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Record W1978373368 · doi:10.1080/10911359.2014.848679

Arab American Marriage: Culture, Tradition, Religion, and the Social Worker

2014· article· en· W1978373368 on OpenAlexaff
Alean Al‐Krenawi, Stephen O. Jackson

Bibliographic record

VenueJournal of Human Behavior in the Social Environment · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicMarriage and Sexual Relationships
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsHonorSociologyStigma (botany)Gender studiesPopulationContext (archaeology)Social workSocial stigmaSocial psychologyPolitical sciencePsychologyLawMedicineGeography

Abstract

fetched live from OpenAlex

The growing and varied Arab American population and the continuing stereotyping and mistrust between people of Arab descent and other Americans make the need for culturally competent social work more pronounced. This study considers the importance the institutions of marriage and family retain within what can be a generally high-context community. Marriage, family, and religious relationships can be complicated by a sense of honor and stigma alongside frequently distressing experiences or news from the country of origin. Various generations of Arab Americans are returning with their Middle Eastern counterparts to their religions to reestablish their identities. We shall consider the problems between fundamental and enlightened readings and understandings of the traditional marriage contract, especially under Sharia law, and traditional gender roles in relation to the varied expectations of the bride and groom, the extended families, and the cultural community. We suggest ways that social workers can develop skillful communications within effective cultural community networks to offset both inappropriate and insensitive misdiagnosis and treatment.

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)0.003
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.003
Scholarly communication0.0020.001
Open science0.0000.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.033
GPT teacher head0.325
Teacher spread0.292 · 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

Citations30
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Human Behavior in the Social EnvironmentSame topicMarriage and Sexual RelationshipsFrench-language works237,207