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Record W2346162079 · doi:10.25035/ijare.04.03.06

Watching Parents, Watching Kids: Water Safety Supervision of Young Children at the Beach

2010· article· en· W2346162079 on OpenAlexaboutno aff
Kevin Moran

Bibliographic record

VenueInternational Journal of Aquatic Research and Education · 2010
Typearticle
Languageen
FieldMedicine
TopicInjury Epidemiology and Prevention
Canadian institutionsnot available
FundersUniversity of Auckland
KeywordsQuarter (Canadian coin)Water safetySunbathingPsychologyIntervention (counseling)NursingMedical educationMedicineGeography

Abstract

fetched live from OpenAlex

The number of children who drown at open-water locations such as surf beaches increases with age. In New Zealand, from 1980-2002, 70% of 5-9-year-olds (n = 71) drowned in open water locations. Little is known about parental supervision of young children at beaches. The purpose of this paper is to report on exploratory observations of caregiver supervision of children at the beach. Two experienced lifeguards were trained to observe caregiver water safety supervisory behaviors at 18 popular beaches in the summer of 2006/7. Of the 544 observations made, one quarter (24%) of children in the water were not considered to be adequately supervised. Most supervision (74%) was done by a single person irrespective of the number of children under their control. Of the 130 caregivers failing to provide adequate supervision, one third (30%) lay on the beach sunbathing, one quarter (28%) talked to others, and one quarter (27%) used cell phones. In light of these findings, recommendations about further research and safe supervision practices by parents/caregivers are suggested. Water safety organizations need to develop and promote guidelines for the safe supervision of young children at beaches.

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)0.005
metaresearch head score (Gemma)0.001
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 score0.155
Threshold uncertainty score0.310

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.033
GPT teacher head0.412
Teacher spread0.378 · 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

Citations23
Published2010
Admission routes1
Has abstractyes

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