The self‐concepts and perceived competencies of gifted and non‐gifted students: a meta‐analysis
Bibliographic record
Abstract
The current meta‐analysis compares the self‐concepts and perceived competencies of gifted and non‐gifted students. Using meta‐analytic methods to synthesise the results of 40 studies, we found that gifted students scored significantly higher than non‐gifted students on measures of academic and behavioural perceived competence, as well as global self‐concept. Gifted students scored significantly lower than non‐gifted students on measures of appearance and athletic perceived competence. Significant heterogeneity was found in the extent to which gifted and non‐gifted students' scores differed in the academic and global domains. Moderator variables such as participant grade level, method of gifted designation and publication year accounted for systematic differences in these domains. Gifted students' appearance and athletic perceived competencies may benefit from specific intervention, but their beliefs in other areas remain positive.
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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 | 0.014 | 0.034 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.022 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".