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Knowledge‐Intensive Firms, Communities, and Creative Cities1

2008· book-chapter· en· W203700749 on OpenAlexaffabout
Patrick Cohendet, Laurent Simon

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldSocial Sciences
TopicCultural Industries and Urban Development
Canadian institutionsHEC Montréal
Fundersnot available
KeywordsCreativityExploitSubsidiaryBusinessEconomic geographyKnowledge managementPublic relationsCreative industriesFrame (networking)MarketingIndustrial organizationSociologyPolitical scienceEngineeringPsychologyEconomicsComputer scienceSocial psychologyTelecommunicationsFinance

Abstract

fetched live from OpenAlex

Abstract This contribution focuses on the relationship between the urban milieu and high creativity firms, focusing on the videogames sector in Montreal. It reveals an organizational frame of a lack of large R&D departments and a lack of global networks of subsidiaries or partners through which firms access creative knowledge. None of these classical ways to enhance creativity is present. Instead, creativity relies on distributed and independent communities of knowing which generate, exploit, and develop a ‘creative slack’ as a source of growth for the firm. These communities find their source of inspiration and innovation in the fertile soil of a creative city.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.066
Threshold uncertainty score0.993

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 studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0110.000

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 head0.115
GPT teacher head0.298
Teacher spread0.183 · 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.

Study designNot applicable
Domainnot available
GenreOther

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

Citations45
Published2008
Admission routes2
Has abstractyes

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