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Arranged Marriages (in<scp>S</scp>outh<scp>A</scp>sia)

2016· other· en· W2975930019 on OpenAlexaffabout
Arshia U. Zaidi

Bibliographic record

VenueThe Wiley Blackwell Encyclopedia of Gender and Sexuality Studies · 2016
Typeother
Languageen
FieldSocial Sciences
TopicMigration and Labor Dynamics
Canadian institutionsOntario Tech University
Fundersnot available
KeywordsCollectivismEthnic groupSociocultural evolutionModernization theoryImmigrationIndividualismCultural assimilationSociologyGender studiesPolitical scienceGeographyAnthropology

Abstract

fetched live from OpenAlex

There has been internationally growing concern about the cultural practice and custom of arranged marriages. With the rise in detraditionalization or modernization of the South Asian family's collectivistic cultural norms, values, and practices, this way of marriage has ignited new dialogue between generations. This is most prevalent for those born and raised in individualistic (host) societies in the West (i.e., Canada, the United States, and the United Kingdom). While youth in the heritage country are also engaged in this conversational exchange about arranged marriages, this occurs to a much lesser degree, as confirmed by recent cross‐cultural and/or ethnic studies. Despite modernization, there are still immigrant South Asian families in the West who hold strong beliefs in favor of the practice. Thus, arranged marriages persist as a major social institution across much of Asia and among ethnic minorities in Western countries and are perceived as the sociocultural norm in South Asian families.

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.275
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.039
GPT teacher head0.326
Teacher spread0.287 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2016
Admission routes2
Has abstractyes

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