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Record W2955534123 · doi:10.1177/0829573519853672

Literature Review of Francophone Psychometric Tests of Creativity: Guiding School Psychologists

2019· article· en· W2955534123 on OpenAlexaff
Philippe Valois, Jacques Forget, Carolanne Ponton

Bibliographic record

VenueCanadian Journal of School Psychology · 2019
Typearticle
Languageen
FieldPsychology
TopicCreativity in Education and Neuroscience
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsCreativityPsychologyCompendiumCurriculumTest (biology)TraitApplied psychologyDevelopmental psychologySocial psychologyPedagogyLinguistics

Abstract

fetched live from OpenAlex

Creativity is viewed as a trait of essential use in many contexts. The need for creative people in different domains implies that school should develop and evaluate creativity in their curriculum. Runco identified more than 80 creativity tests in English. No equivalent compendium exists for creativity tests in French. Thus, francophone students are not well deserved by the current state of creativity’s testing. The first objective of this article is to identify existing French tests of creativity with children and adolescent subjects that were identified in different databases using a systematic literature review method. The second objective is to present the key components and psychometric values of each identified test. Eight instruments for francophones were identified as being validated or being used in research setting with children or adolescent. Different theories of creativity associated with each test are also presented to guide the reader in selecting the most appropriate test for his school curriculum or his research.

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)0.022
metaresearch head score (Gemma)0.059
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.978
Threshold uncertainty score0.115

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0220.059
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0230.019
Science and technology studies0.0010.002
Scholarly communication0.0030.002
Open science0.0020.002
Research integrity0.0010.001
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 head0.071
GPT teacher head0.393
Teacher spread0.322 · 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.

Study designSystematic review
DomainMethods
GenreReview

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

Citations2
Published2019
Admission routes1
Has abstractyes

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