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Information technology policy: an international history

2004· preprint· en· W1606413731 sur OpenAlexaboutno aff
Richard Coopey

Notice bibliographique

RevueRePEc: Research Papers in Economics · 2004
Typepreprint
Langueen
DomaineBusiness, Management and Accounting
ThématiqueBusiness Strategy and Innovation
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésPolitical scienceRegional scienceGeography
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

Information Technology has become symbolic of modernity and progress almost since its inception. The nature and boundaries of IT have also meant that it has shaped, or become embedded within a wide range of other scientific, technological and economic developments. Governments, from the outset, saw the computer as a strategic technology, a keystone of economic development and an area where technology policy should be targeted. This was true for those economies interested in maintaining their technological and economic leadership, but also figured strongly in the developmental programmes of those seeking to modernise or catch up. So strong was the notion that IT policy should be the centre of economic strategy that predominant political economic ideologies have frequently been subverted or distorted to allow for special efforts to promote either the production or use of IT. This book brings together a series of country-based studies to examine, in depth, the nature and extent of IT policies as they have evolved from a complex historical interaction of politics, technology, institutions, and social and cultural factors. In doing so many key questions are critically examined. Where can we find successful examples of IT policy? Who has shaped policy? Who did governments turn to for advice in framing policy? Several chapters outline the impact of military influence on IT. What is the precise nature of this influence on IT development? How closely were industry leaders linked to government programs and to what extent were these programs, particularly those aimed at the generation of 'national champions', misconceived through undue special pleading? How effective were government personnel and politicians in assessing the merits of programs predicated on technological trajectories extrapolated from increasingly complex and specialised information? This book will be of interest to academics and graduate students of Management Studies, History, Economics, and Technology Studies, and Government and Corporate policy makers engaged with IT and Technology policy. Contributors to this volume - William Aspray, Professor, School of Informatics, Indiana University Dimitris Assimakopoulos, Professor of Information Systems and Director of the Doctoral Programme, Grenoble Ecole de Management Martin Campbell-Kelly, Reader, Department of Computer Science, University of Warwick Richard Coopey, Lecturer in History, University of Wales Mihaiela Grundey, Founder, Romanian Youth Support Trust Ross Hamilton, Freelance Software Developer Richard Heeks, Senior Lecturer in Development Informatics, Institute for Development Policy and Management, University of Manchester Eda Kranakis, Associate Professor and Chair of the History Department, University of Ottawa Stuart Macdonald, Professor of Information and Organization, Management School, University of Sheffield Boris Malinovsky, Academician of the International Academy of Sciences on Informatics Lev Malinovsky, Chief of the Scientific Research Laboratory, Institute of Cybernetics, Kiev Rebecca Marschan-Piekkari, Research Fellow, Swedish School of Economics, Helsinki Albert Meijer, Assistant Professor, Utrecht School of Governance Arthur Norberg, ERA Land-Grant Chair in the History of Technology, and Professor in the Program in the History of Science and Technology, University of Minnesota Knut Sogner, Professor of Economic and Business History, Norwegian School of Management Steven W. Usselman, Associate Professor of History, School of History, Technology, and Science, Georgia Institute of Technology Jan Van Den Ende, Associate Professor, Department of the Management of Information and Technology, Rotterdam School of Management Nachoem Wijnberg, Professor of Industrial Economics and Organization, Department of Organization and Management, University of Groningen Seiichiro Yonekura, Professor of Business History, Institute of Innovation Research, Hitotsubashi University, Tokyo

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 distillée sur la base complète

Imitation des enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: aucune
Score de désaccord entre enseignants0,868
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0040,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,003
Science ouverte0,0010,001
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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.

Tête enseignante Opus0,033
Tête enseignante GPT0,289
Écart entre enseignants0,257 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeSans objet
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations21
Publié2004
Routes d'admission1
Résumé présentoui

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