Bibliographic record
Abstract
Aim. A narrative review of the research results of the multi-aspectual phenomenon of sports talent by researchers from various research centers around the world. Basic procedures. Analysis and synthesis in a narrative review of various methodological concepts regarding research on sports talent, with particular notice of selected American (USA), Canadian, Dutch, German (DDR) and Soviet (USSR) stances. Results. The commonly accepted approach presupposes the division of long-term preparation into a number of stages, at which various age and sport-specific tasks are solved, and young athletes overcome appropriate phases of their giftedness and talent evaluation. The objective difficulties in Talent Identification (TI) are associated with variations in the rate of maturation and unevenness of biological and sport-specific development of young prospects. Serious restrictions regarding early evaluation of giftedness and talent are associated with the lack of psychological measures and insufficient attention paid to personality traits that, to a great extent, determine the achievement of exceptional performance. Talent Identification (TI) in team sports requires more sensitive tests for prediction of successful game activity; such an item as fatigue tolerance was not taken into account by training experts and analysts. Main findings. 1. Athletic Talent is a complex, multifaceted phenomenon that is widely considered from methodological, biological, philosophical and social positions; 2. The methodological foundation can be considered the basic background for general comprehension of the problem and fulfilment of various scientific and practical projects directed towards the recognition, identification and promotion of talented individuals.
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 | 0.112 | 0.159 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.005 | 0.031 |
| Scholarly communication | 0.018 | 0.013 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.007 | 0.007 |
| Insufficient payload (model declined to judge) | 0.003 | 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".