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Record W1935597553 · doi:10.1089/chi.2013.0038

Contemporary Research on Parenting: Conceptual, Methodological, and Translational Issues

2013· article· en· W1935597553 on OpenAlexaff
Thomas G. Power, Ester F. C. Sleddens, Jerica M. Berge, Lauren Connell, Bert Govig, Erin Hennessy, Leanne Liggett, Kimberley M. Mallan, Diane Santa Maria, Angela Odoms‐Young, Sara M. St. George

Bibliographic record

VenueChildhood Obesity · 2013
Typearticle
Languageen
FieldPsychology
TopicChild and Adolescent Psychosocial and Emotional Development
Canadian institutionsMcGill University
FundersEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Institute of Diabetes and Digestive and Kidney DiseasesNational Institute on Drug Abuse
KeywordsChildhood obesityParenting stylesPsychologyDevelopmental psychologyPsychological interventionEthnic groupTranslational researchObesityMedicineOverweightSociologyPsychiatry

Abstract

fetched live from OpenAlex

Researchers over the last decade have documented the association between general parenting style and numerous factors related to childhood obesity (e.g., children's eating behaviors, physical activity, and weight status). Many recent childhood obesity prevention programs are family focused and designed to modify parenting behaviors thought to contribute to childhood obesity risk. This article presents a brief consideration of conceptual, methodological, and translational issues that can inform future research on the role of parenting in childhood obesity. They include: (1) General versus domain specific parenting styles and practices; (2) the role of ethnicity and culture; (3) assessing bidirectional influences; (4) broadening assessments beyond the immediate family; (5) novel approaches to parenting measurement; and (6) designing effective interventions. Numerous directions for future research are offered.

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)0.158
metaresearch head score (Gemma)0.239
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.842
Threshold uncertainty score0.836

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1580.239
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0080.014
Science and technology studies0.0040.031
Scholarly communication0.0090.009
Open science0.0040.006
Research integrity0.0030.005
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 head0.283
GPT teacher head0.426
Teacher spread0.143 · 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 designTheoretical or conceptual
DomainMethods
GenreReview

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

Citations75
Published2013
Admission routes1
Has abstractyes

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