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Peer Review #2 of "Family structure as a predictor of screen time among youth (v0.2)"

2015· peer-review· en· W4252684661 on OpenAlexaboutno aff
A Beck

Bibliographic record

Venuenot available
Typepeer-review
Languageen
FieldSocial Sciences
TopicEducation, Sociology, Communication Studies
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyScreen timeDevelopmental psychologyMedicineInternal medicine

Abstract

fetched live from OpenAlex

The family plays a central role in the development of health-related behaviors among youth.The objective of this study was to determine whether non-traditional parental structure and shared custody arrangements predict how much time youth spend watching television, using a computer recreationally, and playing video games.Participants were a nationally representative sample of Canadian youth (N = 26,068) in grades 6-10 who participated in the 2009/10 Health Behaviour in School-aged Children Survey.Screen time in youth from single parent and reconstituted families, with or without regular visitation with their non-residential parent, was compared to that of youth from traditional dualparent families.Multiple imputation was used to account for missing data.After multiple imputation, the relative odds of being in the highest television, computer use, video game, and total screen time quartiles were not different in boys and girls from non-traditional families by comparison to boys and girls from traditional dual-parent families.In conclusion, parental structure and child custody arrangements did not have a meaningful impact on screen time among youth.

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)0.017
metaresearch head score (Gemma)0.172
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Evaluation · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.983
Threshold uncertainty score0.867

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0170.172
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0070.004
Science and technology studies0.0040.002
Scholarly communication0.0070.003
Open science0.0040.004
Research integrity0.0030.001
Insufficient payload (model declined to judge)0.2590.112

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 head0.193
GPT teacher head0.461
Teacher spread0.269 · 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.

Study designNot applicable
DomainEvaluation
GenreOther

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

Citations0
Published2015
Admission routes1
Has abstractyes

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