Oh Captain, My Captain! Using Social Network Analysis to Help Coaching Staff Identify the Leadership of a National Sports Team
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This case study explores the issue of team leadership among players who have been selected to play for their national team in an international tournament. After the coaching staff had solidified the roster, a total of 12 (fictional) players were chosen to represent Canada Basketball on the senior women’s development team. With some players having known their teammates for only 2 weeks, the coaching staff has asked the team’s analytics specialist to gather data regarding the network of players within the team and present potential captains of the team to the coaching staff. Students will take on the role of the analytics specialist and provide the summary of the analysis to the coaching staff. Specifically, using a social network analysis approach, students will use the team’s network of players to determine which individual players are involved in the team’s leadership structure as captains. The primary objective of this case study is to afford students an opportunity to be acquainted with social network analysis in a sport management setting.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it