MétaCan
Menu
Back to cohort
Record W1541151344

Saudi Scholars' Heritage Language and Their Ethno-Cultural Identity in Multilingual Communities: An Exploratory Case Study

2015· article· en· W1541151344 on OpenAlexvenueno aff
Najlaa S. Al-Ghamdi

Bibliographic record

VenueCross-cultural communication · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicMultilingual Education and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsMulticulturalismHeritage languageEthnic groupCultural identityIdentity (music)Cultural heritageTheme (computing)SociologyGender studiesCultural diversityAnthropologySocial scienceAestheticsPolitical sciencePedagogyArt
DOInot available

Abstract

fetched live from OpenAlex

Immigrant students’ linguistic, cultural and ethnic diversity is considered an issue of significance that speaks to the need for more rigorous research, especially in multicultural and multilingual societies. This paper highlights Saudi scholars’ heritage language and the relationship thereof to their ethnic and culture identity and its maintenance dynamics in a multilingual and multicultural society.Employing a case study approach and interviews, the researcher sought to identify the impact of Saudi scholars’ ethno-cultural identity on their heritage language. Analysis of data revealed three broad themes that emerged from the interviews: The first theme indicated that participants of both genders developed a dual cultural identity. The second theme indicated that the proficiency of Arabian scholars and their offspring had a strong impact on the ethno-cultural identity of the parents and the children born and raised in the USA. Third, negative stereotypes could be a potential cause for cultural identity clash. These broad themes seemed to be incongruous with the intricacies identified with cultural and ethnic identity maintenance mechanisms and their impact on heritage language speakers. The results have been discussed with relevance to prior studies and the theoretical framework.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.347
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0010.005
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.182
GPT teacher head0.526
Teacher spread0.343 · 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.

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

Citations2
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueCross-cultural communicationSame topicMultilingual Education and PolicyFrench-language works237,207