COMPARISON OF SPORTS MANAGEMENT SYSTEMS ON THE INTERCONTINENTAL AXIS (USA-GERMANY-CHİNA-AUSTRALİA-CANADA-TURKEY)
Bibliographic record
Abstract
In order to improve the sports development in Turkish society and to be among the successful countries in sports, it is a necessity for sports management systems to benefit from the sports management systems of developed countries in the world. For this reason, it is considered useful to investigate and examine the sports management systems that affect the development in sports and to benefit from the results, to compare them with the sports management system applied in our country and to direct sports practices. These views and practices make it necessary to compare sports management systems. Comparative sports management studies are a descriptive study in the survey model for the qualitative comparison of similar and different aspects of different structures and operations related to sports management of countries. A descriptive approach was used in the study. Documentary scanning technique is used to collect data. It has been examined and summarized by taking into account four variables related to the "sports management systems, financing budget allocated to sports, participation in sports and sports policies" of countries that are successful in international sports organizations in the world. It has been concluded that the examined countries generally have different management systems and socio-economic structures. In Europe, sport is considered part of the welfare state. It turns out that in the European country under review, sports financing related to direct expenditures is closely linked to governments. Participation rates in sports may differ between countries. It is observed that in the sports policies of the 6 countries examined, there is a clear focus on "Sports for All" and "High Performance Sports". Undoubtedly, sports culture has an important function in the implementation of the country's sports policies.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".