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Record W2605243423 · doi:10.3138/jcfs.39.2.187

“I Hardly Understand English, But…”: Mexican Origin Fathers Describe Their Commitment as Fathers Despite the Challenges of Immigration

2008· article· en· W2605243423 on OpenAlexvenueno aff
Andrew O. Behnke, Brent A. Taylor, José Rubén Parra‐Cardona

Bibliographic record

VenueJournal of Comparative Family Studies · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicMigration and Labor Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsImmigrationSalientMeaning (existential)Developmental psychologyFace (sociological concept)Social psychologyGrounded theoryPsychologySociologyGender studiesPolitical scienceQualitative researchSocial science

Abstract

fetched live from OpenAlex

Interviews with 19 Mexican origin fathers in two parts of the United States examined how these men describe their parenting practices and give meaning to their involvement with their children. A grounded theory approach guided by ecological theory revealed salient themes, which included immigration, parental involvement, discipline, decision-making, parenting roles and relationships with their children. Present findings described the important ways in which the experience of immigration influences the fathering experiences of Mexican origin fathers. Such findings challenge traditional stereotypes that depict Mexican origin fathers as uninvolved and emotionally unavailable. In addition, data from this study illustrate that despite the challenges of fathering in the face of immigration challenges, fathers in this sample remain highly committed to their children and their families. Overall, results showed that cultural changes related to immigration were multidimensional and that both social and cultural variables have unique relations to Mexican immigrant fathering practices.

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)0.003
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.002
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.001
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 head0.197
GPT teacher head0.371
Teacher spread0.175 · 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 designQualitative
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

Citations64
Published2008
Admission routes1
Has abstractyes

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