Vers un ‘ <i>Breaking</i> fédéral et olympique’ : genèse d’une discipline sportivo-artistique engagée dans une nouvelle étape de sportification controversée face à l’enjeu de préservation culturelle
Bibliographic record
Abstract
The inclusion of Breaking in the Olympic and Paralympic Games has generated internal reactions: How do the actors of French Breaking position themselves faced with the sudden and additional phase of sportification of their practice? The authors propose a recontextualization of the national and political registration of this practice, which is marked by three forms of institutionalization: first, socio-cultural, then cultural, and finally sporting. The field investigation (2019–2023) shows hip-hop actors, transmitters of a conventional sporting-artistic heritage, not fully adhering to the new “Olympic Breaking.” Some are trying to support federalization, which is favorable to the existence of cultural permanence at the organizational level of this new format. Changes have also been brought about. To understand them, particular interest is focused on the organizational specificities of “underground” Break battles, and on the “committed” positions of “recognized” hip-hop actors faced with the uncontrolled introduction of their culture into the Games.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.015 |
| Scholarly communication | 0.010 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 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".