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Defining Value in the Creative Economy

2019· book-chapter· en· W2948848264 sur OpenAlex
Rachel Granger

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Notice bibliographique

RevueDMU Open Research Archive (De Montfort University) · 2019
Typebook-chapter
Langueen
DomaineSocial Sciences
ThématiqueCultural Industries and Urban Development
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésValue (mathematics)Creative economyEconomicsMathematicsPolitical scienceStatisticsCreativity
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

The creative and cultural industries as the primary focus of this book, constitute the most distinct area of economic growth of the new Millennium, and are increasingly viewed as an emerging paradigm in their own right (see Lazzeretti and Vecco, 2018). Recognising and exhorting their early economic potential, UK and Australia under the Blair and Howard Gov-ernments began to commercialise the creative and cultural industries in earnest during the 1990s and in so doing, invested heavily in public and private flagships, which were to be-come key international demonstrators e.g. London’s Tech City, Manchester’s Northern Quarter and Media City, Brisbane’s South Bank and Creative Precinct. These early demon-strators drove fascination and spawned creative projects throughout much of the western world, drawing on Florida’s (2001) assertions of the creative city and creative workers as an economic panacea, and producing a ‘serial replication’ of investment (McCarthy, 2005) in creative infrastructure. As such, the first decade of the new Millennium could be character-ised as a period of creative consolidation in the UK and Australia, with new international creative cities and clusters emerging in regional capitals such as Bristol, Birmingham, Shef-field, and Glasgow in the UK, and in Australia, Sydney, Melbourne, and Perth. Elsewhere, cities have invested in new creative bases to replicate these early successes in the UK and Australia; developing meandering creative quarters in metropolitan areas across both Eu-rope and in North America (e.g. New York, Portland, Austin, Toronto, Montreal, and Van-couver). 
\n
\nThe resilience of the creative city form in the face of a global downturn has been especially notable, perhaps acting as one of the few truly expansionary areas of the global economy, and the most recent spatial fix under capitalist conditions (see Harvey, 2001; Jessop, 2006). In the Global South, especially in South East Asia, there has been concerted effort over the last decade to develop internationally competitive creative cities to match those of the Global North, and as a result, considerable investment has been directed in recent years into the creative industries in world cities such as Seoul, Shanghai, Taipei, Bangkok, and more recently, the Middle East. This globalisation of the creative and cultural industries has been underpinned especially in South East Asia by new digital technologies, and a landscape of mature multinationals and global investment. 
\n
\nAt the heart of this growing policy attention is the remarkable growth and economic poten-tial of the creative economy, which in some countries has offered a route out of long term structural decline of deindustrialisation. In these countries, creative industries now account for 1 in 10 jobs in the economy, and 1 in 4 new jobs (DCMS, 2018). For example, between 2011-2014 and 2015-2016, the creative industries in the UK, grew on average by 11 per cent, twice as fast as in the rest of the economy (NESTA, 2018a). In a climate of continued economic and political uncertainty, where the effects of the Global Financial Crisis are still being meted out a decade on, and the risk of a further downturn ever present, the potential for employment and income from new areas such as the creative economy, acts as a cen-tripetal pull on policy makers. In this sense, the value of the creative and cultural industries can be seen in terms of jobs and wealth, and this provides one view of value construction in the creative economy. This cursory view of what the creative and cultural industries are, and what value they have, is the primary focus of this book.

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)0,003
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesCharge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: aucune
GenreSignal candidat: Autre · Signal consensuel: Autre
Score de désaccord entre enseignants0,844
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0030,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0010,000
Études des sciences et des technologies0,0010,001
Communication savante0,0000,000
Science ouverte0,0030,001
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

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 Opus0,124
Tête enseignante GPT0,334
Écart entre enseignants0,210 · 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