MétaCan
Menu
Back to cohort
Record W1973754137 · doi:10.1155/2013/102860

The Father-Child Activation Relationship, Sex Differences, and Attachment Disorganization in Toddlerhood

2013· article· en· W1973754137 on OpenAlexaff
Daniel Paquette, Caroline Dumont

Bibliographic record

VenueChild Development Research · 2013
Typearticle
Languageen
FieldPsychology
TopicAttachment and Relationship Dynamics
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsPsychologyDyadStrange situationTemperamentDevelopmental psychologyToddlerAttachment theorySocial psychologyPersonality

Abstract

fetched live from OpenAlex

The activation relationship theory serves as a complement to Bowlby’s attachment theory to better understand the impact of fathering on child development, focusing primarily on parental stimulation of risk taking and control during children’s exploration. The first aim of this study was to confirm that the activation relationship as assessed with the observational procedure, the Risky Situation, is primarily determined by paternal stimulation of risk taking as assessed by questionnaire. The second aim was to verify the link between the activation relationship and attachment disorganization. The third aim was to verify the existence of a sex difference in father-toddler dyad activation relationships. The Strange Situation procedure and the Risky Situation procedure were conducted with 58 father-toddler dyads. Fathers completed questionnaires on child temperament and parental behavior. Paternal stimulation of risk taking explains activation once child sex and temperament, the attachment relationship, and emotional support are taken into account. Moreover, there is no relation between the father-child activation relationship and attachment disorganization. Finally, data confirm the existence of a sex difference in the activation relationship in toddlers: fathers activate their sons more than their daughters.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.044
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.053
GPT teacher head0.396
Teacher spread0.343 · 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

Citations43
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueChild Development ResearchSame topicAttachment and Relationship DynamicsFrench-language works237,207