Futebol masculino nos Jogos Olímpicos: a mudança do perfil dos medalhistas a partir da limitação de idade nos Jogos Olímpicos de Barcelona-1992
Bibliographic record
Abstract
The most popular sport on the planet has always had questioned participation in the Olympic Games. In practically all sports, being in the Olympic Games represents the pinnacle for the sport and, obviously, for the athletes. After all, it's a great opportunity to introduce yourself to people who don't have access to that modality on a daily basis. That doesn't happen with football. In most countries, football is part of people's routine. In addition, football has its main competition: the FIFA World Cup. Even so, it was present in most editions. At first, in a very modest way, then with a wide domination of the countries of the European socialist bloc. However, from 1992 onwards, there was an important change in the profile of the medalists, precisely when the rule of the age of participation of the athletes was changed: only athletes up to 23 years old could compete in the Olympic Games. This change takes away the European protagonism and transfers most of the medals to countries in Latin America and Africa. This work aims to analyze the reasons for this new configuration of the medalists. It is hypothesized that countries with expressive results in grassroots competitions (under-17 and under-20) have more advantages in a competition that has this age limitation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".