MétaCan
Menu
Back to cohort

Understanding How Creative Thinking Skills, Attitudes and Behaviors Work Together: A Causal Process Model

2000· article· en· W2050905215 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueThe Journal of Creative Behavior · 2000
Typearticle
Languageen
FieldPsychology
TopicCreativity in Education and Neuroscience
Canadian institutionsMcMaster University
Fundersnot available
KeywordsProcess (computing)PreferencePsychologyVariable (mathematics)DeferralWork (physics)Quality (philosophy)Social psychologyComputer scienceEconomicsEngineeringMicroeconomicsMathematics

Abstract

fetched live from OpenAlex

Managers ( N = 112) from a large international consumer goods manufacturer participated in a field experiment in which they learned and applied the Simplex process of creative thinking to solve real management problems. The interrelationships among six attitudinal and behavioral skill variables learned during the training were measured to improve understanding of how these variables contribute to the process. Predicted relationships were tested and a best‐fit causal model was developed. Behavioral skill in generating quantity of options was the most important variable overall: it was directly associated with behavioral skill in both generating quality options and evaluating options. The key attitudinal skill and the second most important variable overall was the preference for avoiding premature evaluation of options (deferral of judgment). The other attitude measured, the preference for active divergence, played only an indirect role in the process.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.430
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.105
GPT teacher head0.393
Teacher spread0.289 · 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