New Media, Social Movements, and Global Sport Studies: A Revolutionary Moment and the Sociology of Sport
Bibliographic record
Abstract
By considering three main questions, this article develops an argument for rethinking existing approaches to understanding both sport-related social movements and “local” responses to globalizing forces in light of the emergence of Internet communication. They are: (a) How can extant conceptions of sport-related social movements be expanded to account for more advanced forms of cultural and political opposition that result from and are potentially enhanced by the Internet? (b) How does the link between the development of the Internet and the enhanced formation and functioning of (new) social movements offer a foundation from which to expand understandings of relationships between global sport-related influences and the responses of local cultures? (c) What methodological approaches are best suited for studying Internet-related forms of sport-related activist resistance? The article concludes that recent developments in communication technology have contributed to a situation in which there is immense revolutionary potential in sport-related contexts, and for sociologists (of sport) interested in contributing to activist projects.
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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.003 | 0.043 |
| Scholarly communication | 0.011 | 0.014 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".