The effect of distance to elite sport teams on talent development in German handball players
Bibliographic record
Abstract
The proximity of youth athletes to elite sport teams has been shown to have positive developmental effects in Canadian, Irish and Danish athletes (Farah et al., 2018; Finnegan et al., 2016; Rossing et al., 2018). However, this effect has not been explored in Germany; a country that is much different in its geospatial and sport-systematic nature. The purpose of this study was twofold: a- to explore the influence of distance from birthplace and first club to elite sport teams on selection into the youth national handball team, and b- to examine the long-term effects of distance on the league-level reached years later. Birthplace and first club data were collected for 60 female and 36 male athlete selected into the national youth program, as well as 59 female and 34 male athletes whom were not. Results showed that selected male athletes were closer to elite teams than their non-selected counterparts; however, only distance from birthplace to sex-specific second-division teams reached significance (p = .04, d = .52). As for female athletes, there were no differences in distance between the two groups. In regards to our second objective, distances from birthplace and first clubs to first-division teams significantly varied across league levels but in no particular pattern (p
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".