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Record W3113354795 · doi:10.14434/ijlcle.v1i0.26824

Complexities of Immigrant Identity: Issues of Literacy, Language, and Culture in the Formation of Identity

2012· article· en· W3113354795 on OpenAlexaboutno aff
Bita Zakeri

Bibliographic record

VenueInternational Journal of Literacy Culture and Language Education · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicMultilingual Education and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsIdentity (music)Sociocultural evolutionAcculturationSociologyImmigrationMulticulturalismLiteracyDiversification (marketing strategy)Cultural identityGender studiesIdentity formationSocial identity theoryPedagogySocial scienceSocial groupPolitical scienceEthnic groupAestheticsSelf-conceptAnthropologyLaw

Abstract

fetched live from OpenAlex

Identity is an issue that everyone struggles with on a daily basis while constantly changing, adapting, and becoming agents of the social spheres in which we participate. At large, a society and its social demands mold us into becoming agents of that society. Literacy and education are at the heart of this social molding, from within the family sphere to the larger social spheres. But how can one reformat all the sociocultural training he/she has received in order to adapt to a new social sphere and simply change, lose, and gain identity? These questions are significant to multicultural societies such as US and Canada, and even more prevalent with respect to immigrant populations. Using autoethnographical data and literature in this area, this paper discusses the issues of immigrant identity and literacy in twofold: a) the lack of attention to immigration and acculturation phenomena; b) the importance of understanding immigrant students’ experiences and the need for diversification of teachers and teaching methods, concluding with suggestions for further research.

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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.070
Threshold uncertainty score0.694

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 communication0.0000.003
Open science0.0000.000
Research integrity0.0000.000
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 head0.027
GPT teacher head0.480
Teacher spread0.453 · 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 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

Citations0
Published2012
Admission routes1
Has abstractyes

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