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Record W4393260060 · doi:10.1037/fam0001214

Developmental trajectories of mother–adolescent agreement on maternal autonomy support and their contributions to adolescents’ adjustment.

2024· article· en· W4393260060 on OpenAlexfundno aff
Catherine F. Ratelle, André Plamondon, David Litalien, Stéphane Duchesne

Bibliographic record

VenueJournal of Family Psychology · 2024
Typearticle
Languageen
FieldPsychology
TopicFamily and Disability Support Research
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of CanadaFonds de Recherche du Québec-Société et Culture
KeywordsPsychologyAutonomyDevelopmental psychologyAgreementAdolescent developmentSocial relationSocial psychology

Abstract

fetched live from OpenAlex

= 745 mother-child dyads). Each year, mothers and adolescents completed a questionnaire assessing maternal autonomy support. In both the samples, results of growth mixture modeling showed from mothers' perspective the presence of two distinct trajectories: high (91% of the sample) and moderate and relatively stable (9%) trajectories. From the adolescents' perspective, three trajectories were identified: high and relatively stable (75.7%), high and decreasing (11.8%), and moderate and increasing (12.5%). The normative mother-adolescent convergence pattern was one in which both adolescents and their mother reporting high levels of autonomy support. It was generally associated with more positive indices of adjustment, although academic achievement was highest when adolescents reported comparatively more autonomy support than their mother. The worst mother-adolescent convergence pattern tended to be one in which both reported initially moderate levels of autonomy support that remained relatively stable for mothers and increased for youths. Implications for parenting research and interventions are discussed. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.567
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.052
GPT teacher head0.388
Teacher spread0.336 · 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.

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

Citations1
Published2024
Admission routes1
Has abstractyes

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