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Record W2588987874 · doi:10.1002/ajim.22684

Risk of work injury among adolescent students from single and partnered parent families

2017· article· en· W2588987874 on OpenAlexafffundabout
Imelda S. Wong, F. Curtis Breslin

Bibliographic record

VenueAmerican Journal of Industrial Medicine · 2017
Typearticle
Languageen
FieldMedicine
TopicInjury Epidemiology and Prevention
Canadian institutionsInstitute for Work & Health
FundersOak Ridge Institute for Science and EducationInstitute for Work and Health
KeywordsMedicineSingle parentLogistic regressionInjury preventionOccupational safety and healthHuman factors and ergonomicsSuicide preventionFamily medicinePoison controlDemographyGerontologyEnvironmental healthDevelopmental psychologyPsychologyInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Parental involvement in keeping their children safe at work has been examined in a handful of studies, with mixed results. Evidence has suggested that non-work injury risk is higher among children from single-parent families, but little is known about their risk for work-related injuries. METHODS: Five survey cycles of the Canadian Community Health Survey were pooled to create a nationally representative sample of employed 15-19-year old students (N = 16,620). Multivariable logistic regression estimated the association between family status and work injury. RESULTS: Risk of work-related repetitive strains (OR:1.24, 95%CI: 0.69-2.22) did not differ by family type. However, children of single parents were less likely to sustain a work injury receiving immediate medical care (OR:0.43, 95%CI: 0.19-0.96). CONCLUSION: Despite advantages and disadvantages related to family types, there is no evidence that work-related injury risk among adolescents from single parent families is greater than that of partnered-parent families. Am. J. Ind. Med. 60:285-294, 2017. © 2017 Wiley Periodicals, Inc.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.022
Threshold uncertainty score0.044

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.071
GPT teacher head0.371
Teacher spread0.300 · 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 source (direct Gemma or distilled Codex), 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

Citations8
Published2017
Admission routes3
Has abstractyes

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