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Record W2017196434 · doi:10.1111/mbe.12061

Determinants of Sleep Duration Among High School Students in Part‐Time Employment

2014· article· en· W2017196434 on OpenAlexaffabout
Luc Laberge, Élise Ledoux, Julie Auclair, Marco Gaudreault

Bibliographic record

VenueMind Brain and Education · 2014
Typearticle
Languageen
FieldPsychology
TopicSleep and Work-Related Fatigue
Canadian institutionsInstitut de recherche Robert-Sauvé en santé et en sécurité du travailUniversité de SherbrookeCégep de JonquièreUniversité du Québec à Chicoutimi
FundersNational Institute for Occupational Safety and Health
KeywordsDuration (music)Sleep deprivationSleep (system call)Stepwise regressionOccupational safety and healthPsychologyRegression analysisMedicineDemographyGerontologyPsychiatryCognitionSociology

Abstract

fetched live from OpenAlex

ABSTRACT Adolescents who work while attending school are reported to sleep less than those who do not. This study aimed to identify factors associated with short sleep duration in students who work during the school year. A cross‐sectional survey aiming to describe working conditions and occupational safety and health was completed by representative samples of Quebec high school students aged 12–19 years from three administrative regions (n = 3,871). A multiple stepwise regression analysis was performed with sleep duration as the dependent variable, and sociodemographic, school, occupational, and health factors as potential explanatory variables. Significant factors associated with shorter sleep duration were later bedtimes (p < .001), shorter weekend oversleep (p < .001), higher physical work factors related to handling efforts (p < .001), and female gender (p < .01). Addressing work conditions of student workers may help prevent sleep deprivation. Special efforts should also target girls combining work and study.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.142
Threshold uncertainty score0.281

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.011
GPT teacher head0.307
Teacher spread0.297 · 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

Citations4
Published2014
Admission routes2
Has abstractyes

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