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The Merits of Unconscious Thought in Creativity

2008· article· en· W2020081770 on OpenAlexaff
Chen‐Bo Zhong, Ap Dijksterhuis, Adam D. Galinsky

Bibliographic record

VenuePsychological Science · 2008
Typearticle
Languageen
FieldPsychology
TopicCreativity in Education and Neuroscience
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsUnconscious mindPsychologyConsciousnessCreativityDistractionCollective unconsciousCognitive psychologyAssociation (psychology)Social psychologyPsychoanalysisPsychotherapistNeuroscience

Abstract

fetched live from OpenAlex

Research has yielded weak empirical support for the idea that creative solutions may be discovered through unconscious thought, despite anecdotes to this effect. To understand this gap, we examined the effect of unconscious thought on two outcomes of a remote-association test (RAT): implicit accessibility and conscious reporting of answers. In Experiment 1, which used very difficult RAT items, a short period of unconscious thought (i.e., participants were distracted while holding the goal of solving the RAT items) increased the accessibility of RAT answers, but did not increase the number of correct answers compared with an equal duration of conscious thought or mere distraction. In Experiment 2, which used moderately difficult RAT items, unconscious thought led to a similar level of accessibility, but fewer correct answers, compared with conscious thought. These findings confirm and extend unconscious-thought theory by demonstrating that processes that increase the mental activation of correct solutions do not necessarily lead them into consciousness.

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)0.007
metaresearch head score (Gemma)0.034
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.034
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.012
Scholarly communication0.0030.005
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.095
GPT teacher head0.443
Teacher spread0.348 · 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 designBench or experimental
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

Citations197
Published2008
Admission routes1
Has abstractyes

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