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Record W2051180716 · doi:10.1068/a39391

Internal and External Dynamics of the Munich Film and TV Industry Cluster, and Limitations to Future Growth

2008· article· en· W2051180716 on OpenAlexafffund
Harald Bathelt, Armin Gräf

Bibliographic record

VenueEnvironment and Planning A Economy and Space · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicCultural Industries and Urban Development
Canadian institutionsUniversity of Toronto
FundersUniversity of Toronto
KeywordsMarketing buzzReflexivityCitizen journalismCluster (spacecraft)Economic geographyEconomyIndustrial organizationBusinessPolitical scienceSociologyEconomicsAdvertisingSocial scienceComputer science

Abstract

fetched live from OpenAlex

This analysis uses the case of a seemingly successful industry cluster (ie the film and TV industry in Munich) to demonstrate that deficits in the structure of social relations can impact a cluster's growth potential. In the period after World War II, Munich grew into a national centre of media industries in Germany due to the introduction of private/commercial TV, national entry barriers, and a supportive institutional infrastructure. The recent advertising crisis and the dissolution of the Kirch Group have, however, reinforced already existing internal dilemmas and contradictions. We suggest that the growth prospects of this industry are limited due to a lack of reflexive, interconnected communication and interaction patterns. In conceptual terms, we apply a model which emphasizes that local interaction or ‘buzz’ in clusters and interaction with external firms and markets through translocal or global ‘pipelines’ create reflexive dynamics. Based on this conception, participatory observation and semistructured interviews were conducted with sixty-five Munich firms, as well as with planners and media experts from the region. The results indicate that the regional, national, and occasional international project networks have had a smaller impact on the Munich film and TV industry than expected. Our investigation provides evidence that the cluster's structure of social relations is relatively weak. Internal networks which could drive creative recombination and innovation are underdeveloped, and linkages with external markets which could provide substantial growth impulses to the region are lacking. We argue that this structural weakness limits the potential for future growth.

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)0.000
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.185
Threshold uncertainty score0.321

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.027
GPT teacher head0.224
Teacher spread0.197 · 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

Citations43
Published2008
Admission routes2
Has abstractyes

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