An Examination into the Underlying Factors that Promote the Effectiveness
Bibliographic record
Abstract
The growth of competitive collegiate women’s sports and specifically, women’s soccer, in the collegiate, professional, and national realms has not been matched by research in the field. Currently, there are courses, conventions, and literature about all different aspects of soccer, but the field of collegiate coaching is missing detailed education about the holistic influences and aspects of creating a winning women’s collegiate soccer program. The purpose of this qualitative case study was to discover which major factors influence the effectiveness of a National Collegiate Athletic Association (NCAA) Division I women’s soccer program to consistently win. Data and analysis yielded four major factors. The first major factor is the university which includes four aspects: financial support, supportive management and collaborative colleagues, standard of excellence, and university reputation. The second major factor is recruiting, which includes two aspects: talent and right-fit. The third major factor is development, which includes four aspects: player development, person development, coach development, and team development. The fourth major factor is head coach drive which has three aspects: head coach evolution, head coach confidence, head coach fear of failure. Results produced practical application for current collegiate women’s soccer coaches to analyze strengths and weaknesses within their programs.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".