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Record W4400778654 · doi:10.37725/mgmt.2024.9048

From One Place to Another – Place Attendance as Resources for Innovators

2024· article· en· W4400778654 on OpenAlex
Étienne Capron, Raphaël Suire

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueM n gement · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicCultural Industries and Urban Development
Canadian institutionsHEC Montréal
FundersAgence Nationale de la Recherche
KeywordsAttendancePluralPerspective (graphical)HomogeneousProcess (computing)Knowledge managementBusinessMarketingComputer scienceEconomic growthEconomicsArtificial intelligence

Abstract

fetched live from OpenAlex

Despite a growing interest for places in management research, it remains unclear how the attendance of multiple places by innovators contributes to the innovation process. We propose a new perspective in which innovators attend distinct places that provide them plural resources, and that it is their combination that supports innovation. Based on this proposition, we study the case of projection mapping in Montreal (Canada) as an illustration for creative and cultural industries. We show that the number and types of places attended evolves in the different stages of the innovation process, and that actors are not homogeneous in their attendance. These evolutions are captured with the concept of preferential circulations we introduce to capture the patterns of attendance of places by innovators. Through this, we offer a new lens to the study and the management of innovation through places.

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)0.000
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: Empirical · Consensus signal: none
Teacher disagreement score0.698
Threshold uncertainty score0.999

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)0.0020.000

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 head0.049
GPT teacher head0.316
Teacher spread0.267 · 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