Notice bibliographique
Résumé
Virtuality is a socially constructed reality mediated by electronic media (Morse, 1998). Virtuality has overcome the stage of being considered a “false” reality, and is now being recognized as a process of becoming through information and communication technologies (ICTs), one of the main changing trends in a world in which ownership of assets is overrated. Organizations such as Amazon, Google, Cisco Systems, IBM, Intel Capital, Orange, and Hewlett-Packard are some of the innovative enterprises that have adopted virtual teams in order to accelerate access to global business. For example, most of the people working in product development in Orange Group, one of the UK’s leading mobile phone service providers, work in virtual teams. The World Bank is also using virtual teams that collaborate across national and technical boundaries to meet organizational objectives. IBM, in a way to open up the innovation process, is pulling a technology- enabled global team (around 100,000 people) together for the online equivalent of a town meeting (Business Week Online, 2006) that will hopefully lead to idea generation by the whole IBM population, and powerful innovations in IBM. Characterized mainly by the dimension of timespace distantiation (Giddens, 1991) virtuality has an impact on the nature and dynamics of knowledge creation (Thompson, 1995), innovation (MacKenzie, 2006), social identity (Papacharalambous & McCalman, 2000), and organizational culture (available at http://www.etw. org/2003/Archives/telework2001-proc.pdf). The relentless advancement of ICT, in terms both of new technology and the convergence of technology (e.g., multimedia), is making virtual networking the norm rather than the exception. Socially, virtual communities are more dispersed, have different power dynamics, are less hierarchical, tend to be shaped around special interests, and are open to multiple interpretations, when compared to face-to-face equivalents. To successfully manage virtual communities, these differences need first to be understood, second, the understanding related to varying organizational aims, and third, the contextualised understanding needs to be translated into appropriate managerial implications. In business terms, virtuality exists in the form of lifestyle choices (home-working), ways of working (global product development teams), new products (virtual theme parks), and new business models (e.g., Internet dating agencies). Socially, virtuality can take the form of talking to intelligent agents, combining reality and virtuality in surgery (e.g., using 3D imaging before and during an operation), or in policy making (e.g., combining research and engineering reports with real satellite images of a landscape with digital animations of being within that landscape, to aid environmental policy decisions). Defining virtuality today is easy in comparison with defining, understanding, and managing it on an ongoing basis. As the title “Going Virtual” suggests, virtuality is a matter of a phenomenon in the making, as we enter into it during our everyday lives, as the technology develops, and as society changes as a result of virtual existences. The relentless advances in the technical complexity which underlies virtual functionality and the speeding up and broadening of our lives as a consequence of virtuality, make for little time and inclination to reflect upon the exact nature and effect of going virtual. As it pervades the way we live, work, and play at such a fast rate, we rarely have the time to stop and think about the implications of the phenomenon.
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 | 0,001 | 0,006 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,004 | 0,002 |
| Communication savante | 0,013 | 0,016 |
| Science ouverte | 0,002 | 0,010 |
| Intégrité de la recherche | 0,003 | 0,004 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,480 | 0,255 |
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 ».