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Enregistrement W1540976619

Industry, Government Leaders Confront World's Innovation Needs

2004· article· en· W1540976619 sur OpenAlex

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Notice bibliographique

RevueResearch-Technology Management · 2004
Typearticle
Langueen
DomaineBusiness, Management and Accounting
ThématiqueUniversity-Industry-Government Innovation Models
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésGovernment (linguistics)Investment (military)Political sciencePublic relationsPoliticsLaw
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

Science policy-the ordered management of research-remains as hard to define as industrial policy. But research ministers and industry leaders from 30 countries have made a good stab at understanding the forces binding the processes of innovation with scientific advance. Their venue was the January Organization for Economic Cooperation and Development (OECD) meeting in Paris, where they explored Science, Technology and Innovation for the 21st Century. the chair was Australia's minister for science, Peter McGauran. a world of increasing opportunity and challenge, spending on RD business investment in research continued to be double that of government. Social Needs Weigh on Research These trends are continuing, since governments today are more harried by society-related programs than ever before. Official allocations to support research are thus often easy victims to outside pressures. Consider, for example, the extraordinary heat wave and drought that struck western Europe in summer 2003. sudden demand placed on public-health and water services in France, the area hardest hit, siphoned funds to these sectors from (among others) the research community's budget. One consequence, taking place at the very moment of the OECD science policy conference, was public protest that brought some 10,000 researchers from their labs to the Paris streets. Added to such episodic financial woes are more lingering problems that hinder the march of science. First among these the reluctance of young people to study science, math or engineering. Britain, France and Germany especially, university students face a hitherto virtually unknown threat of tuition fees. This combines with another imminent deterrent, the cross-border harmonization of university degrees-most likely along the lines of the North American model of bachelor's-master's-doctor's degrees. Many professors and students perceive such changes as not only a disruption of current university rhythms but a menace to national excellence in different disciplines. Then, once the young techie ready for professional life, cultural obstacles to job mobility take over. These mobstacles include * Reluctance to move far from home. * Coping with a foreign language or culture. * long tradition of staying with the same employer. * A profound aversion to skipping from university to industry to government, American-style. All of these hurdles blend into a negative synergism that curbs the creation and diffusion of knowledge-with concomitant impacts on innovative research, patent applications and economic access to intellectual property by other players, particularly the less industrialized countries. Meanwhile, the drain of the 1960s-1970s survives; it regularly affects some countries: Britain, Germany, Italy and France (see RTM Perspectives, March-April 2004, pp. 2-3), but especially those of Asia and Latin America. However, a few nations outside the U.S., Canada and Australia actually benefit from a brain gain, notably Sweden and New Zealand. new Irish Institute of Science has been remarkably effective, too, in persuading young native researchers to remain in the country's industries. In today's knowledge society we must discriminate among knowledge, inventiveness, and technology, emphasized Diana Bracco, CEO of Italy's Bracco Group. We need motivated young people capable of logical thinking. research community a meritocracy, the rewards of performance are based on achievement. Environment, Safety and Security There are other factors at play, such as environmental risks. President George W. Bush's science advisor and head of the Office of Science and Technology, John H. Marburger III, spelled some out: The most important thing in terms of pollution from energy use, he said, is how we transform energy from the basic fuels. …

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 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)0,002
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict), Intégrité de la recherche, Charge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Théorique ou conceptuel · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,869
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0020,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0050,013
Études des sciences et des technologies0,0010,001
Communication savante0,0000,001
Science ouverte0,0010,002
Intégrité de la recherche0,0010,003
Charge utile insuffisante (le modèle a refusé de juger)0,0010,001

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 Opus0,077
Tête enseignante GPT0,300
Écart entre enseignants0,223 · 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