Comparaisons sociales et comparaisons temporelles : vers une approche séquentielle et fonction de la situation unique
Bibliographic record
Abstract
Résumé Les comparaisons sociales et temporelles sont des stratégies d’évaluation de soi qui ont des conséquences sur l’estime de soi personnelle. Dans ce travail, nous proposons que les comparaisons sociales et temporelles suivent une approche séquentielle, où les comparaisons sociales précèdent les comparaisons temporelles. Deux postulats sont proposés et testés. En premier lieu, nous postulons que l’influence des comparaisons sociales ou temporelles dans la prédiction de l’estime de soi personnelle dépendra de la disponibilité perçue des repères sociaux saillants à l’évaluation de soi. En second lieu, nous mettons de l’avant le concept de la situation unique afin d’expliquer le processus psychologique par lequel un individu se détourne des comparaisons sociales vers les comparaisons temporelles pour s’évaluer. Des analyses de régression ont permis de confirmer nos hypothèses et de souligner la pertinence d’une approche séquentielle des comparaisons sociales et temporelles.
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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 | 0.035 | 0.129 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.005 | 0.009 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.019 | 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; 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".