business School. Robin Leichenko, Rutgers University. Mark Lorenzen, Copenhagen Business School. Nichola Lowe, University of North Carolina at Chapel Hill. Stephan Manning, University of Massachusetts Boston. Ron Martin, University of Cambridge. Philip McCann, University of Groningen. Caitlin A. McElroy, University of Oxford. Anita M. McGahan, University of Toronto. Sarah McGill, University of Oxford. Charlotta Mellander, Jonkoping International Business School. Ashby Monk, University of Oxford. Phillip O'Neill, Western Sydney University. Jamie Peck, University of British Columbia. Alexander Pfeiffer, University of Oxford. Andres Rodriguez-Pose, London School of Economics. Rajiv Sharma, University of Oxford. Eric Sheppard, University of California, Los Angeles. Janice Stein, University of Toronto. Michael Storper, London School of Economics. Kendra Strauss, Simon Fraser University. Alexander Teytelboym, University of Oxford. Maria Tsampra, University of Patras, Greece. Callum Wilkie, London School of Economics. Neil Wrigley, University of Southampton. Henry Wai-chung Yeung, National University of Singapore. Dariusz Wojcik, University of Oxford. Matthew Zook, University of Kentucky.
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.
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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 découle