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Record W1976630150 · doi:10.1068/a38215

Hollywood, Vancouver, and the World: Employment Relocation and the Emergence of Satellite Production Centers in the Motion-Picture Industry

2007· article· en· W1976630150 on OpenAlexaboutno aff
Allen J. Scott, Naomi Pope

Bibliographic record

VenueEnvironment and Planning A Economy and Space · 2007
Typearticle
Languageen
FieldSocial Sciences
TopicCultural Industries and Urban Development
Canadian institutionsnot available
FundersTowson University
KeywordsHollywoodRelocationFilm industryStudioDecentralizationConsolidation (business)Production (economics)Movie theaterEconomyPolitical scienceHistoryBusinessEngineeringEconomicsLawArt historyTelecommunicationsComputer science

Abstract

fetched live from OpenAlex

The paper opens with an identification of the phenomenon of employment relocation (runaway production) from Hollywood and the concomitant formation of satellite production centers in other parts of the world. A brief theoretical analysis of this issue is provided, emphasizing the role of scale effects and transactions costs. The empirical record of the decentralization of film-shooting activities from Hollywood over the period from the early 1980s to the early 2000s is reviewed. We describe the effects of these activities on the rise and consolidation of the Vancouver film-production complex, and we engage in a broad discussion of the spatial and economic structure of the complex. We subsequently show that many places in other countries (for example, Australia, New Zealand, Romania, the Czech Republic, Mexico, South Africa, and elsewhere) are now competing strongly with Vancouver for film-shooting activities from Hollywood. We predict that this competition is likely to intensify greatly over the next decade or so, and that the global geography of film-shooting activities will almost certainly become increasingly more variegated as new studio complexes open up around the world.

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.

How this classification was reachedexpand

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.465
Threshold uncertainty score0.271

Codex and Gemma teacher scores by category

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

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 head0.017
GPT teacher head0.242
Teacher spread0.225 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations79
Published2007
Admission routes1
Has abstractyes

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