Bibliographic record
Abstract
This book examines the interplay between football, politics, violence, passion, and morality in Argentina. Drawing on original ethnographic research, it considers the role of fans, club officials, politicians, and others in the spread and perpetuation of corruption and violence within football and in wider Argentinian society. Argentina’s triumph in the 2022 World Cup brought millions onto the streets of Buenos Aires in celebration, but this book argues that beneath the veneer of sporting success lie networks of power and practices that have naturalized corruption and violence within Argentinian football and, by extension, in Argentinian society as a whole. It shows how the actions of club officials, politicians, barras (groups of organized, violent fans), and the police, which together represent a system of clientelism, exemplify in the world of football the system of organized chaos that habitually defines Argentinian politics. With the barras given licence to engage in violent behaviours linked not only to sporting passion but also to economic and political interests, this book argues that football, politics, and violence have become entangled in a web of social relations that illustrate Argentina’s struggle to break the vicious cycle of corruption and impunity. Shining new light on the significance of sport in wider society and the centrality of football in one of the world’s greatest footballing nations, this book is essential reading for anybody with an interest in the anthropology, sociology, politics, or history of sport, or in political science, corruption, or Latin American studies.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".