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Record W3177695764 · doi:10.1111/jftr.12424

Ethnic and diverse fathering: Moving research forward

2021· article· en· W3177695764 on OpenAlexaff
Susan S. Chuang, Jay Fagan

Bibliographic record

VenueJournal of Family Theory & Review · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicFamily Dynamics and Relationships
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsEthnic groupDiversity (politics)ImmigrationRelevance (law)SociologyCultural diversityPsychologySocial psychologyDevelopmental psychologyPolitical scienceAnthropology

Abstract

fetched live from OpenAlex

Abstract Fathering in the 21st century has gained significant prominence among scholars who have acknowledged the relevance of fathers in families. However, our understanding of diverse fathering in various contexts such as immigrant and ethnic minority contexts, “nontraditional” fathers (e.g., foster fathers), has significantly lagged . Thus, this collection of articles, Contextualizing Theoretical and Methodological Perspectives on Ethnic Minority and Diverse Fathers, includes five papers that challenge contemporary theories and methodologies to bring greater insights into the complexities of fathering and fatherhood. These articles are intended to encourage researchers to critically reflect on the contexts and diversity of fathers (e.g., immigrant, diverse ethnic backgrounds) and whether theories need to be modified or components of the theory need greater attention to be more reflective of fathers of today.

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)0.022
metaresearch head score (Gemma)0.025
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.022
Threshold uncertainty score0.115

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0220.025
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.004
Science and technology studies0.0020.004
Scholarly communication0.0050.010
Open science0.0010.003
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.0040.001

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 head0.240
GPT teacher head0.462
Teacher spread0.222 · 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 designTheoretical or conceptual
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

Citations6
Published2021
Admission routes1
Has abstractyes

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