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Record W2963884190

Creative Interference and States of Potentiality in Analogy Problem Solving

2011· article· en· W2963884190 on OpenAlexafffund
Liane Gabora, Adam Saab

Bibliographic record

VenueeScholarship (California Digital Library) · 2011
Typearticle
Languageen
FieldPsychology
TopicCreativity in Education and Neuroscience
Canadian institutionsUniversity of British Columbia
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsAnalogyCreativityAssociative propertyCognitionInterference (communication)Cognitive psychologyCognitive scienceComputer scienceContent-addressable memorySelection (genetic algorithm)PsychologyCreative problem-solvingArtificial intelligenceTheoretical computer scienceMathematicsSocial psychologyEpistemologyPure mathematicsArtificial neural network
DOInot available

Abstract

fetched live from OpenAlex

Creative processes are widely believed to involve the generation of multiple, discrete, well-defined possibilities followed by exploration and selection.An alternative, consistent with parallel distributed processing models of associative memory, is that creativity involves the merging and interference of memory items resulting in a single cognitive structure that is ill-defined, and can thus be said to exist in a state of potentiality.We tested this hypothesis in an experiment in which participants were interrupted midway through solving an analogy problem and asked what they were thinking in terms of a solution.Naïve judges categorized their responses as AP if there was evidence of merging solution sources from memory resulting in an ill-defined idea, and SM if there was no evidence of this.Data from frequency counts and mean number of SM versus AP judgments supported the hypothesis that midway through creative processing an idea is in a potentiality state.

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)0.006
metaresearch head score (Gemma)0.072
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.072
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.003
Scholarly communication0.0020.003
Open science0.0000.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.038
GPT teacher head0.278
Teacher spread0.239 · 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 designNot applicable
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

Citations25
Published2011
Admission routes2
Has abstractyes

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