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Record W1890000327 · doi:10.1080/15295192.2015.1053334

Exploring the Factor Structure of the Revised-Parent as a Social Context Questionnaire

2015· article· en· W1890000327 on OpenAlexaff
Natasha Ann Egeli, W. Todd Rogers, Christina M. Rinaldi, Ying Cui

Bibliographic record

VenueParenting · 2015
Typearticle
Languageen
FieldPsychology
TopicChild and Adolescent Psychosocial and Emotional Development
Canadian institutionsUniversity of AlbertaAlberta Advanced Education
Fundersnot available
KeywordsPsychologyExploratory factor analysisContext (archaeology)Reliability (semiconductor)Style (visual arts)Structural equation modelingSocial environmentDevelopmental psychologyPsychometricsSocial psychologyComputer science

Abstract

fetched live from OpenAlex

SYNOPSISObjective. This study explored the factor structure and provided evidence of the validity and reliability of the Revised Parents as a Social Context Questionnaire. Design. Online surveys were completed by 404 parents of children ages 2–18 years. An exploratory factor analysis and a second-order factor analysis were conducted to generate six subscales (warmth, rejection, structure, chaos, autonomy support, and coercion) and an overall measure of parenting style quality based on Self-Determination Theory. Results. Validity and reliability analyses indicate that the Revised Parents as a Social Context Questionnaire can be used to assess six characteristics of parenting style and how well the overall quality of parenting style addresses the psychological needs of children. Conclusions. The Revised Parents as a Social Context Questionnaire can be used as a valid and reliable measure of parenting style for the present sample. Research is needed to provide additional support for the validity and reliability of this measure with other samples.

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)0.006
metaresearch head score (Gemma)0.015
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.141
GPT teacher head0.323
Teacher spread0.183 · 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 designSimulation or modeling
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

Citations20
Published2015
Admission routes1
Has abstractyes

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