The Identification of Giftedness in Children: A Systematic Review
Bibliographic record
Abstract
This systematic review aims to provide a comprehensive and up-to-date overview of the most effective identification protocols used to detect giftedness in primary school students, intended to be used by teachers, parents, and diagnostic professionals. This review, registered in PROSPERO (CRD420251064093), analyzed studies published between 2019 and 2024 in the PsycINFO, Web of Science, and Scopus databases. It included articles published in English or Spanish and focused on multidisciplinary fields. A total of 17 studies were selected and evaluated for quality using the Newcastle–Ottawa Scale. The findings highlight the effectiveness of using multiple tools in the identification process, grouped into teacher nominations, family nominations, and tools for diagnostic professionals. This multidimensional approach helps reduce false negatives and supports the identification of underrepresented and twice-exceptional students. In conclusion, the identification of giftedness should be grounded in methods that prioritize general cognitive abilities over IQ scores and academic achievements.
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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 | 0.020 | 0.091 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.006 |
| Bibliometrics | 0.016 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".