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Record W2166699890 · doi:10.1177/0022022114532358

Intergenerational Conflict Management in Immigrant Arab Canadian Families

2014· article· en· W2166699890 on OpenAlexaffabout
Sarah Rasmi, Timothy M. Daly, Susan S. Chuang

Bibliographic record

VenueJournal of Cross-Cultural Psychology · 2014
Typearticle
Languageen
FieldPsychology
TopicAttachment and Relationship Dynamics
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsImmigrationHonorConflict managementSocial psychologyContext (archaeology)PopulationConflict resolutionSalientConflict resolution researchPsychologyStyle (visual arts)Cultural conflictSociologyDevelopmental psychologyPolitical scienceDemographyGeographySocial science

Abstract

fetched live from OpenAlex

The present studies bridged across the conflict management and family psychology literatures to increase our understanding of intergenerational conflict within the context of immigrant Arab Canadian families. Using a quantitative approach, Study 1 ( n = 71) found that although emerging adults reported relatively low levels of intergenerational conflict, honor-related conflict issues were salient to this population and not captured by the Intergenerational Conflict Inventory. Study 1 also found that emerging adults’ preferred conflict handling style was associated with overall levels of intergenerational conflict as well as cultural orientation and adaptation. Three conflict handling styles (avoid, integrate, and dominate) were associated with increased intergenerational conflict, whereas oblige was associated with decreased intergenerational conflict. These results were confirmed using a qualitative approach in Study 2 ( n = 12). Importantly, Study 2 also suggested that oblige took two distinct forms in this population, as some emerging adults actually obliged their parents in the conflict situation, whereas others stated that they would but covertly disobeyed their parents.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.140
Threshold uncertainty score0.708

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.035
GPT teacher head0.449
Teacher spread0.414 · 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.

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

Citations22
Published2014
Admission routes2
Has abstractyes

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