Empirical Investigations of Creativity and Giftedness in Mathematics: An International Perspective
Bibliographic record
Abstract
The idea for this book originated at the first joint meeting of the Korean Mathematical Society and the American Mathematical Society, held in Seoul, South Korea, on December 16–20, 2009. Contributing authors from Sweden, Norway, Turkey, Israel, Iran, China, Canada, South Korea, and the United States provide international perspectives on creativity and giftedness in mathematics education. The vast majority of the book is comprised of reports from empirical studies. In this respect, the book is not theory driven, per se. Instead, the focus is on reporting findings from studies in an attempt to elucidate the relationship between giftedness and creativity in mathematics. In this review, I provide a brief synopsis of each chapter (except Chapter 1, which outlines the book) and discuss the relevance of the work to the literature on mathematical creativity and giftedness. The overview of the chapters is followed by general remarks on the state of mathematics education research on creativity and giftedness and final thoughts about the contribution of this book to the field.
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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".