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Record W2997714004 · doi:10.1177/0731121419895006

Successful yet Precarious: South Asian Muslim Americans, Islamophobia, and the Model Minority Myth

2019· article· en· W2997714004 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueSociological Perspectives · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Ethnicity, and Economy
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsIslamophobiaGender studiesPoliticsMythologyEthnographyVulnerability (computing)SociologyModel minorityFeelingRace (biology)Political scienceEthnic groupAsian americansSocial psychologyPsychology

Abstract

fetched live from OpenAlex

Precariousness is the notion that unstable and temporary employment can induce feelings of vulnerability and insecurity. As a “successful” minority because of their high education levels and economic attainments, South Asian Americans can hardly be described as precarious. However, ethnographic observations reveal a collective precariousness felt by this group. Despite measures of success, their positionality as a racialized and stigmatized religious “Other” induces in them an insecurity akin to that felt by those un(der)employed. They fear that despite their achievements, they can be discriminated against in their workplace because of their race and religion. This anxiety influences their education and career choices, and political engagements. Theoretically, precariousness is largely conceptualized as a phenomenon contained within national borders. However, South Asian Muslim Americans’ precariousness is influenced by that of Muslims of other nationalities abroad, underscoring the transnational dimension of precariousness and how it can extend beyond immediate networks and physical borders.

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.

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 score0.094
Threshold uncertainty score0.955

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 studies0.0010.003
Scholarly communication0.0000.000
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 head0.023
GPT teacher head0.290
Teacher spread0.267 · 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