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Record W1968319261 · doi:10.1017/s0021932011000411

MONTH OF BIRTH, SOCIOECONOMIC BACKGROUND AND HEIGHT IN RURAL CHINESE MEN

2011· article· en· W1968319261 on OpenAlex
William Zhang

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

VenueJournal of Biosocial Science · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicDemographic Trends and Gender Preferences
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsSocioeconomic statusDemographySocial classGeographyRural areaMedicinePopulationSociologyEconomics

Abstract

fetched live from OpenAlex

This study examines the effects of birth month and socioeconomic factors on height in rural Chinese men. The analysis of sample data of 833 adult men, 18-52 years of age, collected from 600 families in rural Hebei in 2005, shows that adult men born in winter months (November to January) are, on average, 1.04 cm shorter (p<0.01) than those born during the rest of the year. In addition to the conventional OLS regression models, the household fixed and random effects models also indicate that the month-of-birth effect exists when socioeconomic variables are controlled for. The birth-month effect on height is, however, smaller than effects of socioeconomic variables, including the household registration status, household economy and father's class status.

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)0.002
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 score0.119
Threshold uncertainty score0.657

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.002
Scholarly communication0.0000.001
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 head0.039
GPT teacher head0.310
Teacher spread0.271 · 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