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Discrimination History, Backlash Fear, and Ethnic Identity Among Arab Americans: Post‐9/11 Snapshots

2011· article· es· W2028511883 on OpenAlexaff
Sylvia C. Nassar‐McMillan, Richard G. Lambert, Julie Hakim‐Larson

Bibliographic record

VenueJournal of Multicultural Counseling and Development · 2011
Typearticle
Languagees
FieldSocial Sciences
TopicRacial and Ethnic Identity Research
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsEthnic groupAcculturationIdentity (music)BacklashPsychologyHumanitiesGender studiesSocial psychologySociologyArtAnthropology

Abstract

fetched live from OpenAlex

The authors examined discrimination history, backlash fear, and ethnic identity of Arab Americans nationally at 3 times, beginning shortly after September 11, 2001. Relations between variables were moderate, and discrimination history and backlash fear were statistically significant predictors of ethnic identity. Implications for acculturation and ethnic identity are discussed. Los autores examinaron la historia de la discriminación, el miedo a las reacciones violentas, y la identidad étnica de individuos Americanos de origen Árabe a nivel nacional en 3 momentos distintos, comenzando poco tiempo después del 11 de Septiembre de 2001. Las relaciones entre las variables fueron moderadas, y la historia de la discriminación y el miedo a las reacciones violentas pronosticaron con una fiabilidad estadísticamente significativa el nivel de identidad étnica. Se discuten las implicaciones para la aculturación y la identidad étnica.

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)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.037
Threshold uncertainty score0.073

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
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 head0.099
GPT teacher head0.348
Teacher spread0.250 · 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 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

Citations37
Published2011
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Multicultural Counseling and DevelopmentSame topicRacial and Ethnic Identity ResearchFrench-language works237,207