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Record W4312404945 · doi:10.1590/1413-82712025270304

Inventory of Father Involvement and Fathers’ Perceptions of Family Life

2022· article· en· W4312404945 on OpenAlexaff
Lígia de Santis, Elizabeth Joan Barham, Susan S. Chuang

Bibliographic record

VenuePsico-USF · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicFamily Dynamics and Relationships
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsSocioemotional selectivity theoryPsychologyDevelopmental psychologyPerceptionClinical psychology

Abstract

fetched live from OpenAlex

Abstract Cross-cultural comparisons of father involvement and related issues are still scarce, as are consolidated measures for its assessment. We examined relationships among father involvement and family-related variables, in Brazil, and then compared these results with findings from other countries. In total, 200 fathers with children aged 5 to 10 completed the Brazilian version of the Inventory of Father Involvement (IFI-BR), and measures of stress, marital satisfaction, parent-child relationship, children’s social skills and their behavior problems. Correlations among these variables were between .32 and .58, providing new evidence of validity for the IFI-BR. When comparing Brazilian results with correlations observed in other countries, the majority did not differ in magnitude, indicating that father involvement systematically influences the fathers’ well-being, family relationships, and their children’s socioemotional development, in different countries. In addition to the psychometric evidence for the IFI-BR, these results also indicate the potential for using the IFI in different cultures.

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)0.002
metaresearch head score (Gemma)0.005
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 score0.002
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.049
GPT teacher head0.294
Teacher spread0.245 · 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

Citations7
Published2022
Admission routes1
Has abstractyes

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