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Record W4385969766 · doi:10.1080/00324728.2023.2233964

Age-specific sex ratios: Examining rural–urban variation within low- and middle-income countries

2023· article· en· W4385969766 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

VenuePopulation Studies · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicDemographic Trends and Gender Preferences
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsSex ratioDemographyLatin AmericansGeographyRural areaDivergence (linguistics)Demographic economicsSocioeconomicsPopulationEconomicsSociologyPolitical science

Abstract

fetched live from OpenAlex

The balance of men and women in society, captured by sex ratios, determines key social and demographic phenomena. Previous research has explored sex ratios mainly at birth and up to age five at national level, whereas we address rural-urban gaps in sex ratios for all ages. Our measures are based on the United Nations data on rural and urban populations by age and sex for 112 low- and middle-income countries in 2015. We show that rural sex ratios are higher than urban sex ratios among children and older people, whereas at working ages, urban areas are dominated by males. Our analysis suggests that the urban transition itself is not driving the gap in rural-urban sex ratios. Rather, internal migration seems to be key in shaping rural-urban sex ratio divergence in sub-Saharan Africa, while both internal migration and mortality differentials appear to be the predominant mechanisms driving sex ratio gaps in Latin America.

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 score0.176
Threshold uncertainty score0.850

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 head0.131
GPT teacher head0.342
Teacher spread0.211 · 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