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Record W4391999614 · doi:10.1080/03004430.2023.2283693

Validation of a revised parental phubbing scale for parents of young children in China

2024· article· en· W4391999614 on OpenAlexaff
Juan Li, Yue Jiang, Bowen Xiao, Jingyao Wang, Qing Zhang, Weifang Zhang, Yan Li

Bibliographic record

VenueEarly Child Development and Care · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicChild Development and Digital Technology
Canadian institutionsCarleton University
Fundersnot available
KeywordsPsychologyDevelopmental psychologyScale (ratio)ChinaEarly childhood educationGeography

Abstract

fetched live from OpenAlex

To examine the reliability and validity of revised Parental Phubbing Scale (PPS) and measure the level of parental phubbing, 701 Chinese children aged 3–6 years and their parents were investigated. The results indicated that (1) the construct validity of the PPS was supported by the best-fit one-factor model; (2) concurrent validity was established by demonstrating that the PPS was positively related to parental smartphone addiction; (3) the PPS was positively correlated with authoritarian parenting style, established the predictive validity; (4) internal reliability was satisfactory. The results also showed that fathers’ and mothers’ phubbing were at the intermediate level; moreover, phubbing levels were highest among parents aged 31–40. The findings conclude that PPS can be used as a reliable and valid measure to evaluate parents’ phubbing and also highlight the need for further research on mothers’ and fathers’ phubbing.

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)0.005
metaresearch head score (Gemma)0.010
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 score0.015
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.010
GPT teacher head0.256
Teacher spread0.247 · 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

Citations7
Published2024
Admission routes1
Has abstractyes

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