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Record W2212582748 · doi:10.1177/2158244015611448

Culture and Creativity

2015· article· en· W2212582748 on OpenAlexaboutno aff
Catharine Dishke Hondzel, Marte Sørebø Gulliksen

Bibliographic record

VenueSAGE Open · 2015
Typearticle
Languageen
FieldPsychology
TopicCreativity in Education and Neuroscience
Canadian institutionsnot available
Fundersnot available
KeywordsTorrance Tests of Creative ThinkingCreativityPsychologyNorwegianTest (biology)Divergent thinkingDevelopmental psychologyEarly childhoodStandardized testSubject (documents)Creative thinkingSocial psychologyMathematics educationEcology

Abstract

fetched live from OpenAlex

Creativity and divergent thinking are components of learning in childhood that often go unmeasured in favor of standardized subject assessments. To better understand the ways in which creativity develops and is related to environmental and cross-cultural factors, this study reports on the scores obtained by 8-year-old students living in differently sized communities in Norway and Canada measured using the Torrance Test of Creative Thinking (TTCT). Results of multivariate analyses indicate statistically significant differences between Norwegian and Canadian children on several Torrance Test subscales as well as surprising relationships between the size of the community in which the children lived and the scores they obtained. Results and discussion are framed in reference to the ways in which culture and communities potentially shape the development of divergent thinking skills and open up questions about the ways in which social environments can influence the development of creativity in childhood.

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)0.004
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 score0.007
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.004
Scholarly communication0.0040.001
Open science0.0000.002
Research integrity0.0000.001
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 head0.123
GPT teacher head0.443
Teacher spread0.319 · 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

Citations20
Published2015
Admission routes1
Has abstractyes

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