Toward Defining Water Competency: An American Red Cross Definition
Bibliographic record
Abstract
Water competency entails more than a perception of just being able to swim and an operational definition of water competency is necessary for learn-to-swim program evaluation and policy development.To devise an operational definition, members of the American Red Cross Scientific Advisory Aquatic subcouncil surveyed nine key national (United States) organizations, 14 international organizations, and 19 other key informants involved with water safety and swimming activities for their requirements for swimming in the "deep end."The most frequently reported variables included (a) distance swum, (b) floating or treading water, (c) entrance into water unassisted, and (d) exit from the water unassisted.The subcouncil proposed that water competency include the following: (1) entry with total submersion;(2) recovery to the surface and float or tread for at least 1 min; (3) turn 360° and orient toward an exit point; (4) level off and move on front and/or on back position for at least 25 yards; and (5) exit from the water.We note that water competency is influenced by conditions of the aquatic environment (e.g., water temperature, movement, depth) into which the person may be introduced, and that skills demonstrated in one aquatic environment may not transfer to another.Our proposed operational definition for water competency provides an initial framework for an expanded version that may be expanded to be used globally.
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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 | 0.036 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.005 |
| Science and technology studies | 0.005 | 0.007 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.003 | 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".