Heath: Learning to Swim: Age Group Swim Clubs and Embodied Identity in Canada
Bibliographic record
Abstract
Activation involves loosening up joints and muscles by swinging arms and legs through their full range of motion. Most warm-up routines are designed to get blood flowing to areas not used outside of the water, which can help prevent injury. Children take full advantage of these moments to socialize by catching up on the day's school activities and discussing what will or has happened on their precious days off and while away from their peers. Here is a place where children bond, make closer friendships within their groups, and establish a sense of belonging. It is during the pre-workout activation sessions and the post-workout mandatory stretching that children often exhibit the varying levels of a swimmer's embodied identity. Some have bought into the training regimes required of them, while others pretend and put on a show of complying with the demands of the club and coach they are attached to. Age group club swimming can be far more than a recreational activity that parents put their children into. It can include a large assortment of activities and practices that range from the developmental club enrolled swimmer to that of competitive international podiums. Inside these fields, identity is contested and shaped and bodies are subjected to regimes of discipline and training, all in the attempt to form individuals who will embody the identity of their sport in and out of the pool.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.021 | 0.006 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 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".