Transformations through sport : the case of capoeira and basketball
Bibliographic record
Abstract
The third phase of the AHRC-funded Translation and Translanguaging (TLang) project focuses on the theme of Sport. The Key Participant in Leeds is Tiago from Mozambique who is involved in capoeira and basketball, which gives our case study a dual focus. It should be noted that our analysis of both sets of sessions, capoeira and basketball, while kept roughly in parallel in the report, also reflects the different opportunities and affordances of the activities: capoeira for example provided notable opportunities for participants to learn Portuguese, while there was no such obvious equivalent in basketball. In Section One we introduce the case study, then in Section Two we introduce Tiago and look at the role that basketball and capoeira has played in his transformations and ideological becoming when he was growing up in Mozambique but also since he moved to England. We see how sport has always played a central shaping role in his life. Next in Section Three we introduce the two sports, basketball and capoeira (though as we shall see, capoeira, designated a UNESCO World Heritage treasure, is something more multi-layered than just a sport). In Section Four we review some of the themes that have cut across the TLang case studies so far: the work/home dynamic, the dynamics and politics of space, including borrowed space, entrepreneurship and precarity (finding a place and transforming what one knows, is and can do into something marketable), and finally of course a reflection on sport in relation to the core themes of our project, translanguaging, mobility, globalization and superdiversity. We show how Tiago, caught in the trap of precarious hourly paid work, is striving to transform an activity he loves, capoeira, into something he could earn a living by. The challenge of the Sports case study methodologically lay in the fact that we were dealing with highly visual data which could only really be captured on video. Additionally, due to difficulties in sound recording we were further led to consider the dynamic interaction of visual, verbal and embodied action rather than extensive analysis of spoken data. In Section Five we therefore focus on methodological issues concerned with obtaining and working with such visual data. In the first part of Section Six, we look at the event structure of both capoeira and basketball sessions, then go on to provide more detailed analysis of video data. In the case of capoeira we focus on the roda stage, which is the culmination of each session; in the case of basketball, we look at the lead up to an actual game: warm up, practice and strategy setting. In the final part of this section we look at the language learning opportunities afforded by participation in the capoeira group, and interaction both in English and Brazilian Portuguese with a marked Afro-Brazilian inflection. This is both through the songs and chants that are characteristic of capoeira, but also the language of instruction and regulation of the activity, where Portuguese/English translanguaging is often in evidence. In Section Seven we briefly conclude the case study.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.042 | 0.028 |
| Scholarly communication | 0.011 | 0.005 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.009 | 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".