Survey of Public Knowledge and Responses to Educational Slogans Regarding Cold-Water Immersion
Bibliographic record
Abstract
OBJECTIVES: Cold water temperature is a significant factor in North American drownings. These deaths are usually attributed to hypothermia. Survey questions were administered to 661 attendees of cold-stress seminars-including medical, rescue, law enforcement and lay attendees-to determine general knowledge of the effects of ice water immersion and responses to 2 public service educational slogans. METHODS: Five questions were posed at the beginning of seminars to 8 groups (ranging in size from 46 to 195) during a 2-year period. Pi(2) analyses were used to determine if responses within any occupational category differed from the group responses. RESULTS: A high portion of respondents greatly underestimated the time to become hypothermic in ice water (correct answer >30 minutes; 84% stated 15 minutes or less) and the time until cooling was life threatening (correct answer >60 minutes; 85% stated 30 minutes or less). There were no occupational differences in these responses. Most of the respondents identified a correct cause of death during cold stress (81% stated cardiac arrest, hypothermia, or drowning). Although both educational slogans had some advantages, between 40% (Slogan #1) to 50% (Slogan #2) of respondents did not respond correctly. CONCLUSIONS: The majority of respondents underestimated the time available for survival during ice water immersion. It is important to educate the public accurately to decrease the probability of panic under these circumstances. More work is required to develop effective educational slogans that provide proper information and actions for victims of cold-water immersion.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".