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Record W4377084394 · doi:10.7202/1097130ar

L’influence des types conatifs sur le rendement scolaire d’un groupe d’élèves franco-albertains de niveau secondaire

2023· article· fr· W4377084394 on OpenAlexaffvenueabout
René Langevin, Jean Toupin

Bibliographic record

VenueRevue de psychoéducation · 2023
Typearticle
Languagefr
FieldMathematics
TopicCognitive and developmental aspects of mathematical skills
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsHumanitiesForestryArtGeography

Abstract

fetched live from OpenAlex

L’objectif de cette étude exploratoire consiste à vérifier l’influence des quatre types conatifs (Fact Finder/Follow Thru/Quick Start/Implementor) décrits par Kolbe (1990) sur le rendement scolaire. Soixante (60) sujets franco-albertains âgés de 14 à 17 ans ont été recrutés à cette fin. Le recrutement s’est fait à Edmonton dans une école alternative pour adolescents ayant des difficultés d’adaptation scolaire et dans une école secondaire régulière située dans cette même ville. L’instrument de mesure des types conatifs fut le Kolbe Youth Index (KYI) de Kolbe (2003). Les résultats montrent qu’un type conatif Fact Finder dans la zone Initiate est associé à un niveau de rendement scolaire élevé tandis qu’un type conatif Quick Start dans la même zone est lié à un niveau de rendement scolaire faible. Enfin, d’autres résultats indiquent qu’un rendement scolaire moyen est associé aux quatre types conatifs et ce, à des niveaux variables dans les zones (Prevent/Respond/Initiate).

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 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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.459
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.002

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 head0.026
GPT teacher head0.289
Teacher spread0.262 · 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 teacher head, not a consensus.

Study designTheoretical or conceptual
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
Published2023
Admission routes3
Has abstractyes

Explore more

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