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Record W4205465932 · doi:10.1371/journal.pone.0262175

Identifying risk factors and implications for beach drowning prevention amongst an Australian multicultural community

2022· article· en· W4205465932 on OpenAlexaboutno aff
Mark Woods, William Koon, Robert W. Brander

Bibliographic record

VenuePLoS ONE · 2022
Typearticle
Languageen
FieldMedicine
TopicInjury Epidemiology and Prevention
Canadian institutionsnot available
Fundersnot available
KeywordsWater safetyGeographyPsychological interventionRip currentMulticulturalismQuarter (Canadian coin)Occupational safety and healthSocioeconomicsFisheryPsychologyMedicineEcologyShoreSociologyArchaeologyNursing

Abstract

fetched live from OpenAlex

Multicultural communities in Australia are recognised as a priority area for drowning prevention, but no evidence-based study has addressed their knowledge of beach safety. This study used an online survey tool to identify and examine risk factors relating to swimming ability, beach visitation characteristics and behaviour, and beach safety knowledge of the Australian Southern Asian community to assist in the development of future beach safety interventions. Data was obtained through 249 online and in-person surveys of people aged > 18 years. Most respondents reported poor swimming ability (80%), often swam in in the absence of lifeguards (77%), did not understand the rip current hazard (58%), but reported that they entered the water (76%) when visiting beaches. Close to one-quarter (28%) had not heard, or didn't know the purpose, of the red and yellow beach flags, which identify lifeguard supervised areas on Australian beaches. Length of time living in Australia is an important beach safety consideration for this community, with minimal differences in terms of gender and age. Those who have lived < 10 years in Australia visit beaches more frequently and are less likely to have participated in swimming lessons, be able to swim, heard of the flags or swim between them, understand rip currents, or have participated in a beach safety program. Very few (3%) respondents received beach safety information from within their own community. The importance of beach safety education and swimming lessons within the Southern Asian community should be prioritised for new and recent migrants to Australia.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.057
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.207
GPT teacher head0.383
Teacher spread0.177 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations33
Published2022
Admission routes1
Has abstractyes

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