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Record W4392139319 · doi:10.1177/27538699241233195

The Creative Space Theory as a map to explore the mind

2024· article· en· W4392139319 on OpenAlexafffund
Jean‐Christophe Goulet‐Pelletier, Denis Cousineau

Bibliographic record

VenuePossibility Studies & Society · 2024
Typearticle
Languageen
FieldPsychology
TopicCreativity in Education and Neuroscience
Canadian institutionsUniversity of Ottawa
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSpace (punctuation)Cognitive scienceSociologyCreativitySymbol (formal)Conceptual frameworkEpistemologyComputer sciencePsychologySocial psychologySocial science

Abstract

fetched live from OpenAlex

Despite significant transformations in most domains of activities, there might still be some constancies in the creative spaces explored throughout history. This paper introduces the Creative Space Theory (CST), a conceptual framework delineating 10 distinct creative spaces, analogous to creative landscapes. These creative spaces are proposed as navigational terrains for an array of media, tools, activities, and domains. The 10 spaces of the theory are movement, sound, image, sensation, emotion, strategy, story, symbol, network, and system. Notably, these creative spaces transcend specific media, and cover artistic as well as intellectual domains. For example, the sound space would be relevant to music, poetry, filmmaking, and acting among others, whereas the system space may be relevant to engineering, medicine, science, and design among others. The proposed theory holds potential utility in three key areas: (1) nurturing individual’s creative potential, (2) helping creators adapt to continuously changing circumstances, and (3) fostering positive creative self-beliefs in overlooked domains of creation. The current paper is a theoretical elaboration. We describe the creative spaces and discuss the implications of the theory towards individuals, educational practices, and research within the fields of cognition and Artificial Intelligence.

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)0.002
metaresearch head score (Gemma)0.001
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.089
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
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)0.0000.001

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 head0.119
GPT teacher head0.461
Teacher spread0.342 · 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 designQualitative
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

Citations4
Published2024
Admission routes2
Has abstractyes

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