Changing the Sports administrative structure according to the sports scientific standard PhD and Master’s degree exclusively to lead the engineering of the operations of the national and international sports institution in light of the background of the events of FIFA 2015
Bibliographic record
Abstract
Sports management is a vital area that plays a crucial role in the development and management of sports activities at the national and international levels. The administrative structures of sports institutions are witnessing increasing challenges, exacerbated by sporting developments and important events that have occurred in the global sports scene, among which is what happened in 2015 in the context of scandals and abuses that followed. (Bishop & Cooper, 2018a) The 2015 FIFA events, which were related to corruption scandals and ethical abuses within the international sports body, cast a shadow over the various sports management structures. The impact of these events was not only local, but extended to international dimensions, igniting the need to reconsider and improve sports management structures in light of scientific standards in the field of sports leadership. (Rowe, 2017b) This study aims to explore and analyse in depth the changes that can be achieved in sports management structures, particularly in the context of leading the engineering of the operations of national and international sports organizations. Emphasis will be placed on reviewing the relevant scientific literature and analysing current management structures to provide a comprehensive assessment of the positive and negative impacts that resulted from the events of FIFA 2015. This study also proposes amendments to sports management structures, based on doctoral and master's standards in sports leadership, with the aim of improving the effectiveness of these structures in crisis management and achieving the objectives of sport in a more comprehensive and robust manner.
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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 | 0.010 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".