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Record W2905295628 · doi:10.1080/10409289.2018.1548811

How to Support Toddlers’ Autonomy: Socialization Practices Reported by Parents

2018· article· en· W2905295628 on OpenAlexaff
Eftichia Andreadakis, Mireille Joussemet, Geneviève A. Mageau

Bibliographic record

VenueEarly Education and Development · 2018
Typearticle
Languageen
FieldPsychology
TopicChild and Adolescent Psychosocial and Emotional Development
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsPsychologyAutonomyDevelopmental psychologySocializationEmpathyContext (archaeology)ToddlerSocial psychologyScale (ratio)Prosocial behavior

Abstract

fetched live from OpenAlex

Autonomy-supportive parenting is found to foster children’s adjustment but relatively few studies have been conducted with toddlers. In the present exploratory study, parents (N = 182) reported what practices they use when asking their toddlers (M age = 26.9 months) to engage in important yet uninteresting activities. Parents rated twenty-six potentially autonomy-supportive practices, along with a well-known scale measuring the extent to which they have a positive attitude towards autonomy support. Research Findings: Using correlational and factorial analyses, eight practices were identified: various ways to communicate empathy, providing developmentally appropriate rationales, describing the problem in an informational and neutral way, and modeling the requested behavior. This subset of autonomy-supportive practices for toddlers was positively related with toddlers’ rule internalization, providing them with further validity. Practice or Policy: These preliminary findings may be useful in guiding future conceptual, empirical, and applied work on the support of toddlers’ autonomy and its assessment in an emotionally-charged and challenging context.

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)0.001
metaresearch head score (Gemma)0.009
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 score0.007
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.052
GPT teacher head0.349
Teacher spread0.297 · 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

Citations21
Published2018
Admission routes1
Has abstractyes

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