Banter as transformative practice: linguistic play and joking relationships in a UK swimming club
Bibliographic record
Abstract
This article investigates the multiple interpretations and uses of banter as an inclusive and exclusionary practice amongst competitive youth swimmers in the Southeast of England. As a metacommunicative act, banter is a form of linguistic play that focuses on the ways in which the words are delivered, and the social relationships involved between those engaged in banter. Through an immersive "apprenticeship" within a competitive swimming club from 2018 to 2022, I was party to particular forms of English "humorous" communication and invitations to join in banter with coaches and swimmers. As competitive swimming can be a monotonous activity, with long periods between competitions and nigh endless repetition of training drills, coaches encouraged swimmers' engagement in banter as an inclusive strategy for squad cohesiveness and to stave off boredom throughout the swimming season. Playful teasing was used to invite engagement in banter from one or more people, helping to foster social bonds, develop joking relationships, and create a relaxed atmosphere within training spaces. Mockery and teasing used to initiate banter were also mobilized as exclusionary social positioning strategies to test the limits of social interaction and define oneself against others. This article asserts that despite the nearly-totalitarian position of the coach within high-performance swimming humorous or joking banter does not simply function as a morale-booting activity or as a substitute for active resistance against monotonous training requirements. By paying attention to the intersubjective processes within joking relationships, here through banter, we can see how youth actively navigate sociality and assert their agency within institutional training environments.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.014 | 0.011 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.012 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".