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Record W4379091942 · doi:10.5281/zenodo.7993881

Exploring the Relation between State and Trait Boredom and Various Measures of Creativity

2023· article· en· W4379091942 on OpenAlexaff
Jamie Nettinga, ROY GUTGLICK, JAMES DANCKERT

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2023
Typearticle
Languageen
FieldNeuroscience
TopicMind wandering and attention
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsBoredomTraitCreativityRelation (database)PsychologySocial psychologyState (computer science)Computer scienceData mining

Abstract

fetched live from OpenAlex

Popular sentiment suggests that boredom ought to lead to creativity despite a lack of research investigating the relationship explicitly. Across two experiments the relation between boredom and creativity was examined via a mood induction and surveys (Experiment 1) and behavioural tasks (Experiments 1 and 2). Results from Experiment 1 indicated that state boredom was in fact associated with poorer performance on the divergent thinking task and that trait boredom proneness was associated with both diminished belief in one’s creative potential and lower levels of engagement of everyday creative pursuits. Results from Experiment 2 again found no relation between state or trait boredom and creativity on a novel creativity task. Clearly, these findings indicate that neither state nor trait boredom promote increased creativity.

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)0.001
metaresearch head score (Gemma)0.009
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.228
GPT teacher head0.277
Teacher spread0.048 · 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

Citations20
Published2023
Admission routes1
Has abstractyes

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