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Record W2071348755 · doi:10.1080/00221325.2014.926264

Concordance Between the Quality of Maternal and Paternal Parenting Behavior Within Couples

2014· article· en· W2071348755 on OpenAlexafffund
Marie Deschênes, Annie Bernier, Véronique Jarry‐Boileau, Diane St‐Laurent

Bibliographic record

VenueThe Journal of Genetic Psychology · 2014
Typearticle
Languageen
FieldPsychology
TopicChild and Adolescent Psychosocial and Emotional Development
Canadian institutionsUniversité du Québec à Trois-RivièresUniversité de MontréalUniversité du Québec à Montréal
FundersCanadian Institutes of Health Research
KeywordsConcordancePsychologyDevelopmental psychologyToddlerSocioeconomic statusSimilarity (geometry)Quality (philosophy)DemographyMedicinePopulation

Abstract

fetched live from OpenAlex

There is compelling evidence that the quality of maternal and paternal parenting behavior bears critical importance for child development. Yet, less is known of the degree of similarity between maternal and paternal parenting behavior in families, and especially little is known about the factors that may explain variation in degrees of similarity. This article aims to examine (a) the concordance (similarity) between the quality of mothers' and fathers' interactive behavior with their child and (b) the sociodemographic determinants of this concordance. The sample included 74 families (mother, father, and their child). The quality of maternal and paternal interactive behavior was assessed independently, and rated with the Maternal Behavior Q-Sort (mother-infant, 12 months; D. R. Pederson et al., 1990) or the Mutually Responsive Orientation scale (father-toddler, 18 months; N. Aksan et al., 2006). The results indicated that the overall correlation between the quality of mothers' and fathers' behavior was moderate. The concordance was greater among higher socioeconomic status families or when interacting with a boy, but did not differ according to the presence or absence of siblings in the family.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.037
Threshold uncertainty score0.272

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.052
GPT teacher head0.358
Teacher spread0.306 · 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 teacher head, 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

Citations13
Published2014
Admission routes2
Has abstractyes

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