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Record W2948848264

Defining Value in the Creative Economy

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

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueDMU Open Research Archive (De Montfort University) · 2019
Typebook-chapter
Languageen
FieldSocial Sciences
TopicCultural Industries and Urban Development
Canadian institutionsnot available
Fundersnot available
KeywordsValue (mathematics)Creative economyEconomicsMathematicsPolitical scienceStatisticsCreativity
DOInot available

Abstract

fetched live from 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. 
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\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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.844
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0030.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.124
GPT teacher head0.334
Teacher spread0.210 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it