Rolling with the Flow: An Enactive Ethnography of Embodied Emotional Socialization in Brazilian Jiu Jitsu
Bibliographic record
Abstract
This dissertation explores Brazilian Jiu Jitsu training at 2 gyms: Mixed Martial Arts Academy (Toronto, Canada) and Team Gracie BJJ (Rio de Janeiro, Brazil). Drawing on enactive ethnography, the dissertation deepens sociological understanding of embodied processes of socialization and emotion work. The first paper advances the concept of “social calibration” to elucidate the embodied processes through which new Brazilian Jiu Jitsu practitioners in Toronto learn to align their intensity levels with prevailing training norms. It examines how intensity breaches are managed by experienced practitioners and highlights how, through social calibration, practitioners either transgress or reinforce broader gender norms and expectations. The second paper takes a comparative approach, unpacking the relationship between social environments and structures inside and outside the gym, and the embodiment of habitus at the individual level. It uncovers how the unique social contexts in Rio de Janeiro and Toronto lead practitioners at each site to develop varying levels of anticipated violence, which in turn shape how they understand, embody, and choose to show, hide or apply their BJJ practitioner training and identities. The final paper elaborates the concept of “emotional base work” to illustrate how practitioners in Rio de Janeiro learn to establish and maintain a strong emotional base from which to withstand the pull of emotionally heightened situations, and maintain emotional stability and resilience when facing challenges both inside and outside of the gym. Taken together, this dissertation uses Brazilian Jiu Jitsu as a case study to raise new empirical and theoretical insights into the micro-interactional, embodied processes though which social actors develop the social and emotional competency needed to navigate contexts of interactional risk and adversity.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.009 | 0.012 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".