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Record W1996064687 · doi:10.1002/jocb.38

Creative Imagination is Stable Across Technological Media: The Spore Creature Creator Versus Pencil and Paper

2013· article· en· W1996064687 on OpenAlexaff
Jessica Cockbain, Michael O. Vertolli, Jim Davies

Bibliographic record

VenueThe Journal of Creative Behavior · 2013
Typearticle
Languageen
FieldPsychology
TopicCreativity in Education and Neuroscience
Canadian institutionsCarleton University
Fundersnot available
KeywordsCreativityCreaturesPencil (optics)PsychologyAestheticsSocial psychologyCognitive psychologyArtNatural (archaeology)HistoryEngineering

Abstract

fetched live from OpenAlex

Abstract T. B. Ward (1994) investigated creativity by asking participants to draw alien creatures that they imagined to be from a planet very different from Earth. He found that participant drawings reliably contained features typical of common Earth animals. As a consequence, Ward concluded that creativity is structured. The present investigation predicts that this limitation on creativity is not restricted to drawings: the use of different technology will not change creative output. To investigate this question, participants performed Ward's task twice: once using pencil and paper and once using software made to design creatures (the Spore Creature Creator). Only minor significant differences were found. This preliminarily suggests that changing tools does not affect the overall rigidity of the creative process. This lends further support to Ward's thesis on the structural rigidity of creativity. We conclude by suggesting an elaboration to Ward's thesis that will be explored in future work. We suggest that aesthetics might be one of the factors that contribute to creative constraint, in that creatures that are too unusual would be less interesting.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.051
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.051
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.002
Scholarly communication0.0050.002
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0100.000

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 head0.047
GPT teacher head0.378
Teacher spread0.331 · 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 source (direct Gemma or distilled Codex), 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

Citations5
Published2013
Admission routes1
Has abstractyes

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