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Record W2809737169 · doi:10.5539/jedp.v8n2p68

Risk and Resilience Factors of Divorce and Young Children’s Emotional Well-Being in Greece: A Correlational Study

2018· article· en· W2809737169 on OpenAlexvenueno aff
Christina Karela, Konstantinos Petrogiannis

Bibliographic record

VenueJournal of Educational and Developmental Psychology · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicFamily Dynamics and Relationships
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyFeelingDevelopmental psychologyPsychological resilienceHostilityIntervention (counseling)Parenting stylesClinical psychologySocial psychology

Abstract

fetched live from OpenAlex

This study examined the relation between some of the major risk and protective factors of divorce and young children’s (4 to 7 years old) emotional well-being by adοpting an ecosystemic approach based on Bronfenbrenner’s theory and Kurdek’s model of divorce. Children’s well-being was assessed by a set of components such as attention, emotional and behavioural regulation, ability to take initiatives, positive relationships with others, parents’ sensitive response to child’s needs and cooperation with school. The study was conducted with a representative sample of 130 divorced parents from different regions in Greece. The questionnaire comprised of a cluster of scales and was completed by the custodial parent. Data supported that parent-child affective relationship, supportive co-parenting, parent’s life satisfaction and the availability of supportive social groups were positively correlated to children’s emotional well-being. On the other hand, pre-divorce intra-parental hostility, conflicts between the custodial parent and the child and child’s feeling of rejection were related to less favourable developmental outcomes according to parental perception. Τhe findings are discussed through the prism of the crucial role that divorce related factors play on the developmental process and their implications to divorce intervention programs.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.274

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.016
GPT teacher head0.327
Teacher spread0.311 · 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

Citations9
Published2018
Admission routes1
Has abstractyes

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