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Record W2346699153 · doi:10.1142/s1363919616020011

CREATIVITY AND INNOVATION: STATE OF THE ART AND FUTURE PERSPECTIVES FOR RESEARCH

2016· article· en· W2346699153 on OpenAlex
Alexander Brem, Rogelio Puente‐Díaz, Marine Agogué

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.

Bibliographic record

VenueInternational Journal of Innovation Management · 2016
Typearticle
Languageen
FieldPsychology
TopicCreativity in Education and Neuroscience
Canadian institutionsHEC Montréal
Fundersnot available
KeywordsOperationalizationCreativityVariety (cybernetics)Field (mathematics)Engineering ethicsObject (grammar)Creativity techniqueResearch ObjectState (computer science)SociologyEpistemologyPsychologyKnowledge managementComputer scienceSocial psychologyArtificial intelligenceRegional scienceEngineering

Abstract

fetched live from OpenAlex

Creativity is a vibrant field of scientific research with important applied implications for the management of innovation. In this article, we argue that the proliferation of creativity research has led to positive and less positive outcomes and discuss five relevant research themes. We first introduce our readers to the different proposed dimensions of a creative object. Next, we explain recent developments on the level of the creativity magnitude issue. Based on that, we review how researchers currently operationalize creativity. After discussing how creativity is conceptualized and operationalized, we outline how it might be enhanced. Finally, we present an overview of the wide variety of methodological approaches currently used in creativity research. We close by calling for more interdisciplinary research and offering other suggestions for future directions.

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)0.002
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.742
Threshold uncertainty score0.134

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.097
GPT teacher head0.463
Teacher spread0.366 · 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