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Record W2949281652 · doi:10.3389/fpsyg.2019.01426

The Ubiquity of Cross-Domain Thinking in the Early Phase of the Creative Process

2019· article· en· W2949281652 on OpenAlexafffund
Victoria S. Scotney, Sarah Weissmeyer, Nicole Carbert, Liane Gabora

Bibliographic record

VenueFrontiers in Psychology · 2019
Typearticle
Languageen
FieldPsychology
TopicCreativity in Education and Neuroscience
Canadian institutionsUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsCreativityProcess (computing)Domain (mathematical analysis)PsychologyCreative briefCreativity techniqueCreative workProduct (mathematics)Cognitive scienceCognitive psychologySocial psychologyComputer scienceVisual arts

Abstract

fetched live from OpenAlex

To what extent are creative processes in one domain (e.g., technology) affected by information from other domains (e.g., music)? While some studies of professional creators suggest that creative abilities are domain-specific, other studies suggest that creative avocations stimulate creativity. The latter is consistent with the predictions of the honing theory of creativity, according to which the iterative process culminating in a creative work is made possible by the self-organizing nature of a conceptual network, or worldview, and its innate holistic tendency to minimize inconsistency. As such, the creative process is not restricted to the creative domain; influences from domains other than that of the final product are predicted to impact the creative process and its outcome. To assess the prevalence of cross-domain influences on creativity we conducted two studies: one with creative experts, and one with undergraduate students from diverse academic backgrounds. Participants listed both their creative outputs, and the influences (sources of inspiration) associated with each of these outputs. In both studies, cross-domain influences on creativity were found to be widespread, and indeed more frequent than within-domain sources of inspiration. Thus, examination of the inputs to, rather than the outputs of, creative tasks supported the prediction of honing theory that cross-domain influences are a ubiquitous component of the creative process.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.049
Threshold uncertainty score0.438

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.032
GPT teacher head0.434
Teacher spread0.401 · 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.

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

Citations38
Published2019
Admission routes2
Has abstractyes

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