Pour une meilleure compréhension de l’estime de soi : liens entre la perception de soi et les indicateurs sociométriques
Bibliographic record
Abstract
L’objectif de cette recherche est d’explorer les liens entre l’estime de soi et les différents indicateurs sociométriques. Nous avons utilisé le questionnaire Reflet permettant ainsi de prendre en compte les perceptions de l’élève quant à ses relations dans la classe. Les analyses effectuées, portant sur un échantillon de 263 élèves, indiquent que le statut sociométrique imaginé apporte un élément supplémentaire à la compréhension de l’estime de soi dans le domaine social. Si les sympathies réciproques entre camarades dans la classe constituent un facteur important dans la construction de l’image de soi, nos résultats soulignent le caractère prédominant de la perception qu’a l’élève des relations qu’il entretient avec ses pairs.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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; both teacher heads agree on what is shown here.
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".