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Record W4210621494 · doi:10.1111/sifp.12185

Child Marriage in Mainland China

2022· article· en· W4210621494 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

VenueStudies in Family Planning · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicDemographic Trends and Gender Preferences
Canadian institutionsMcGill University Health CentreUniversity of British ColumbiaMcGill University
Fundersnot available
KeywordsDemographyMainland ChinaChinaGeographyBeijingInequalityChild marriagePopulationSocioeconomicsSociology

Abstract

fetched live from OpenAlex

Child marriage, defined as marriage before 18 years of age, has harmful consequences for health and development and is an indicator of gender inequality. We used publicly available data from the 2000 and 2010 censuses to estimate the national and provincial-level prevalence of child marriage across mainland China. Between 2000 and 2010, the prevalence of child marriage rose from 2.41 percent to 2.85 percent among women and from 0.54 percent to 0.77 percent among men. The 2010 estimates are equivalent to roughly 1.8 million women and 0.5 million men. Child marriage was more common in western provinces among both girls and boys. Provincial prevalence estimates ranged from 0.44 percent in Beijing to 12.94 percent in Qinghai among girls. Among boys, estimates ranged from 0.13 percent in Beijing to 5.03 percent in Tibet. The gender gap widened across much of the country between censuses. Our results indicate that child marriage continues across mainland China despite laws that ostensibly prohibit the practice. They also draw attention to the global nature of child marriage as a threat to gender equality.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.292
Threshold uncertainty score0.680

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
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 head0.112
GPT teacher head0.379
Teacher spread0.268 · 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