Notice bibliographique
Résumé
During the dotcom boom, when technology innovation appeared to offer a solution to almost any structural economic woe, government technology strategists from as far away as Brazil, Canada, China and Singapore made a pilgrimage to the fenlands in the southeast of England. They travelled in the hope that if they could just understand the they would be able to recreate its success in emerging technology hubs elsewhere. It turned out that Cambridge wasn't about to hand out a recipe for recreating its Phenomenon. Being able to describe how this formerly agrarian economy, centered on a 795-year-old university, has become a hotbed of technological innovation does not mean it is easy to replicate. High-Tech Cluster Economy So what is the Phenomenon? Simply put, Cambridge and its surrounding area has become a high-technology cluster economy focused on computer hardware and software, scientific instruments, electronics and biotechnology. Academics, entrepreneurs, business and support services have coalesced to create an environment that encourages and enables the formation and growth of high-technology companies. The cluster is sufficiently well-established for serial entrepreneurs to have emerged, mentoring schemes to have been formed, and enablers such as venture capital and professional services to have flocked to the region in support. Links between firms, the university and research organizations are strong and often based on personal relationships. The impact of the Cambridge Phenomenon is evident from the statistics. According to Cambridgeshire County Council, the region's population grew by more than 20 percent in the 20 years from 1981 to 2001. By then, the region was employing 48,300 people in 1,526 high-technology companies, out of a working population of 337,510. More than half (58%) of these businesses employed ten people or less. And the focus on the city was strong, with 34 percent of the jobs based in the city and an additional 39 percent in nearby south Cambridgeshire. Explaining the Phenomenon One obvious reason for Cambridge's success is its university, one of the oldest and best-known in the world, with a record of producing more than 60 Nobel Prize winners. The University's reputation has encouraged undergraduates to stay on to do their research, and this, coupled with a collegiate organization, has tended to create strong personal networks. The colleges have responded to the entrepreneurial culture by creating science parks and business incubators. In 1970, Trinity College founded Cambridge Science Park, on land it had owned since 1546, as a response to a government report the previous year calling for better links between academia and industry. The site hosts start-ups, developing companies, technology consultancies, and attendant services such as venture capital. In 1987, St John's College built an Innovation Centre to host early-stage companies, providing business advice and help with finding funding. It has since acted as midwife to at least one billion-pound company. Networking lies at the heart of the Cambridge Phenomenon, with the colleges, departments, innovation center, and science parks all creating pools of shared experience and personal contacts. In 1998, a group of six companies formed the Cambridge Network to formalize and strengthen this networking, which has underpinned much of the region's technology development. The Cambridge Network has grown to 1,300 companies that use its website and meetings to make contacts, find services and promote their businesses. Between 100 and 200 of these are overseas companies with at least one person in Cambridge, according to Peter Hewkin, chief executive of the Network. He estimates that between a quarter and a third of these are U.S. companies. Another 20 to 30 overseas companies are members despite not having a local presence. Individuals also play a vital role in creating networks. …
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 | 0,005 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,003 | 0,002 |
| Communication savante | 0,012 | 0,004 |
| Science ouverte | 0,001 | 0,010 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,084 | 0,025 |
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 ».