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Record W1987890855 · doi:10.2466/pr0.2001.88.3.734

Relations of Imagery, Creativity, and Socioeconomic Status with Performance on a Stock-Market e-Trading Game

2001· article· en· W1987890855 on OpenAlexaff
Daniel S. L. Roberts, Brenda E. Macdonald

Bibliographic record

VenuePsychological Reports · 2001
Typearticle
Languageen
FieldPsychology
TopicCreativity in Education and Neuroscience
Canadian institutionsMcGill UniversityConcordia University
Fundersnot available
KeywordsSocioeconomic statusCreativityPsychologyAdjective check listPersonalityInterdependenceStock marketSocial psychologyDevelopmental psychologyDemographySocial scienceSociologyGeography

Abstract

fetched live from OpenAlex

The purpose of the present investigation was to examine how measures of imagery, creativity, and socioeconomic status relate to performance in a stock-market trading game. The 368 participants were students enrolled in an administration studies curriculum. A multiple regression analysis showed imaging scores to be a predictor of stock-trading performance as were creativity and socioeconomic status to a lesser extent. High imagers and high scorers on creativity and socioeconomic status made several times more profit with their portfolios. Results are discussed in terms of imagery having multiple repercussions on learning, e.g., memory and problem-solving. It is concluded that scores on imagery, creativity, and socioeconomic status, being weakly correlated, are interdependent and likely associated with personality traits shaped within a stimulating home or social environment.

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)0.007
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 score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
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)0.0040.000

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 head0.047
GPT teacher head0.371
Teacher spread0.325 · 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

Citations1
Published2001
Admission routes1
Has abstractyes

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