La configuration des corrélations entre le concept de soi et le rendement scolaire : une méta-analyse
Bibliographic record
Abstract
Cet article présente la problématique, la méthodologie et les résultats d'une méta-analyse de la configuration du lien corrélatif entre le concept de soi et le rendement scolaire. Il ressort de la recherche que la caractérisation des diverses catégories de concept de soi et de rendement scolaire constitue un premier facteur explicatif de ce lien. La configuration proposée permet de conclure que le concept de soi non scolaire et le concept de soi général ont des corrélations faibles alors que le concept de soi scolaire présente des liens nettement plus élevés variant selon les types de rendement scolaire de moyen à modérément élevé. Le rejet de l'hypothèse d'homogénéité des corrélations de chaque catégorie soulève la possibilité de l'existence de variables concomitantes constituant un deuxième facteur explicatif.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.030 | 0.092 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.012 |
| Bibliometrics | 0.014 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".